RDF Primer — Turtle version

2.1 Basic Concepts

Imagine trying to state that someone named John Smith created a particular Web page. A straightforward way to state this in a natural language such as English would be in the form of a simple statement such as:

http://www.example.org/index.html has a creator whose value is John Smith

Parts of this statement are emphasized to illustrate that, in order to describe the properties of something, there need to be ways to name, or identify, a number of things:

• the thing the statement describes (the Web page, in this case)
• a specific property (creator, in this case) of the thing the statement describes
• the thing the statement says is the value of this property (who the creator is), for the thing the statement describes

In this statement, the Web page's URL (Uniform Resource Locator) is used to identify it. In addition, the word "creator" is used to identify the property, and the two words "John Smith" to identify the thing (a person) that is the value of this property.

Other properties of this Web page could be described by writing additional English statements of the same general form, using the URL to identify the page, and words (or other expressions) to identify the properties and their values. For example, the date the page was created, and the language in which the page is written, could be described using the additional statements:

http://www.example.org/index.html has a creation-date whose value is August 16, 1999
http://www.example.org/index.html has a language whose value is English

RDF is based on the idea that the things being described have properties which have values, and that resources can be described by making statements, similar to those above, that specify those properties and values. RDF uses a particular terminology for talking about the various parts of statements. Specifically, the part that identifies the thing the statement is about (the Web page in this example) is called the subject. The part that identifies the property or characteristic of the subject that the statement specifies (creator, creation-date, or language in these examples) is called the predicate, and the part that identifies the value of that property is called the object. So, taking the English statement

http://www.example.org/index.html has a creator whose value is John Smith

the RDF terms for the various parts of the statement are:

• the subject is the URL http://www.example.org/index.html
• the predicate is the word "creator"
• the object is the phrase "John Smith"

However, while English is good for communicating between (English-speaking) humans, RDF is about making machine-processable statements. To make these kinds of statements suitable for processing by machines, two things are needed:

• a system of machine-processable identifiers for identifying a subject, predicate, or object in a statement without any possibility of confusion with a similar-looking identifier that might be used by someone else on the Web.
• a machine-processable language for representing these statements and exchanging them between machines.

Fortunately, the existing Web architecture provides both these necessary facilities.

As illustrated earlier, the Web already provides one form of identifier, the Uniform Resource Locator (URL). A URL was used in the original example to identify the Web page that John Smith created. A URL is a character string that identifies a Web resource by representing its primary access mechanism (essentially, its network "location"). However, it is also important to be able to record information about many things that, unlike Web pages, do not have network locations or URLs.

The Web provides a more general form of identifier for these purposes, called the Uniform Resource Identifier (URI). URLs are a particular kind of URI. All URIs share the property that different persons or organizations can independently create them, and use them to identify things. However, URIs are not limited to identifying things that have network locations, or use other computer access mechanisms. In fact, a URI can be created to refer to anything that needs to be referred to in a statement, including

• network-accessible things, such as an electronic document, an image, a service (e.g., "today's weather report for Los Angeles"), or a group of other resources.
• things that are not network-accessible, such as human beings, corporations, and bound books in a library.
• abstract concepts that do not physically exist, such as the concept of a "creator".

Because of this generality, RDF uses URIs as the basis of its mechanism for identifying the subjects, predicates, and objects in statements. To be more precise, RDF uses URI references [URIS]. A URI reference (or URIref) is a URI, together with an optional fragment identifier at the end. For example, the URI reference http://www.example.org/index.html#section2 consists of the URI http://www.example.org/index.html and (separated by the "#" character) the fragment identifier Section2. RDF URIrefs can contain Unicode [UNICODE] characters (see [RDF-CONCEPTS]), allowing many languages to be reflected in URIrefs. RDF defines a resource as anything that is identifiable by a URI reference, so using URIrefs allows RDF to describe practically anything, and to state relationships between such things as well. URIrefs and fragment identifiers are discussed further in Appendix A, and in [RDF-CONCEPTS].

To represent RDF statements in a machine-processable way, RDF normatively uses the Extensible Markup Language [XML], but other syntaxes are also possible. The XML serialization syntax (referrred to as RDF/XML) is described in a separate document [RDF-SYNTAX]. This document uses the Turtle syntax [TURTLE]. An example of Turtle was given in Section 1. Turtle content can contain Unicode [UNICODE] characters, allowing information from many languages to be directly represented. The specific Turtle syntax is defined in [TURTLE]

2.2 The RDF Model

Section 2.1 has introduced RDF's basic statement concepts, the idea of using URI references to identify the things referred to in RDF statements, and Turtle as a machine-processable way to represent RDF statements. With that background, this section describes how RDF uses URIs to make statements about resources. The introduction said that RDF was based on the idea of expressing simple statements about resources, where each statement consists of a subject, a predicate, and an object. In RDF, the English statement:

http://www.example.org/index.html has a creator whose value is John Smith

could be represented by an RDF statement having:

• a subject http://www.example.org/index.html
• a predicate http://purl.org/dc/elements/1.1/creator
• and an object http://www.example.org/staffid/85740

Note how URIrefs are used to identify not only the subject of the original statement, but also the predicate and object, instead of using the words "creator" and "John Smith", respectively (some of the effects of using URIrefs in this way will be discussed later in this section).

RDF models statements as nodes and arcs in a graph. RDF's graph model is defined in [RDF-CONCEPTS]. In this notation, a statement is represented by:

• a node for the subject
• a node for the object
• an arc for the predicate, directed from the subject node to the object node.

So the RDF statement above would be represented by the graph shown in Figure 2:

Figure 2: A Simple RDF Statement

Groups of statements are represented by corresponding groups of nodes and arcs. So, to reflect the additional English statements

http://www.example.org/index.html has a creation-date whose value is August 16, 1999
http://www.example.org/index.html has a language whose value is English

in the RDF graph, the graph shown in Figure 3 could be used (using suitable URIrefs to name the properties "creation-date" and "language"):

Figure 3: Several Statements About the Same Resource

Figure 3 illustrates that objects in RDF statements may be either URIrefs, or constant values (called literals) represented by character strings, in order to represent certain kinds of property values. (In the case of the predicate http://purl.org/dc/elements/1.1/language the literal is an international standard two-letter code for English.) Literals may not be used as subjects or predicates in RDF statements. In drawing RDF graphs, nodes that are URIrefs are shown as ellipses, while nodes that are literals are shown as boxes. (The simple character string literals used in these examples are called plain literals, to distinguish them from the typed literals to be introduced in Section 2.4. The various kinds of literals that can be used in RDF statements are defined in [RDF-CONCEPTS]. Both plain and typed literals can contain Unicode [UNICODE] characters, allowing information from many languages to be directly represented.)

Sometimes it is not convenient to draw graphs when discussing them, so an alternative way of writing down the statements, called triples, is also used. In the triples notation, each statement in the graph is written as a simple triple of subject, predicate, and object, in that order. For example, the three statements shown in Figure 3 would be written in the triples notation as:

<http://www.example.org/index.html> <http://purl.org/dc/elements/1.1/creator> <http://www.example.org/staffid/85740> .
<http://www.example.org/index.html> <http://www.example.org/terms/creation-date> "August 16, 1999" .
<http://www.example.org/index.html> <http://purl.org/dc/elements/1.1/language> "en" .

Each triple corresponds to a single arc in the graph, complete with the arc's beginning and ending nodes (the subject and object of the statement). Unlike the drawn graph (but like the original statements), the triples notation requires that a node be separately identified for each statement it appears in. So, for example, http://www.example.org/index.html appears three times (once in each triple) in the triples representation of the graph, but only once in the drawn graph. However, the triples represent exactly the same information as the drawn graph, and this is a key point: what is fundamental to RDF is the graph model of the statements. The notation used to represent or depict the graph is secondary.

The full triples notation requires that URI references be written out completely, in angle brackets, which, as the example above illustrates, can result in very long lines on a page. For convenience, the Primer uses a shorthand way of writing triples (the same shorthand is also used in other RDF specifications). This shorthand substitutes a qualified name (or QName) without angle brackets as an abbreviation for a full URI reference . A QName contains a prefix that has been assigned to a namespace URI, followed by a colon, and then a local name. The full URIref is formed from the QName by appending the local name to the namespace URI assigned to the prefix. So, for example, if the QName prefix foo is assigned to the namespace URI http://example.org/somewhere/, then the QName foo:bar is shorthand for the URIref http://example.org/somewhere/bar. Primer examples will also use several "well-known" QName prefixes (without explicitly specifying them each time), defined as follows:

prefix rdf:, namespace URI: http://www.w3.org/1999/02/22-rdf-syntax-ns#
prefix rdfs:, namespace URI: http://www.w3.org/2000/01/rdf-schema#
prefix dc:, namespace URI: http://purl.org/dc/elements/1.1/
prefix owl:, namespace URI: http://www.w3.org/2002/07/owl#
prefix ex:, namespace URI: http://www.example.org/ (or http://www.example.com/)
prefix xsd:, namespace URI: http://www.w3.org/2001/XMLSchema#

Obvious variations on the "example" prefix ex: will also be used as needed in the examples, for instance,

prefix exterms:, namespace URI: http://www.example.org/terms/ (for terms used by an example organization),
prefix exstaff:, namespace URI: http://www.example.org/staffid/ (for the example organization's staff identifiers),
prefix ex2:, namespace URI: http://www.domain2.example.org/ (for a second example organization), and so on.

Using this new shorthand, the previous set of triples can be written as:

ex:index.html  dc:creator             exstaff:85740 .
ex:index.html  exterms:creation-date  "August 16, 1999" .
ex:index.html  dc:language            "en" .

ex:index.html  dc:creator  exstaff:85740 .
ex:index.html  dc:creator  exstaff:27354 .
ex:index.html  dc:creator  exstaff:00816 .

These examples of RDF statements begin to illustrate some of the advantages of using URIrefs as RDF's basic way of identifying things. For instance, in the first statement, instead of identifying the creator of the Web page by the character string "John Smith", he has been assigned a URIref, in this case (using a URIref based on his employee number) http://www.example.org/staffid/85740 . An advantage of using a URIref in this case is that the identification of the statement's subject can be more precise. That is, the creator of the page is not the character string "John Smith", or any one of the thousands of people named John Smith, but the particular John Smith associated with that URIref (whoever created the URIref defines the association). Moreover, since there is a URIref to refer to John Smith, he is a full-fledged resource, and additional information can be recorded about him, simply by adding additional RDF statements with John's URIref as the subject. For example, Figure 4 shows some additional statements giving John's name and age.

Figure 4: More Information About John Smith

These examples also illustrate that RDF uses URIrefs as predicates in RDF statements. That is, rather than using character strings (or words) such as "creator" or "name" to identify properties, RDF uses URIrefs. Using URIrefs to identify properties is important for a number of reasons. First, it distinguishes the properties one person may use from different properties someone else may use that would otherwise be identified by the same character string. For instance, in the example in Figure 4, example.org uses "name" to mean someone's full name written out as a character string literal (e.g., "John Smith"), but someone else may intend "name" to mean something different (e.g., the name of a variable in a piece of program text). A program encountering "name" as a property identifier on the Web (or merging data from multiple sources) would not necessarily be able to distinguish these uses. However, if example.org writes http://www.example.org/terms/name for its "name" property, and the other person writes http://www.domain2.example.org/genealogy/terms/name for hers, it is clear that there are distinct properties involved (even if a program cannot automatically determine the distinct meanings). Also, using URIrefs to identify properties enables the properties to be treated as resources themselves. Since properties are resources, additional information can be recorded about them (e.g., the English description of what example.org means by "name"), simply by adding additional RDF statements with the property's URIref as the subject.

Using URIrefs as subjects, predicates, and objects in RDF statements supports the development and use of shared vocabularies on the Web, since people can discover and begin using vocabularies already used by others to describe things, reflecting a shared understanding of those concepts. For example, in the triple

ex:index.html   dc:creator   exstaff:85740 .

the predicate dc:creator, when fully expanded as a URIref, is an unambiguous reference to the "creator" attribute in the Dublin Core metadata attribute set (discussed further in Section 6.1), a widely-used set of attributes (properties) for describing information of all kinds. The writer of this triple is effectively saying that the relationship between the Web page (identified by http://www.example.org/index.html ) and the creator of the page (a distinct person, identified by http://www.example.org/staffid/85740 ) is exactly the concept identified by http://purl.org/dc/elements/1.1/creator. Another person familiar with the Dublin Core vocabulary, or who finds out what dc:creator means (say by looking up its definition on the Web) will know what is meant by this relationship. In addition, based on this understanding, people can write programs to behave in accordance with that meaning when processing triples containing the predicate dc:creator.

Of course, this depends on increasing the general use of URIrefs to refer to things instead of using literals; e.g., using URIrefs like exstaff:85740 and dc:creator instead of character string literals like John Smith and creator. Even then, RDF's use of URIrefs does not solve all identification problems because, for example, people can still use different URIrefs to refer to the same thing. For this reason, it is a good idea to try to use terms from existing vocabularies (such as the Dublin Core) where possible, rather than making up new terms that might overlap with those of some other vocabulary. Appropriate vocabularies for use in specific application areas are being developed all the time, as illustrated by the applications described in Section 6. However, even when synonyms are created, the fact that these different URIrefs are used in the commonly-accessible "Web space" provides the opportunity both to identify equivalences among these different references, and to migrate toward the use of common references.

ex:index.html  dc:creator  exstaff:85740 .

fy:joefy.iunm  ed:dsfbups  fytubgg:85740 .

The result of all this is that RDF provides a way to make statements that applications can more easily process. An application cannot actually "understand" such statements, as noted already, any more than a database system "understands" terms like "employee" or "salary" in processing a query like SELECT NAME FROM EMPLOYEE WHERE SALARY > 35000. However, if an application is appropriately written, it can deal with RDF statements in a way that makes it seem like it does understand them, just as a database system and its applications can do useful work in processing employee and payroll information without understanding "employee" and "payroll". For example, a user could search the Web for all book reviews and create an average rating for each book. Then, the user could put that information back on the Web. Another Web site could take that list of book rating averages and create a "Top Ten Highest Rated Books" page. Here, the availability and use of a shared vocabulary about ratings, and a shared group of URIrefs identifying the books they apply to, allows individuals to build a mutually-understood and increasingly-powerful (as additional contributions are made) "information base" about books on the Web. The same principle applies to the vast amounts of information that people create about thousands of subjects every day on the Web.

RDF statements are similar to a number of other formats for recording information, such as:

• entries in a simple record or catalog listing describing the resource in a data processing system.
• rows in a simple relational database.
• simple assertions in formal logic

and information in these formats can be treated as RDF statements, allowing RDF to be used to integrate data from many sources.

2.3 Structured Property Values and Blank Nodes

Things would be very simple if the only types of information to be recorded about things were obviously in the form of the simple RDF statements illustrated so far. However, most real-world data involves structures that are more complicated than that, at least on the surface. For instance, in the original example, the date the Web page was created is recorded as a single exterms:creation-date property, with a plain literal as its value. However, suppose the value of the exterms:creation-date property needed to record the month, day, and year as separate pieces of information? Or, in the case of John Smith's personal information, suppose John's address was being described. The whole address could be written out as a plain literal, as in the triple

exstaff:85740   exterms:address   "1501 Grant Avenue, Bedford, Massachusetts 01730" .

However, suppose John's address needed to be recorded as a structure consisting of separate street, city, state, and postal code values? How would this be done in RDF?

Structured information like this is represented in RDF by considering the aggregate thing to be described (like John Smith's address) as a resource, and then making statements about that new resource. So, in the RDF graph, in order to break up John Smith's address into its component parts, a new node is created to represent the concept of John Smith's address, with a new URIref to identify it, say http://www.example.org/addressid/85740 (abbreviated as exaddressid:85740). RDF statements (additional arcs and nodes) can then be written with that node as the subject, to represent the additional information, producing the graph shown in Figure 5:

Figure 5: Breaking Up John's Address

or the triples:

exstaff:85740       exterms:address    exaddressid:85740 .
exaddressid:85740   exterms:street     "1501 Grant Avenue" .
exaddressid:85740   exterms:city       "Bedford" .
exaddressid:85740   exterms:state      "Massachusetts" .
exaddressid:85740   exterms:postalCode "01730" .

This way of representing structured information in RDF can involve generating numerous "intermediate" URIrefs such as exaddressid:85740 to represent aggregate concepts such as John's address. Such concepts may never need to be referred to directly from outside a particular graph, and hence may not require "universal" identifiers. In addition, in the drawing of the graph representing the group of statements shown in Figure 5, the URIref assigned to identify "John Smith's address" is not really needed, since the graph could just as easily have been drawn as in Figure 6:

Figure 6: Using a Blank Node

Figure 6, which is a perfectly good RDF graph, uses a node without a URIref to stand for the concept of "John Smith's address". This blank node serves its purpose in the drawing without needing a URIref, since the node itself provides the necessary connectivity between the various other parts of the graph. (Blank nodes were called anonymous resources in [RDF-MS].) However, some form of explicit identifier for that node is needed in order to represent this graph as triples. To see this, trying to write the triples corresponding to what is shown in Figure 6 would produce something like:

exstaff:85740   exterms:address      ??? .
???             exterms:street       "1501 Grant Avenue" .
???             exterms:city         "Bedford" .
???             exterms:state        "Massachusetts" .
???             exterms:postalCode   "01730" .

where ??? stands for something that indicates the presence of the blank node. Since a complex graph might contain more than one blank node, there also needs to be a way to differentiate between these different blank nodes in a triples representation of the graph. As a result, triples use blank node identifiers, having the form _:name, to indicate the presence of blank nodes. For instance, in this example a blank node identifier _:johnaddress might be used to refer to the blank node, in which case the resulting triples might be:

exstaff:85740   exterms:address     _:johnaddress .
_:johnaddress   exterms:street      "1501 Grant Avenue" .
_:johnaddress   exterms:city        "Bedford" .
_:johnaddress   exterms:state       "Massachusetts" .
_:johnaddress   exterms:postalCode  "01730" .

In a triples representation of a graph, each distinct blank node in the graph is given a different blank node identifier. Unlike URIrefs and literals, blank node identifiers are not considered to be actual parts of the RDF graph (this can be seen by looking at the drawn graph in Figure 6 and noting that the blank node has no blank node identifier). Blank node identifiers are just a way of representing the blank nodes in a graph (and distinguishing one blank node from another) when the graph is written in triple form. Blank node identifiers also have significance only within the triples representing a single graph (two different graphs with the same number of blank nodes might independently use the same blank node identifiers to distinguish them, and it would be incorrect to assume that blank nodes from different graphs having the same blank node identifiers are the same). If it is expected that a node in a graph will need to be referenced from outside the graph, a URIref should be assigned to identify it. Finally, because blank node identifiers represent (blank) nodes, rather than arcs, in the triple form of an RDF graph, blank node identifiers may only appear as subjects or objects in triples; blank node identifiers may not be used as predicates in triples.

The beginning of this section noted that aggregate structures, like John Smith's address, can be represented by considering the aggregate thing to be described as a separate resource, and then making statements about that new resource. This example illustrates an important aspect of RDF: RDF directly represents only binary relationships, e.g. the relationship between John Smith and the literal representing his address. Representing the relationship between John and the group of separate components of this address involves dealing with an n-ary (n-way) relationship (in this case, n=5) between John and the street, city, state, and postal code components. In order to represent such structures directly in RDF (e.g., considering the address as a group of street, city, state, and postal code components), this n-way relationship must be broken up into a group of separate binary relationships. Blank nodes provide one way to do this. For each n-ary relationship, one of the participants is chosen as the subject of the relationship (John in this case), and a blank node is created to represent the rest of the relationship (John's address in this case). The remaining participants in the relationship (such as the city in this example) are then represented as separate properties of the new resource represented by the blank node.

Blank nodes also provide a way to more accurately make statements about resources that may not have URIs, but that are described in terms of relationships with other resources that do have URIs. For example, when making statements about a person, say Jane Smith, it may seem natural to use a URI based on that person's email address as her URI, e.g., mailto:jane@example.org. However, this approach can cause problems. For example, it may be necessary to record information both about Jane's mailbox (e.g., the server it is on) as well as about Jane herself (e.g., her current physical address), and using a URIref for Jane based on her email address makes it difficult to know whether it is Jane or her mailbox that is being described. The same problem exists when a company's Web page URL, say http://www.example.com/, is used as the URI of the company itself. Once again, it may be necessary to record information about the Web page itself (e.g., who created it and when) as well as about the company, and using http://www.example.com/ as an identifier for both makes it difficult to know which of these is the actual subject.

The fundamental problem is that using Jane's mailbox as a stand-in for Jane is not really accurate: Jane and her mailbox are not the same thing, and hence they should be identified differently. When Jane herself does not have a URI, a blank node provides a more accurate way of modeling this situation. Jane can be represented by a blank node, and that blank node used as the subject of a statement with exterms:mailbox as the property and the URIref mailto:jane@example.org as its value. The blank node could also be described with an rdf:type property having a value of exterms:Person (types are discussed in more detail in the following sections), an exterms:name property having a value of "Jane Smith", and any other descriptive information that might be useful, as shown in the following triples:

_:jane   exterms:mailbox   <mailto:jane@example.org> .
_:jane   rdf:type          exterms:Person .
_:jane   exterms:name      "Jane Smith" .
_:jane   exterms:empID     "23748"  .
_:jane   exterms:age       "26" .

(Note that mailto:jane@example.org is written within angle brackets in the first triple. This is because mailto:jane@example.org is a full URIref in the mailto URI scheme, rather than a QName abbreviation, and full URIrefs must be enclosed in angle brackets in the triples notation.)

This says, accurately, that "there is a resource of type exterms:Person, whose electronic mailbox is identified by mailto:jane@example.org, whose name is Jane Smith, etc." That is, the blank node can be read as "there is a resource". Statements with that blank node as subject then provide information about the characteristics of that resource.

In practice, using blank nodes instead of URIrefs in these cases does not change the way this kind of information is handled very much. For example, if it is known that an email address uniquely identifies someone at example.org (particularly if the address is unlikely to be reused), that fact can still be used to associate information about that person from multiple sources, even though the email address is not the person's URI. In this case, if some RDF is found on the Web that describes a book, and gives the author's contact information as mailto:jane@example.org, it might be reasonable, combining this new information with the previous set of triples, to conclude that the author's name is Jane Smith. The point is that saying something like "the author of the book is mailto:jane@example.org" is typically a shorthand for "the author of the book is someone whose mailbox is mailto:jane@example.org". Using a blank node to represent this "someone" is just a more accurate way to represent the real world situation. (Incidentally, some RDF-based schema languages allow specifying that certain properties are unique identifiers of the resources they describe. This is discussed further in Section 5.5.)

ex2terms:book78354   rdf:type          ex2terms:Book .
ex2terms:book78354   ex2terms:author   "Jane Smith" .

ex2terms:book78354   rdf:type         ex2terms:Book .
ex2terms:book78354   ex2terms:author  _:author78354 .
_:author78354        rdf:type         ex2terms:Person .
_:author78354        ex2terms:name    "Jane Smith" .

2.4 Typed Literals

The last section described how to handle situations in which property values represented by plain literals had to be broken up into structured values to represent the individual parts of those literals. Using this approach, instead of, say, recording the date a Web page was created as a single exterms:creation-date property, with a single plain literal as its value, the value would be represented as a structure consisting of the month, day, and year as separate pieces of information, using separate plain literals to represent the corresponding values. However, so far, all constant values that serve as objects in RDF statements have been represented by these plain (untyped) literals, even when the intent is probably for the value of the property to be a number (e.g., the value of a year or age property) or some other kind of more specialized value.

For example, Figure 4 illustrated an RDF graph recording information about John Smith. That graph recorded the value of John Smith's exterms:age property as the plain literal "27", as shown in Figure 7:

Figure 7: Representing John Smith's Age

In this case, the hypothetical organization example.org probably intends for "27" to be interpreted as a number, rather than as the string consisting of the character "2" followed by the character "7" (since the literal represents the value of an "age" property). However, there is no information in Figure 7's graph that explicitly indicates that "27" should be interpreted as a number. Similarly, example.org also probably intends for "27" to be interpreted as a decimal number, i.e., the value twenty seven, rather than, say, as an octal number, i.e., the value twenty three. However, once again there is no information in Figure 7's graph that explicitly indicates this. Specific applications might be written with the understanding that they should interpret values of the exterms:age property as decimal numbers, but this would mean that proper interpretation of this RDF would depend on information not explicitly provided in the RDF graph, and hence on information that would not necessarily be available to other applications that might need to interpret this RDF.

The common practice in programming languages or database systems is to provide this additional information about how to interpret a literal by associating a datatype with the literal, in this case, a datatype like decimal or integer. An application that understands the datatype then knows, for example, whether the literal "10" is intended to represent the number ten, the number two, or the string consisting of the character "1" followed by the character "0", depending on whether the specified datatype is integer, binary, or string. (More specialized datatypes could also be used to include the units information mentioned at the end of Section 2.3, e.g., a datatype integerYears, although the Primer will not elaborate on this idea.) In RDF, typed literals are used to provide this kind of information.

An RDF typed literal is formed by pairing a string with a URIref that identifies a particular datatype. This results in a single literal node in the RDF graph with the pair as the literal. The value represented by the typed literal is the value that the specified datatype associates with the specified string. For example, using a typed literal, John Smith's age could be described as being the integer number 27 using the triple:

<http://www.example.org/staffid/85740>  <http://www.example.org/terms/age> "27"^^<http://www.w3.org/2001/XMLSchema#integer> .

or, using the QName simplification for writing long URIs:

exstaff:85740  exterms:age  "27"^^xsd:integer .

or as shown in Figure 8:

Figure 8: A Typed Literal for John Smith's Age

Similarly, in the graph shown in Figure 3 describing information about a Web page, the value of the page's exterms:creation-date property was written as the plain literal "August 16, 1999". However, using a typed literal, the creation date of the Web page could be explicitly described as being the date August 16, 1999, using the triple:

ex:index.html  exterms:creation-date  "1999-08-16"^^xsd:date .

or as shown in Figure 9:

Figure 9: A Typed Literal for a Web Page's Creation Date

Unlike typical programming languages and database systems, RDF has no built-in set of datatypes of its own, such as datatypes for integers, reals, strings, or dates. Instead, RDF typed literals simply provide a way to explicitly indicate, for a given literal, what datatype should be used to interpret it. The datatypes used in typed literals are defined externally to RDF, and identified by their datatype URIs. (There is one exception: RDF defines a built-in datatype with the URIref rdf:XMLLiteral to represent XML content as a literal value. This datatype is defined in [RDF-CONCEPTS], and its use is described in Section 4.5.) For instance, the examples in Figure 8 and Figure 9 use the datatypes integer and date from the XML Schema datatypes defined in XML Schema Part 2: Datatypes [XML-SCHEMA2]. An advantage of this approach is that it gives RDF the flexibility to directly represent information coming from different sources without the need to perform type conversions between these sources and a native set of RDF datatypes. (Type conversions would still be required when moving information between systems having different sets of datatypes, but RDF would impose no extra conversions into and out of a native set of RDF datatypes.)

Since the value that a given typed literal denotes is defined by the typed literal's datatype, and, with the exception of rdf:XMLLiteral, RDF does not define any datatypes, the actual interpretation of a typed literal appearing in an RDF graph (e.g., determining the value it denotes) must be performed by software that is written to correctly process not only RDF, but the typed literal's datatype as well. Effectively, this software must be written to process an extended language that includes not only RDF, but also the datatype, as part of its built-in vocabulary. This raises the issue of which datatypes will be generally available in RDF software. Generally, the XML Schema datatypes that are listed as suitable for use in RDF in [RDF-SEMANTICS] have a "first among equals" status in RDF. As noted already, the examples in Figure 8 and Figure 9 used some of these XML Schema datatypes, and the Primer will be using these datatypes in most of its other examples of typed literals as well (for one thing, XML Schema datatypes already have assigned URIrefs that can be used to refer to them, specified in [XML-SCHEMA2]). These XML Schema datatypes are treated no differently than any other datatype, but they are expected to be the most widely used, and therefore the most likely to be interoperable among different software. As a result, it is expected that much RDF software will also be written to process these datatypes. However, RDF software could be written to process other sets of datatypes as well, assuming they were determined to be suitable for use with RDF, as described already.

In general, RDF software may be called on to process RDF data that contains references to datatypes that the software has not been written to process, in which case there are some things the software will not be able to do. For one thing, with the exception of rdf:XMLLiteral, RDF itself does not define the URIrefs that identify datatypes. As a result, RDF software, unless it has been written to recognize specific URIrefs, will not be able to determine whether or not a URIref written in a typed literal actually identifies a datatype. Moreover, even when a URIref does identify a datatype, RDF itself does not define the validity of pairing that datatype with a particular literal. This validity can only be determined by software written to correctly process that particular datatype.

For example, the typed literal in the triple:

exstaff:85740  exterms:age  "pumpkin"^^xsd:integer .

or the graph shown in Figure 10:

Figure 10: An Invalid Typed Literal for John Smith's Age

is valid RDF, but obviously an error as far as the xsd:integer datatype is concerned, since "pumpkin" is not defined as being in the lexical space of xsd:integer. RDF software not written to process the xsd:integer datatype would not be able to recognize this error.

However, proper use of RDF typed literals provides more information about the intended interpretation of literal values, and hence makes RDF statements a better means of information exchange among applications.

2.5 Concepts Summary

Taken as a whole, RDF is basically simple: nodes-and-arcs diagrams interpreted as statements about things identified by URIrefs. This section has presented an introduction to these concepts. As noted earlier, the normative (i.e., definitive) RDF specification describing these concepts is RDF Concepts and Abstract Syntax [RDF-CONCEPTS], which should be consulted for further information. The formal semantics (meaning) of these concepts is defined in the (normative) RDF Semantics [RDF-SEMANTICS] document.

However, in addition to the basic techniques for describing things using RDF statements discussed so far, it should be clear that people or organizations also need a way to describe the vocabularies (terms) they intend to use in those statements, specifically, vocabularies for:

• describing types of things (like exterms:Person)
• describing properties (like exterms:age and exterms:creation-date), and
• describing the types of things that can serve as the subjects or objects of statements involving those properties (such as specifying that the value of an exterms:age property should always be an xsd:integer).

The basis for describing such vocabularies in RDF is the RDF Vocabulary Description Language 1.0: RDF Schema [RDF-VOCABULARY], which will be described in Section 5.

Additional background on the basic ideas underlying RDF, and its role in providing a general language for describing Web information, can be found in [WEBDATA]. RDF draws upon ideas from knowledge representation, artificial intelligence, and data management, including Conceptual Graphs, logic-based knowledge representation, frames, and relational databases. Some possible sources of background information on these subjects include [SOWA], [CG], [KIF], [HAYES], [LUGER], and [GRAY].

4.1 RDF Containers

There is often a need to describe groups of things: for example, to say that a book was created by several authors, or to list the students in a course, or the software modules in a package. RDF provides several predefined (built-in) types and properties that can be used to describe such groups.

First, RDF provides a container vocabulary consisting of three predefined types (together with some associated predefined properties). A container is a resource that contains things. The contained things are called members. The members of a container may be resources (including blank nodes) or literals. RDF defines three types of containers:

• rdf:Bag
• rdf:Seq
• rdf:Alt

A Bag (a resource having type rdf:Bag) represents a group of resources or literals, possibly including duplicate members, where there is no significance in the order of the members. For example, a Bag might be used to describe a group of part numbers in which the order of entry or processing of the part numbers does not matter.

A Sequence or Seq (a resource having type rdf:Seq) represents a group of resources or literals, possibly including duplicate members, where the order of the members is significant. For example, a Sequence might be used to describe a group that must be maintained in alphabetical order.

An Alternative or Alt (a resource having type rdf:Alt) represents a group of resources or literals that are alternatives (typically for a single value of a property). For example, an Alt might be used to describe alternative language translations for the title of a book, or to describe a list of alternative Internet sites at which a resource might be found. An application using a property whose value is an Alt container should be aware that it can choose any one of the members of the group as appropriate.

To describe a resource as being one of these types of containers, the resource is given an rdf:type property whose value is one of the predefined resources rdf:Bag, rdf:Seq, or rdf:Alt (whichever is appropriate). The container resource (which may either be a blank node or a resource with a URIref) denotes the group as a whole. The members of the container can be described by defining a container membership property for each member with the container resource as its subject and the member as its object. These container membership properties have names of the form rdf:_n , where n is a decimal integer greater than zero, with no leading zeros, e.g., rdf:_1, rdf:_2, rdf:_3, and so on, and are used specifically for describing the members of containers. Container resources may also have other properties that describe the container, in addition to the container membership properties and the rdf:type property.

It is important to understand that while these types of containers are described using predefined RDF types and properties, any special meanings associated with these containers, e.g., that the members of an Alt container are alternative values, are only intended meanings. These specific container types, and their definitions, are provided with the aim of establishing a shared convention among those who need to describe groups of things. All RDF does is provide the types and properties that can be used to construct the RDF graphs to describe each type of container. RDF has no more built-in understanding of what a resource of type rdf:Bag is than it has of what a resource of type ex:Tent (discussed in Section 3.2) is. In each case, applications must be written to behave according to the particular meaning involved for each type. This point will be expanded on in the following examples.

A typical use of a container is to indicate that the value of a property is a group of things. For example, to represent the sentence "Course 6.001 has the students Amy, Mohamed, Johann, Maria, and Phuong", the course could be described by giving it a s:students property (from an appropriate vocabulary) whose value is a container of type rdf:Bag (representing the group of students). Then, using the container membership properties, individual students could be identified as being members of that group, as in the RDF graph shown in Figure 14:

Figure 14: A Simple Bag Container Description

Since the value of the s:students property in this example is described as a Bag, there is no intended significance in the order given for the URIrefs of the students, even though the membership properties in the graph have integers in their names. It is up to applications creating and processing graphs that include rdf:Bag containers to ignore any (apparent) order in the names of the membership properties.

Example 12 describes the graph shown in Figure 14:

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix s:   <http://example.org/students/vocab#>.

<http://example.org/courses/6.001>
    s:students [
        a rdf:Bag;
        rdf:_1 <http://example.org/students/Amy>;
        rdf:_2 <http://example.org/students/Mohamed>;
        rdf:_3 <http://example.org/students/Johann>;
        rdf:_4 <http://example.org/students/Maria>;
        rdf:_5 <http://example.org/students/Phuong>.
    ].

The graph structure for an rdf:Seq container, and the corresponding Turtle, are similar to those for an rdf:Bag (the only difference is in the type, rdf:Seq). Once again, although an rdf:Seq container is intended to describe a sequence, it is up to applications creating and processing the graph to appropriately interpret the sequence of integer-valued property names.

Note that this example also shows a Turtle abbreviation for the property http://www.w3.org/1999/02/22-rdf-syntax-ns#type in the form of the special predicate name "a". Because using rdf typing is very frequent, this abbreviation is very useful in practice.

To illustrate an Alt container, the sentence "The source code for X11 may be found at ftp.example.org, ftp1.example.org, or ftp2.example.org" could be expressed in the RDF graph shown in Figure 15:

Figure 15: A Simple Alt Container Description

Example 13 shows how the graph in Figure 15 could be written in Turtle:

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix s:   <http://example.org/packages/vocab#>.

<http://example.org/packages/X11>
    s:DistributionSite [
        a rdf:Alt;
        rdf:_1 <ftp://ftp.example.org>;
        rdf:_2 <ftp://ftp1.example.org>;
        rdf:_3 <ftp://ftp2.example.org>.
    ].

An Alt container is intended to have at least one member, identified by the property rdf:_1. This member is intended to be considered as the default or preferred value. Other than the member identified as rdf:_1, the order of the remaining elements is not significant.

The RDF in Figure 15 as written states simply that the value of the s:DistributionSite site property is the Alt container resource itself. Any additional meaning that is to be read into this graph, e.g., that one of the members of the Alt container is to be considered as the value of the s:DistributionSite site property, or that ftp://ftp.example.org is the default or preferred value, must be built into an application's understanding of the intended meaning of an Alt container, and/or into the meaning defined for the particular property (s:DistributionSite in this case), which also must be understood by the application.

Alt containers are frequently used in conjunction with language tagging. (Turtle permits the use of a language tag to indicate that the element content is in a specified language. The use of this tag is described in [TURTLE], and illustrated later in Section 6.2.) For example, a work whose title has been translated into several languages might have its title property pointing to an Alt container holding literals representing the titles expressed in each of the language variants.

The distinction between the intended meanings of a Bag and an Alt can be further illustrated by considering the authorship of the book "Huckleberry Finn". The book has exactly one author, but the author has two names (Mark Twain and Samuel Clemens). Either name is sufficient to specify the author. Thus using an Alt container for the author's names more accurately represents the relationship than using a Bag (which might suggest there are two different authors).

Users are free to choose their own ways to describe groups of resources, rather than using the RDF container vocabulary. These RDF containers are merely provided as common definitions that, if generally used, could help make data involving groups of resources more interoperable.

Sometimes there are clear alternatives to using these RDF container types. For example, a relationship between a particular resource and a group of other resources could be indicated by making the first resource the subject of multiple statements using the same property. This is structurally different from the resource being the subject of a single statement whose object is a container containing multiple members. In some cases, these two structures may have equivalent meaning, but in other cases they may not. The choice of which to use in a given situation should be made with this in mind.

Consider as an example the relationship between a writer and her publications, as in the sentence:

Sue has written "Anthology of Time", "Zoological Reasoning", and "Gravitational Reflections".

In this case, there are three resources each of which was written independently by the same writer. This could be expressed using repeated properties as:

exstaff:Sue   exterms:publication   ex:AnthologyOfTime .
exstaff:Sue   exterms:publication   ex:ZoologicalReasoning .
exstaff:Sue   exterms:publication   ex:GravitationalReflections .

In this example there is no stated relationship between the publications other than that they were written by the same person. Each of the statements is an independent fact, and so using repeated properties would be a reasonable choice. However, this could just as reasonably be represented as a statement about the group of resources written by Sue:

exstaff:Sue   exterms:publication _:z
_:z           rdf:type            rdf:Bag .
_:z           rdf:_1              ex:AnthologyOfTime .
_:z           rdf:_2              ex:ZoologicalReasoning .
_:z           rdf:_3              ex:GravitationalReflections .

On the other hand, the sentence:

The resolution was approved by the Rules Committee, having members Fred, Wilma, and Dino.

says that the committee as a whole approved the resolution; it does not necessarily state that each committee member individually voted in favor of the resolution. In this case, it would be potentially misleading to model this sentence as three separate exterms:approvedBy statements, one for each committee member, as shown below:

ex:resolution   exterms:approvedBy   ex:Fred .
ex:resolution   exterms:approvedBy   ex:Wilma .
ex:resolution   exterms:approvedBy   ex:Dino .

since these statements say that each member individually approved the resolution.

In this case, it would be better to model the sentence as a single exterms:approvedBy statement whose subject is the resolution and whose object is the committee itself. The committee resource could then be described as a Bag whose members are the members of the committee, as in the following triples:

ex:resolution      exterms:approvedBy   ex:rulesCommittee .
ex:rulesCommittee  rdf:type             rdf:Bag .
ex:rulesCommittee  rdf:_1               ex:Fred .
ex:rulesCommittee  rdf:_2               ex:Wilma .
ex:rulesCommittee  rdf:_3               ex:Dino .

When using RDF containers, it is important to understand that the statements are not constructing containers, as in a programming language data structure. Instead, the statements are describing containers (groups of things) that presumably exist. For instance, in the Rules Committee example just given, the Rules Committee is an unordered group of people, whether it is described in RDF that way or not. Saying that the resource ex:rulesCommittee has type rdf:Bag is not saying that the Rules Committee is a data structure, or constructing a particular data structure to hold the members of the group (the Rules Committee could be described as a Bag without describing any members at all). Instead, it is describing the Rules Committee as having characteristics corresponding to those associated with a Bag container, namely that it has members, and their order of description is not significant. Similarly, using the container membership properties simply describes a container resource as having certain things as members. This does not necessarily say that the things described as members are the only members that exist. For example, the triples given above to describe the Rules Committee say only that Fred, Wilma, and Dino are members of the committee, not that they are the only members of the committee.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix s:   <http://example.org/packages/vocab#>.

<http://example.org/packages/X11>
    s:DistributionSite [
        a rdf:Alt;
        a rdf:Bag;
        rdf:_2 <ftp://ftp.example.org>;
        rdf:_2 <ftp://ftp1.example.org>;
        rdf:_5 <ftp://ftp2.example.org>
    ].

4.2 RDF Collections

A limitation of the containers described in Section 4.1 is that there is no way to close them, i.e., to say "these are all the members of the container". As noted in Section 4.1, a container only says that certain identified resources are members; it does not say that other members do not exist. Also, while one graph may describe some of the members, there is no way to exclude the possibility that there is another graph somewhere that describes additional members. RDF provides support for describing groups containing only the specified members, in the form of RDF collections. An RDF collection is a group of things represented as a list structure in the RDF graph. This list structure is constructed using a predefined collection vocabulary consisting of the predefined type rdf:List, the predefined properties rdf:first and rdf:rest, and the predefined resource rdf:nil.

To illustrate this, the sentence "The students in course 6.001 are Amy, Mohamed, and Johann" could be represented using the graph shown in Figure 16:

Figure 16: An RDF Collection (list structure)

In this graph, each member of the collection, such as s:Amy, is the object of an rdf:first property whose subject is a resource (a blank node in this example) that represents a list. This list resource is linked to the rest of the list by an rdf:rest property. The end of the list is indicated by the rdf:rest property having as its object the resource rdf:nil (the resource rdf:nil represents the empty list, and is defined as being of type rdf:List). This structure will be familiar to those who know the Lisp programming language. As in Lisp, the rdf:first and rdf:rest properties allow applications to traverse the structure. Each of the blank nodes forming this list structure is implicitly of type rdf:List (that is, each of these nodes implicitly has an rdf:type property whose value is the predefined type rdf:List), although this is not explicitly shown in the graph. The RDF Schema language [RDF-VOCABULARY] defines the properties rdf:first and rdf:rest as having subjects of type rdf:List, so the information about these nodes being lists can generally be inferred, rather than the corresponding rdf:type triples being written out all the time.

Turtle provides a special notation to make it easy to describe collections using graphs of this form. To illustrate how this notation works, the Turtle from Example 15 would result in the RDF graph shown in Figure 16:

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix s:   <http://example.org/students/vocab#>.

<http://example.org/courses/6.001>
    s:students (
        <http://example.org/students/Amy>
        <http://example.org/students/Mohamed>
        <http://example.org/students/Johann>
    ).

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix s:   <http://example.org/students/vocab#>.

<http://example.org/courses/6.001> s:student _:sch1.

_:sch1 
    rdf:first <http://example.org/students/Amy>;
    rdf:rest  _:sch2.
        
_:sch2 
    rdf:first <http://example.org/students/Mohamed>;
    rdf:rest  _:sch3.

_:sch3 
    rdf:first <http://example.org/students/Johann>;
    rdf:rest  rdf:nil.

4.3 RDF Reification

RDF applications sometimes need to describe other RDF statements using RDF, for instance, to record information about when statements were made, who made them, or other similar information (this is sometimes referred to as "provenance" information). For example, Example 9 in Section 3.2 described a particular tent with URIref exproducts:item10245, offered for sale by example.com. One of the triples from that description, describing the weight of the tent, was:

exproducts:item10245   exterms:weight   "2.4"^^xsd:decimal .

and it might be useful for example.com to record who provided that particular piece of information.

RDF provides a built-in vocabulary intended for describing RDF statements. A description of a statement using this vocabulary is called a reification of the statement. The RDF reification vocabulary consists of the type rdf:Statement, and the properties rdf:subject, rdf:predicate, and rdf:object. However, while RDF provides this reification vocabulary, care is needed in using it, because it is easy to imagine that the vocabulary defines some things that are not actually defined. This point will be discussed further later in this section.

Using the reification vocabulary, a reification of the statement about the tent's weight would be given by assigning the statement a URIref such as exproducts:triple12345 (so statements can be written describing it), and then describing the statement using the statements:

exproducts:triple12345  rdf:type        rdf:Statement .
exproducts:triple12345  rdf:subject     exproducts:item10245 .
exproducts:triple12345  rdf:predicate   exterms:weight .
exproducts:triple12345  rdf:object      "2.4"^^xsd:decimal .

These statements say that the resource identified by the URIref exproducts:triple12345 is an RDF statement, that the subject of the statement refers to the resource identified by exproducts:item10245, the predicate of the statement refers to the resource identified by exterms:weight, and the object of the statement refers to the decimal value identified by the typed literal "2.4"^^xsd:decimal. Assuming that the original statement is actually identified by exproducts:triple12345, it should be clear by comparing the original statement with the reification that the reification actually does describe it. The conventional use of the RDF reification vocabulary always involves describing a statement using four statements in this pattern; the four statements are sometimes referred to as a "reification quad" for this reason.

Using reification according to this convention, example.com could record the fact that John Smith made the original statement about the tent's weight by first assigning the original statement a URIref (such as exproducts:triple12345 as before), describing that statement using the reification just described, and then adding an additional statement that exproducts:triple12345 was written by John Smith (using a URIref to identify which John Smith is being referred to). The resulting statements would be:

exproducts:triple12345   rdf:type        rdf:Statement .
exproducts:triple12345   rdf:subject     exproducts:item10245 .
exproducts:triple12345   rdf:predicate   exterms:weight .
exproducts:triple12345   rdf:object      "2.4"^^xsd:decimal .
exproducts:triple12345   dc:creator      exstaff:85740 . 

The original statement, together with the reification and the attribution of the statement to John Smith, forms the graph shown in Figure 17:

Figure 17: A Statement, Its Reification, and Its Attribution

Section 3.2 introduced the use of the Turtle shorthand for URIrefs. This can also be used in a property element to automatically produce a reification of the triple that the property element generates. Example 17 shows how this could be used to produce the same graph :

In this case, specifying the attribute :triple12345 in the exterms:weight element results in the original triple describing the tent's weight:

exproducts:item10245   exterms:weight   "2.4"^^xsd:decimal .

plus the reification triples:

exproducts:triple12345   rdf:type        rdf:Statement .
exproducts:triple12345   rdf:subject     exproducts:item10245 .
exproducts:triple12345   rdf:predicate   exterms:weight .
exproducts:triple12345   rdf:object      "2.4"^^xsd:decimal .

The subject of these reification triples is a URIref formed by concatenating the base URI of the document (given in the @base declaration), the character "#" (to indicate that what follows is a fragment identifier), and the value of the shorthand; that is, the triples have the same subject exproducts:triple12345 as in the previous examples.

Note that asserting the reification is not the same as asserting the original statement, and neither implies the other. That is, when someone says that John said something about the weight of a tent, they are not making a statement about the weight of a tent themselves, they are making a statement about something John said. Conversely, when someone describes the weight of a tent, they are not also making a statement about a statement they made (since they may have no intention of talking about things called "statements").

The text above deliberately referred in a number of places to "the conventional use of reification". As noted earlier, care is needed when using the RDF reification vocabulary because it is easy to imagine that the vocabulary defines some things that are not actually defined. While there are applications that successfully use reification, they do so by following some conventions, and making some assumptions, that are in addition to the actual meaning that RDF defines for the reification vocabulary, and the actual facilities that RDF provides to support it.

For one thing, it is important to note that in the conventional use of reification, the subject of the reification triples is assumed to identify a particular instance of a triple in a particular RDF document, rather than some arbitrary triple having the same subject, predicate, and object. This particular convention is used because reification is intended for expressing properties such as dates of composition and source information, as in the examples given already, and these properties need to be applied to specific instances of triples. There could be several triples that have the same subject, predicate, and object and, although a graph is defined as a set of triples, several instances with the same triple structure might occur in different documents. Thus, to fully support this convention, there needs to be some means of associating the subject of the reification triples with an individual triple in some document. However, RDF provides no way to do this.

For instance, in the examples above, there is no explicit information in either the triples or the Turtle code that actually indicates that the original statement describing the tent's weight is the resource exproducts:triple12345, the resource that is the subject of the four reification statements and the statement that John Smith created it. This can be seen by looking at the drawn graph shown in Figure 17. The original statement is certainly part of this graph, but as far as the information in the graph is concerned, exproducts:triple12345 is a separate resource, rather than identifying that part of the graph. RDF does not provide a built-in way of indicating how a URIref like exproducts:triple12345 is associated with a particular statement or graph, any more than it provides a built-in way of indicating how a URIref like exproducts:item10245 is associated with an actual tent. Associating specific URIrefs with specific resources (statements in this case) must be done using mechanisms outside of RDF.

Using URIrefs shorthand as shown in Example 17 generates the reification automatically, and provides a convenient way of indicating the URIref to be used as the subject of the statements in the reification. Moreover, it provides a partial "hook" relating the triples in the reification with the piece of Turtle syntax that caused them to be created, since the value triple12345 of the shorthand is used to generate the URIref of the subject of the reification triples. However, this relationship is once again outside RDF, since there is nothing in the resulting triples that explicitly says that the original triple had the URIref exproducts:triple12345 (RDF does not assume there is any relationship between a URIref and any Turtle code that it might have been used or abbreviated in).

The lack of a built-in means for assigning URIrefs to statements does not mean that "provenance" information of this kind cannot be expressed in RDF, just that it cannot be done using only the meaning RDF associates with the reification vocabulary. For example, if an RDF document (say, a Web page) has a URI, statements could be made about the resource identified by that URI and, based on some application-dependent understanding of how those statements should be interpreted, an application could act as if those statements "distribute" over (apply equally to) all the statements in the document. Also, if some mechanism exists (outside of RDF) to assign URIs to individual RDF statements, then statements could certainly be made about those individual statements, using their URIs to identify them. However, in these cases, it would also not be strictly necessary to use the reification vocabulary in the conventional way.

To see this, assuming the original statement:

exproducts:item10245  exterms:weight  "2.4"^^xsd:decimal .

had a URIref of exproducts:triple12345, the statement could be attributed to John Smith simply by the statement:

exproducts:triple12345  dc:creator  exstaff:85740 .

with no use of the reification vocabulary (although the description of exproducts:triple12345 as having rdf:type rdf:Statement might also be helpful).

In addition, the reification vocabulary could be used directly according to the convention described above, along with an application-dependent understanding as to how to associate specific triples with their reifications. However, other applications receiving this RDF would not necessarily share this application-dependent understanding, and thus would not necessarily interpret the graphs appropriately.

It is also important to note that the interpretation of reification described here is not the same as "quotation", as found in some languages. Instead, the reification describes the relationship between a particular instance of a triple and the resources the triple refers to. The reification can be read intuitively as saying "this RDF triple talks about these things", rather than (as in quotation) "this RDF triple has this form." For instance, in the reification example used in this section, the triple:

exproducts:triple12345  rdf:subject  exproducts:item10245 .

describing the rdf:subject of the original statement says that the subject of the statement is the resource (the tent) identified by the URIref exproducts:item10245. It does not say that the subject of the statement is the URIref itself (i.e., a string beginning with certain characters), as quotation would do.

4.4 More on Structured Values: rdf:value

Section 2.3 noted that the RDF model intrinsically supports only binary relations; that is, a statement specifies a relation between two resources. For example, the statement:

exstaff:85740   exterms:manager   exstaff:62345 .

states that the relation exterms:manager holds between two employees (presumably one manages the other).

However, in some cases it is necessary to represent information involving higher arity relations (relations between more than two resources) in RDF. Section 2.3 discussed one example of this, where the problem was to represent the relationship between John Smith and his address information, and the value of John's address was a structured value of his street, city, state, and postal code. Writing this as a relation shows that this address is a 5-ary relation of the form:

address(exstaff:85740, "1501 Grant Avenue", "Bedford", "Massachusetts", "01730")

Section 2.3 noted that this kind of structured information can be represented in RDF by considering the aggregate thing be described (here, the group of components representing John's address) as a separate resource, and then making separate statements about that new resource, as in the triples:

exstaff:85740   exterms:address        _:johnaddress .
_:johnaddress   exterms:street         "1501 Grant Avenue" .
_:johnaddress   exterms:city           "Bedford" .
_:johnaddress   exterms:state          "Massachusetts" .
_:johnaddress   exterms:postalCode     "01730" .

(where _:johnaddress is the blank node identifier of the blank node representing John's address.)

This is a general way to represent any n-ary relation in RDF: select one of the participants (John in this case) to serve as the subject of the original relation (address in this case), then specify an intermediate resource to represent the rest of the relation (either with or without assigning it a URI), then give that new resource properties representing the remaining components of the relation.

In the case of John's address, none of the individual parts of the structured value could be considered the "main" value of the exterms:address property; all of the parts contribute equally to the value. However, in some cases one of the parts of the structured value is often thought of as the "main" value, with the other parts of the relation providing additional contextual or other information that qualifies the main value. For instance, in Example 9 in Section 3.2, the weight of a particular tent was given as the decimal value 2.4 using a typed literal, i.e.,

exproduct:item10245   exterms:weight   "2.4"^^xsd:decimal .

In fact, a more complete description of the weight would have been 2.4 kilograms rather than just the decimal value 2.4. To state this, the value of the exterms:weight property would need to have two components, the typed literal for the decimal value and an indication of the unit of measure (kilograms). In this situation the decimal value could be considered the "main" value of the exterms:weight property, because frequently the value would be recorded simply as the typed literal (as in the triple above), relying on an understanding of the context to fill in the unstated units information.

In the RDF model a qualified property value of this kind can be considered as simply another kind of structured value. To represent this, a separate resource could be used to represent the structured value as a whole (the weight, in this case), and to serve as the object of the original statement. That resource could then be given properties representing the individual parts of the structured value. In this case, there should be a property for the typed literal representing the decimal value, and a property for the unit. RDF provides a predefined rdf:value property to describe the main value (if there is one) of a structured value. So in this case, the typed literal could be given as the value of the rdf:value property, and the resource exunits:kilograms as the value of an exterms:units property (assuming the resource exunits:kilograms is defined as part of example.org's vocabulary). The resulting triples would be:

exproduct:item10245   exterms:weight   _:weight10245 .
_:weight10245         rdf:value        "2.4"^^xsd:decimal .
_:weight10245         exterms:units    exunits:kilograms .

The same approach can be used to represent quantities using any units of measure, as well as values taken from different classification schemes or rating systems, by using the rdf:value property to give the main value, and using additional properties to identify the classification scheme or other information that further describes the value.

There is no need to use rdf:value for these purposes (e.g., a user-defined property name, such as exterms:amount, could have been used instead of rdf:value), and RDF does not associate any special meaning with rdf:value. rdf:value is simply provided as a convenience for use in these commonly-occurring situations.

However, even though much existing data in databases and on the Web (and in later Primer examples) takes the form of simple values for properties such as weights, costs, etc., the principle that such simple values are often insufficient to adequately describe these values is an important one. In a global environment such as the Web, it is generally not safe to make the assumption that anyone accessing a property value will understand the units being used (or other contextually-dependent information that may be involved). For example, a U.S. site might give a weight value in pounds, but someone accessing that data from outside the U.S. might assume that weights are given in kilograms. The correct interpretation of data in the Web environment may require that additional information (such as units information) be explicitly recorded. This can be done in many ways, such as using rdf:value, building units into property names (e.g., exterms:weightInKg), defining specialized datatypes that include units information (e.g., extypes:kilograms), or adding additional user-defined properties to specify this information (e.g., exterms:unitOfWeight), either in descriptions of individual items or products, in descriptions of sets of data (e.g., all the data in a catalog or on a site), or in schemas (see Section 5).

5.1 Describing Classes

A basic step in any kind of description process is identifying the various kinds of things to be described. RDF Schema refers to these "kinds of things" as classes. A class in RDF Schema corresponds to the generic concept of a Type or Category, somewhat like the notion of a class in object-oriented programming languages such as Java. RDF classes can be used to represent almost any category of thing, such as Web pages, people, document types, databases or abstract concepts. Classes are described using the RDF Schema resources rdfs:Class and rdfs:Resource, and the properties rdf:type and rdfs:subClassOf.

For example, suppose an organization example.org wanted to use RDF to provide information about different kinds of motor vehicles. In RDF Schema, example.org would first need a class to represent the category of things that are motor vehicles. The resources that belong to a class are called its instances. In this case, example.org intends for the instances of this class to be resources that are motor vehicles.

In RDF Schema, a class is any resource having an rdf:type property whose value is the resource rdfs:Class. So the motor vehicle class would be described by assigning the class a URIref, say ex:MotorVehicle (using ex: to stand for the URIref http://www.example.org/schemas/vehicles, which is used as the prefix for URIrefs from example.org's vocabulary) and describing that resource with an rdf:type property whose value is the resource rdfs:Class. That is, example.org would write the RDF statement:

ex:MotorVehicle   rdf:type   rdfs:Class .

As indicated in Section 3.2, the property rdf:type is used to indicate that a resource is an instance of a class. So, having described ex:MotorVehicle as a class, resource exthings:companyCar would be described as a motor vehicle by the RDF statement:

exthings:companyCar   rdf:type   ex:MotorVehicle .

(This statement uses a common convention that class names are written with an initial uppercase letter, while property and instance names are written with an initial lowercase letter. However, this convention is not required in RDF Schema. The statement also assumes that example.org has decided to define separate vocabularies for classes of things, and instances of things.)

The resource rdfs:Class itself has an rdf:type of rdfs:Class. A resource may be an instance of more than one class.

After describing class ex:MotorVehicle, example.org might want to describe additional classes representing various specialized kinds of motor vehicle, e.g., passenger vehicles, vans, minivans, and so on. These classes can be described in the same way as class ex:MotorVehicle, by assigning a URIref for each new class, and writing RDF statements describing these resources as classes, e.g., writing:

ex:Van     rdf:type   rdfs:Class .
ex:Truck   rdf:type   rdfs:Class .

and so on. However, these statements by themselves only describe the individual classes. example.org may also want to indicate their special relationship to class ex:MotorVehicle, i.e., that they are specialized kinds of MotorVehicle.

This kind of specialization relationship between two classes is described using the predefined rdfs:subClassOf property to relate the two classes. For example, to state that ex:Van is a specialized kind of ex:MotorVehicle, example.org would write the RDF statement:

ex:Van   rdfs:subClassOf   ex:MotorVehicle .

The meaning of this rdfs:subClassOf relationship is that any instance of class ex:Van is also an instance of class ex:MotorVehicle. So if resource exthings:companyVan is an instance of ex:Van then, based on the declared rdfs:subClassOf relationship, RDF software written to understand the RDF Schema vocabulary can infer the additional information that exthings:companyVan is also an instance of ex:MotorVehicle.

This example of exthings:companyVan illustrates the point made earlier about RDF Schema defining an extended language. RDF itself does not define the special meaning of terms from the RDF Schema vocabulary such as rdfs:subClassOf. So if an RDF schema defines this rdfs:subClassOf relationship between ex:Van and ex:MotorVehicle, RDF software not written to understand the RDF Schema terms would recognize this as a triple, with predicate rdfs:subClassOf, but it would not understand the special significance of rdfs:subClassOf, and not be able to draw the additional inference that exthings:companyVan is also an instance of ex:MotorVehicle.

The rdfs:subClassOf property is transitive. This means, for example, that given the RDF statements:

ex:Van       rdfs:subClassOf   ex:MotorVehicle .
ex:MiniVan   rdfs:subClassOf   ex:Van .

RDF Schema defines ex:MiniVan as also being a subclass of ex:MotorVehicle. As a result, RDF Schema defines resources that are instances of class ex:MiniVan as also being instances of class ex:MotorVehicle (as well as being instances of class ex:Van). A class may be a subclass of more than one class (for example, ex:MiniVan may be a subclass of both ex:Van and ex:PassengerVehicle). RDF Schema defines all classes as subclasses of class rdfs:Resource (since the instances belonging to all classes are resources).

Figure 18 shows the full class hierarchy being discussed in these examples.

Figure 18: A Vehicle Class Hierarchy

(To simplify the figure, the rdf:type properties relating each of the classes to rdfs:Class are omitted in Figure 18. In fact, RDF Schema defines both the subjects and objects of statements that use the rdfs:subClassOf property to be resources of type rdfs:Class, so this information could be inferred. However, in actually writing schemas, it is good practice to explicitly provide this information.)

This schema could also be described by the triples:

ex:MotorVehicle       rdf:type          rdfs:Class .
ex:PassengerVehicle   rdf:type          rdfs:Class .
ex:Van                rdf:type          rdfs:Class .
ex:Truck              rdf:type          rdfs:Class .
ex:MiniVan            rdf:type          rdfs:Class .

ex:PassengerVehicle   rdfs:subClassOf   ex:MotorVehicle .
ex:Van                rdfs:subClassOf   ex:MotorVehicle .
ex:Truck              rdfs:subClassOf   ex:MotorVehicle .

ex:MiniVan            rdfs:subClassOf   ex:Van .
ex:MiniVan            rdfs:subClassOf   ex:PassengerVehicle .

5.2 Describing Properties

In addition to describing the specific classes of things they want to describe, user communities also need to be able to describe specific properties that characterize those classes of things (such as rearSeatLegRoom to describe a passenger vehicle). In RDF Schema, properties are described using the RDF class rdf:Property, and the RDF Schema properties rdfs:domain, rdfs:range, and rdfs:subPropertyOf.

All properties in RDF are described as instances of class rdf:Property. So a new property, such as exterms:weightInKg, is described by assigning the property a URIref, and describing that resource with an rdf:type property whose value is the resource rdf:Property, for example, by writing the RDF statement:

exterms:weightInKg   rdf:type   rdf:Property .

RDF Schema also provides vocabulary for describing how properties and classes are intended to be used together in RDF data. The most important information of this kind is supplied by using the RDF Schema properties rdfs:range and rdfs:domain to further describe application-specific properties.

The rdfs:range property is used to indicate that the values of a particular property are instances of a designated class. For example, if example.org wanted to indicate that the property ex:author had values that are instances of class ex:Person, it would write the RDF statements:

ex:Person   rdf:type     rdfs:Class .
ex:author   rdf:type     rdf:Property .
ex:author   rdfs:range   ex:Person .

These statements indicate that ex:Person is a class, ex:author is a property, and that RDF statements using the ex:author property have instances of ex:Person as objects.

A property, say ex:hasMother, can have zero, one, or more than one range property. If ex:hasMother has no range property, then nothing is said about the values of the ex:hasMother property. If ex:hasMother has one range property, say one specifying ex:Person as the range, this says that the values of the ex:hasMother property are instances of class ex:Person. If ex:hasMother has more than one range property, say one specifying ex:Person as its range, and another specifying ex:Female as its range, this says that the values of the ex:hasMother property are resources that are instances of all of the classes specified as the ranges, i.e., that any value of ex:hasMother is both a ex:Female and a ex:Person.

ex:hasMother   rdfs:range   ex:Female .
ex:hasMother   rdfs:range   ex:Person .

exstaff:frank   ex:hasMother   exstaff:frances .

The rdfs:range property can also be used to indicate that the value of a property is given by a typed literal, as discussed in Section 2.4. For example, if example.org wanted to indicate that the property ex:age had values from the XML Schema datatype xsd:integer, it would write the RDF statements:

ex:age   rdf:type     rdf:Property .
ex:age   rdfs:range   xsd:integer .

The datatype xsd:integer is identified by its URIref (the full URIref being http://www.w3.org/2001/XMLSchema#integer). This URIref can be used without explicitly stating in the schema that it identifies a datatype. However, it is often useful to explicitly state that a given URIref identifies a datatype. This can be done using the RDF Schema class rdfs:Datatype. To state that xsd:integer is a datatype, example.org would write the RDF statement:

xsd:integer   rdf:type   rdfs:Datatype .

This statement says that xsd:integer is the URIref of a datatype (which is assumed to conform to the requirements for RDF datatypes described in [RDF-CONCEPTS]). Such a statement does not constitute a definition of a datatype, e.g., in the sense that example.org is defining a new datatype. There is no way to define datatypes in RDF Schema. As noted in Section 2.4, datatypes are defined externally to RDF (and to RDF Schema), and referred to in RDF statements by their URIrefs. This statement simply serves to document the existence of the datatype, and indicate explicitly that it is being used in this schema.

The rdfs:domain property is used to indicate that a particular property applies to a designated class. For example, if example.org wanted to indicate that the property ex:author applies to instances of class ex:Book, it would write the RDF statements:

ex:Book     rdf:type      rdfs:Class .
ex:author   rdf:type      rdf:Property .
ex:author   rdfs:domain   ex:Book .

These statements indicate that ex:Book is a class, ex:author is a property, and that RDF statements using the ex:author property have instances of ex:Book as subjects.

A given property, say exterms:weight, may have zero, one, or more than one domain property. If exterms:weight has no domain property, then nothing is said about the resources that exterms:weight properties may be used with (any resource could have a exterms:weight property). If exterms:weight has one domain property, say one specifying ex:Book as the domain, this says that the exterms:weight property applies to instances of class ex:Book. If exterms:weight has more than one domain property, say one specifying ex:Book as the domain and another one specifying ex:MotorVehicle as the domain, this says that any resource that has a exterms:weight property is an instance of all of the classes specified as the domains, i.e., that any resource that has a exterms:weight property is both a ex:Book and a ex:MotorVehicle (illustrating the need for care in specifying domains and ranges).

exterms:weight   rdfs:domain   ex:Book .
exterms:weight   rdfs:domain   ex:MotorVehicle .

exthings:companyCar   exterms:weight   "2500"^^xsd:integer .

The use of these range and domain descriptions can be illustrated by extending the vehicle schema, adding two properties ex:registeredTo and ex:rearSeatLegRoom, a new class ex:Person, and explicitly describing the datatype xsd:integer as a datatype. The ex:registeredTo property applies to any ex:MotorVehicle and its value is a ex:Person. For the sake of this example, ex:rearSeatLegRoom applies only to instances of class ex:PassengerVehicle. The value is an xsd:integer giving the number of centimeters of rear seat legroom. These descriptions are shown in Example 18 :

:registeredTo a rdf:Property;
    rdfs:domain :MotorVehicle;
    rdfs:range  :Person.

:rearSeatLegRoom a rdf:Property;
    rdfs:domain :PassengerVehicle;
    rdfs:range  xsd:integer.
 
:Person a rdfs:Class.
xsd:integer a rdfs:Datatype.                 

RDF Schema provides a way to specialize properties as well as classes. This specialization relationship between two properties is described using the predefined rdfs:subPropertyOf property. For example, if ex:primaryDriver and ex:driver are both properties, example.org could describe these properties, and the fact that ex:primaryDriver is a specialization of ex:driver, by writing the RDF statements:

ex:driver          rdf:type             rdf:Property .
ex:primaryDriver   rdf:type             rdf:Property .
ex:primaryDriver   rdfs:subPropertyOf   ex:driver .

The meaning of this rdfs:subPropertyOf relationship is that if an instance exstaff:fred is an ex:primaryDriver of the instance ex:companyVan, then RDF Schema defines exstaff:fred as also being an ex:driver of ex:companyVan.

A property may be a subproperty of zero, one or more properties. All RDF Schema rdfs:range and rdfs:domain properties that apply to an RDF property also apply to each of its subproperties. So, in the above example, RDF Schema defines ex:primaryDriver as also having an rdfs:domain of ex:MotorVehicle, because of its subproperty relationship to ex:driver.

Example 19 shows the Turtle for the full vehicle schema, containing all the descriptions given so far:

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
@prefix xsd: <http://www.w3.org/2001/XMLSchema#>.
@base <http://example.org/schemas/vehicles>

:MotorVehicle a rdfs:Class.

:PassengerVehicle a rdfs:Class;
   rdfs:subClassOf :MotorVehicle.

:Truck a rdfs:Class;
   rdfs:subClassOf :MotorVehicle.
    
:Van a rdfs:Class;
   rdfs:subClassOf :MotorVehicle.

:MiniVan a rdfs:Class;
   rdfs:subClassOf :Van.
   rdfs:subClassOf :PassengerVehicle;

:Person a rdfs:Class.

xsd:integer a rdfs:Datatype.

:registeredTo a rdf:Property;
   rdfs:domain :MotorVehicle;
   rdfs:range  :Person.
    
:rearSeatLegRoom a rdf:Property;
   rdfs:domain rdf:resource :MotorVehicle;
   rdfs:range xsd:integer.

:driver a rdf:Property;
   rdfs:domain :MotorVehicle.

:primaryDriver a rdf:Property;
   rdfs:subPropertyOf :driver.

Having shown how to describe classes and properties using RDF Schema, instances using those classes and properties can now be illustrated. For example, Example 29 Example 20 describes an instance of the ex:PassengerVehicle class described in Example 19, together with some hypothetical values for its properties.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
@prefix ex:  <http://example.org/schemas/vehicles#>
@base <http://example.org/things>

:johnSmithsCar a ex:PassengerVehicle;
    ex:registeredTo    <http://www.example.org/staffid/85740>;
    ex:rearSeatLegRoom "127"^^xsd:integer;
    ex:primaryDriver   <http://www.example.org/staffid/85740>.

Note that an ex:registeredTo property can be used in describing this instance of ex:PassengerVehicle, because ex:PassengerVehicle is a subclass of ex:MotorVehicle. Note also that a typed literal is used for the value of the ex:rearSetLegRoom property in this instance, rather than a plain literal (i.e., rather than stating the value as ex:rearSeatLegRoom 127;). Because the schema describes the range of this property as an xsd:integer, the value of the property should be a typed literal of that datatype in order to match the range description (i.e., the range declaration does not automatically "assign" a datatype to a plain literal, and so a typed literal of the appropriate datatype must be explicitly provided). Additional information, either in the schema, or in additional instance data, could also be provided to explicitly specify the units of the ex:rearSetLegRoom property (centimeters), as discussed in Section 4.4.

5.3 Interpreting RDF Schema Declarations

As noted earlier, the RDF Schema type system is similar in some respects to the type systems of object-oriented programming languages such as Java. However, RDF differs from most programming language type systems in several important respects.

One important difference is that instead of describing a class as having a collection of specific properties, an RDF schema describes properties as applying to specific classes of resources, using domain and range properties. For example, a typical object-oriented programming language might define a class Book with an attribute called author having values of type Person. A corresponding RDF schema would describe a class ex:Book, and, in a separate description, a property ex:author having a domain of ex:Book and a range of ex:Person.

The difference between these approaches may seem to be only syntactic, but in fact there is an important difference. In the programming language class description, the attribute author is part of the description of class Book, and applies only to instances of class Book. Another class (say, softwareModule) might also have an attribute called author, but this would be considered a different attribute. In other words, the scope of an attribute description in most programming languages is restricted to the class or type in which it is defined. In RDF, on the other hand, property descriptions are, by default, independent of class definitions, and have, by default, global scope (although they may optionally be declared to apply only to certain classes using domain specifications).

As a result, an RDF schema could describe a property exterms:weight without a domain being specified. This property could then be used to describe instances of any class that might be considered to have a weight. One benefit of the RDF property-based approach is that it becomes easier to extend the use of property definitions to situations that might not have been anticipated in the original description. At the same time, this is a "benefit" which must be used with care, to insure that properties are not mis-applied in inappropriate situations.

Another result of the global scope of RDF property descriptions is that it is not possible in an RDF schema to define a specific property as having locally-different ranges depending on the class of the resource it is applied to. For example, in defining the property ex:hasParent, it would be desirable to be able to say that if the property is used to describe a resource of class ex:Human, then the range of the property is also a resource of class ex:Human, while if the property is used to describe a resource of class ex:Tiger, then the range of the property is also a resource of class ex:Tiger. This kind of definition is not possible in RDF Schema. Instead, any range defined for an RDF property applies to all uses of the property, and so ranges should be defined with care. However, while such locally-different ranges cannot be defined in RDF Schema, they can be defined in some of the richer schema languages discussed in Section 5.5.

Another important difference is that RDF Schema descriptions are not necessarily prescriptive in the way programming language type declarations typically are. For example, if a programming language declares a class Book with an author attribute having values of type Person, this is usually interpreted as a group of constraints. The language will not allow the creation of an instance of Book without an author attribute, and it will not allow an instance of Book with an author attribute that does not have a Person as its value. Moreover, if author is the only attribute defined for class Book, the language will not allow an instance of Book with some other attribute.

RDF Schema, on the other hand, provides schema information as additional descriptions of resources, but does not prescribe how these descriptions should be used by an application. For example, suppose an RDF schema states that an ex:author property has an rdfs:range of class ex:Person. This is simply an RDF statement that RDF statements containing ex:author properties have instances of ex:Person as objects.

This schema-supplied information might be used in different ways. One application might interpret this statement as specifying part of a template for RDF data it is creating, and use it to ensure that any ex:author property has a value of the indicated (ex:Person) class. That is, this application interprets the schema description as a constraint in the same way that a programming language might. However, another application might interpret this statement as providing additional information about data it is receiving, information which may not be provided explicitly in the original data. For example, this second application might receive some RDF data that includes an ex:author property whose value is a resource of unspecified class, and use this schema-provided statement to conclude that the resource must be an instance of class ex:Person. A third application might receive some RDF data that includes an ex:author property whose value is a resource of class ex:Corporation, and use this schema information as the basis of a warning that "there may be an inconsistency here, but on the other hand there may not be". Somewhere else there may be a declaration that resolves the apparent inconsistency (e.g., a declaration to the effect that "a Corporation is a (legal) Person").

Moreover, depending on how the application interprets the property descriptions, a description of an instance might be considered valid either without some of the schema-specified properties (e.g., there might be an instance of ex:Book without an ex:author property, even if ex:author is described as having a domain of ex:Book), or with additional properties (there might be an instance of ex:Book with an ex:technicalEditor property, even though the schema describing class ex:Book does not describe such a property).

In other words, statements in an RDF schema are always descriptions. They may also be prescriptive (introduce constraints), but only if the application interpreting those statements wants to treat them that way. All RDF Schema does is provide a way of stating this additional information. Whether this information conflicts with explicitly specified instance data is up to the application to determine and act upon.

5.4 Other Schema Information

RDF Schema provides a number of other built-in properties, which can be used to provide documentation and other information about an RDF schema or about instances. For example the rdfs:comment property can be used to provide a human-readable description of a resource. The rdfs:label property can be used to provide a more human-readable version of a resource's name. The rdfs:seeAlso property can be used to indicate a resource that might provide additional information about the subject resource. The rdfs:isDefinedBy property is a subproperty of rdfs:seeAlso, and can be used to indicate a resource that (in a sense not specified by RDF; e.g., the resource may not be an RDF schema) "defines" the subject resource. RDF Vocabulary Description Language 1.0: RDF Schema [RDF-VOCABULARY] should be consulted for further discussion of these properties.

As with a number of the built-in RDF properties such as rdf:value, the uses described for these RDF Schema properties are only their intended uses. [RDF-SEMANTICS] defines no special meanings for these properties, and RDF Schema does not define any constraints based on these intended uses. For example, there is no constraint specified that the object of a rdfs:seeAlso property must provide additional information about the subject of the statement in which it appears.

5.5 Richer Schema Languages

RDF Schema provides basic capabilities for describing RDF vocabularies, but additional capabilities are also possible, and can be useful. These capabilities may be provided through further development of RDF Schema, or in other languages based on RDF. Other richer schema capabilities that have been identified as useful (but that are not provided by RDF Schema) include:

• cardinality constraints on properties, e.g., that a Person has exactly one biological father.
• specifying that a given property (such as ex:hasAncestor) is transitive, e.g., that if A ex:hasAncestor B, and B ex:hasAncestor C, then A ex:hasAncestor C.
• specifying that a given property is a unique identifier (or key) for instances of a particular class.
• specifying that two different classes (having different URIrefs) actually represent the same class.
• specifying that two different instances (having different URIrefs) actually represent the same individual.
• specifying constraints on the range or cardinality of a property that depend on the class of resource to which a property is applied, e.g., being able to say that for a soccer team the ex:hasPlayers property has 11 values, while for a basketball team the same property should have only 5 values.
• the ability to describe new classes in terms of combinations (e.g., unions and intersections) of other classes, or to say that two classes are disjoint (i.e., that no resource is an instance of both classes).

The additional capabilities mentioned above, in addition to others, are the targets of ontology languages such as DAML+OIL [DAML+OIL] and OWL [OWL]. Both these languages are based on RDF and RDF Schema (and both currently provide all the additional capabilities mentioned above). The intent of such languages is to provide additional machine-processable semantics for resources, that is, to make the machine representations of resources more closely resemble their intended real world counterparts. While such capabilities are not necessarily needed to build useful applications using RDF (see Section 6 for a description of a number of existing RDF applications), the development of such languages is a very active subject of work as part of the development of the Semantic Web.

6.1 Dublin Core Metadata Initiative

Metadata is data about data. Specifically, the term refers to data used to identify, describe, or locate information resources, whether these resources are physical or electronic. While structured metadata processed by computers is relatively new, the basic concept of metadata has been used for many years in helping manage and use large collections of information. Library card catalogs are a familiar example of such metadata.

The Dublin Core is a set of "elements" (properties) for describing documents (and hence, for recording metadata). The element set was originally developed at the March 1995 Metadata Workshop in Dublin, Ohio. The Dublin Core has subsequently been modified on the basis of later Dublin Core Metadata workshops, and is currently maintained by the Dublin Core Metadata Initiative. The goal of the Dublin Core is to provide a minimal set of descriptive elements that facilitate the description and the automated indexing of document-like networked objects, in a manner similar to a library card catalog. The Dublin Core metadata set is intended to be suitable for use by resource discovery tools on the Internet, such as the "Webcrawlers" employed by popular World Wide Web search engines. In addition, the Dublin Core is meant to be sufficiently simple to be understood and used by the wide range of authors and casual publishers who contribute information to the Internet. Dublin Core elements have become widely used in documenting Internet resources (the Dublin Core creator element has already been used in earlier examples). The current elements of the Dublin Core are defined in the Dublin Core Metadata Element Set, Version 1.1: Reference Description [DC], and contain definitions for the following properties:

• Title: A name given to the resource.
• Creator: An entity primarily responsible for making the content of the resource.
• Subject: The topic of the content of the resource.
• Description: An account of the content of the resource.
• Publisher: An entity responsible for making the resource available
• Contributor: An entity responsible for making contributions to the content of the resource.
• Date: A date associated with an event in the life cycle of the resource.
• Type: The nature or genre of the content of the resource.
• Format: The physical or digital manifestation of the resource.
• Identifier: An unambiguous reference to the resource within a given context.
• Source: A reference to a resource from which the present resource is derived.
• Language: A language of the intellectual content of the resource.
• Relation: A reference to a related resource.
• Coverage: The extent or scope of the content of the resource.
• Rights: Information about rights held in and over the resource.

Information using the Dublin Core elements may be represented in any suitable language (e.g., in HTML meta elements). However, RDF is an ideal representation for Dublin Core information. The examples below represent the simple description of a set of resources in RDF using the Dublin Core vocabulary. Note that the specific Dublin Core RDF vocabulary shown here is not intended to be authoritative. The Dublin Core Reference Description [DC] is the authoritative reference.

The first example, Example 21, describes a Web site home page using Dublin Core properties:

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.               
@prefix dc:  <http://purl.org/dc/elements/1.1/>.        

<http://www.dlib.org>
    dc:title       "D-Lib Program - Research in Digital Libraries";
    dc:description """The D-Lib program supports the community of people
       with research interests in digital libraries and electronic
       publishing.""";
    dc:publisher:  "Corporation For National Research Initiatives";
    dc:date        "1995-01-07";
    dc:subject [
         a rdf:Bag;
         rdf:_1 "Research; statistical methods";
         rdf:_2 "Education, research, related topics";
         rdf:_3 "Library use Studies".
    ];
    dc:type        "World Wide Web Home Page";
    dc:format      "text/html";
    dc:language    "en".

Note that both RDF and the Dublin Core define an (XML) element called "Description" (although the Dublin Core element name is written in lowercase). Even if the initial letter were identically uppercase, the XML namespace mechanism enables these two elements to be distinguished (one is rdf:Description, and the other is dc:description). Also, as a matter of interest, accessing http://purl.org/dc/elements/1.1/ (the namespace URI used to identify the Dublin Core vocabulary in this example) in a Web browser (as of the current writing) will retrieve an RDF Schema declaration for [DC].

The second example, Example 22, describes a published magazine:

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.               
@prefix dc: <http://purl.org/dc/elements/1.1/>.        
@prefix dcterms: <http://purl.org/dc/terms/>.        

<http://www.dlib.org/dlib/may98/05contents.html>
      dc:title         "DLIB Magazine - The Magazine for Digital Library Research - May 1998";
      dc:description   """D-LIB magazine is a monthly compilation of
       contributed stories, commentary, and briefings.""";
      dc:contributor   "Amy Friedlander";
      dc:publisher     "Corporation for National Research Initiatives";
      dc:date          "1998-01-05";
      dc:type          "electronic journal";
      dc:subject [
        a rdf:Bag;
        rdf:_1 "library use studies";
        rdf:_2 "magazines and newspapers".
      ];
      dc:format        "text/html";
      dc:identifier    <urn:issn:1082-9873>;
      dcterms:isPartOf <http://www.dlib.org>.

Example 22 uses (in the last line) the Dublin Core qualifier isPartOf (from a separate vocabulary) to indicate that this magazine is "part of" the previously-described Web site.

The third example, Example 23, describes a specific article in the magazine described in Example 22.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.               
@prefix dc: <http://purl.org/dc/elements/1.1/>.        
@prefix dcterms: <http://purl.org/dc/terms/>.        

<http://www.dlib.org/dlib/may98/miller/05miller.html>
   dc:title         "An Introduction to the Resource Description Framework";
   dc:creator       "Eric J. Miller";
   dc:description 
      """The Resource Description Framework (RDF) is an
       infrastructure that enables the encoding, exchange and reuse of
       structured metadata. rdf is an application of xml that imposes needed
       structural constraints to provide unambiguous methods of expressing
       semantics. rdf additionally provides a means for publishing both
       human-readable and machine-processable vocabularies designed to
       encourage the reuse and extension of metadata semantics among
       disparate information communities. the structural constraints rdf
       imposes to support the consistent encoding and exchange of
       standardized metadata provides for the interchangeability of separate
       packages of metadata defined by different resource description
       communities.""";
    dc:publisher     "Corporation for National Research Initiatives";
    dc:subject [
        a rdf:Bag;
        rdf:_1 "machine-readable catalog record formats";
        rdf:_2 "applications of computer file organization and access methods".
    ];
    dc:rights        "Copyright © 1998 Eric Miller";
    dc:type          "Electronic Document";
    dc:format        "text/html";
    dc:language      "en";
    dcterms:isPartOf <http://www.dlib.org/dlib/may98/05contents.html>.

Example 23 also uses the qualifier isPartOf, this time to indicate that this article is "part of" the previously-described magazine.

6.2 PRISM

PRISM: Publishing Requirements for Industry Standard Metadata [PRISM] is a metadata specification developed in the publishing industry. Magazine publishers and their vendors formed the PRISM Working Group to identify the industry's needs for metadata and define a specification to meet them. Publishers want to use existing content in many ways in order to get a greater return on the investment made in creating it. Converting magazine articles to HTML for posting on the Web is one example. Licensing it to aggregators like LexisNexis is another. All of these are "first uses" of the content; typically they all go live at the time the magazine hits the stands. The publishers also want their content to be "evergreen". It might be used in new issues, such as in a retrospective article. It could be used by other divisions in the company, such as in a book compiled from the magazine's photos, recipes, etc. Another use is to license it to outsiders, such as in a reprint of a product review, or in a retrospective produced by a different publisher. This overall goal requires a metadata approach that emphasizes discovery, rights tracking, and end-to-end metadata.

Discovery: Discovery is a general term for finding content which encompasses searching, browsing, content routing, and other techniques. Discussions of discovery frequently center on a consumer searching a public Web site. However, discovering content is much broader than that. The audience may consist of consumers, or it may consist of internal users such as researchers, designers, photo editors, licensing agents, etc. To assist discovery, PRISM provides properties to describe the topics, formats, genre, origin, and contexts of a resource. It also provides means for categorizing resources using multiple subject description taxonomies.

Rights Tracking: Magazines frequently contain material licensed from others. Photos from a stock photo agency are the most common type of licensed material, but articles, sidebars, and all other types of content may be licensed. Simply knowing if content was licensed for one-time use, requires royalty payments, or is wholly-owned by the publisher is a struggle. PRISM provides elements for basic tracking of such rights. A separate vocabulary defined in the PRISM specification supports description of places, times, and industries where content may or may not be used.

End-to-end metadata: Most published content already has metadata created for it. Unfortunately, when content moves between systems, the metadata is frequently discarded, only to be re-created later in the production process at considerable expense. PRISM aims to reduce this problem by providing a specification that can be used in multiple stages in the content production pipeline. An important feature of the PRISM specification is its use of other existing specifications. Rather than create an entirely new thing, the group decided to use existing specifications as much as possible, and only define new things where needed. For this reason, the PRISM specification uses XML, RDF, Dublin Core, and well as various ISO formats and vocabularies.

A PRISM description may be as simple as a few Dublin Core properties with plain literal values. Example 24 describes a photograph, giving basic information on its title, photographer, format, etc.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix dc: <http://purl.org/dc/elements/1.1/>.

<http://travel.example.com/2000/08/Corfu.jpg>
    dc:title       "Walking on the Beach in Corfu";
    dc:description "Photograph taken at 6:00 am on Corfu with two models";
    dc:creator     "John Peterson";
    dc:contributor "Sally Smith, lighting";
    dc:format      "image/jpeg".

PRISM also augments the Dublin Core to allow more detailed descriptions. The augmentations are defined as three new vocabularies, generally cited using the prefixes prism:, pcv:, and prl:.

prism: This prefix refers to the main PRISM vocabulary, whose terms use the URI prefix http://prismstandard.org/namespaces/basic/1.0/ . Most of the properties in this vocabulary are more specific versions of properties from the Dublin Core. For example, more specific versions of dc:date are provided by properties like prism:publicationTime, prism:releaseTime, prism:expirationTime, etc.

pcv: This prefix refers to the PRISM Controlled Vocabulary (pcv) vocabulary, whose terms use the URI prefix http://prismstandard.org/namespaces/pcv/1.0/ . Currently, common practice for describing the subject(s) of an article is by supplying descriptive keywords. Unfortunately, simple keywords do not make a great difference in retrieval performance, due to the fact that different people will use different keywords [BATES96]. Best practice is to code the articles with subject terms from a "controlled vocabulary". The vocabulary should provide as many synonyms as possible for its terms in the vocabulary. This way the controlled terms provide a meeting ground for the keywords supplied by the searcher and the indexer. The pcv vocabulary provides properties for specifying terms in a vocabulary, the relations between terms, and alternate names for the terms.

prl: This prefix refers to the PRISM Rights Language vocabulary, whose terms use the URI prefix http://prismstandard.org/namespaces/prl/1.0/ . Digital Rights Management is an area undergoing considerable upheaval. There are a number of proposals for rights management languages, but none are clearly favored throughout the industry. Because there was no clear choice to recommend, the PRISM Rights Language (PRL) was defined as an interim measure. It provides properties which let people say if an item can or cannot be "used", depending on conditions of time, geography, and industry. This is believed to be an 80/20 trade-off which will help publishers begin to save money when tracking rights. It is not intended to be a general rights language, or allow publishers to automatically enforce limits on consumer uses of the content.

PRISM uses RDF because of its abilities for dealing with descriptions of varying complexity. Currently, a great deal of metadata uses simple character string (plain literal) values, such as:

dc:coverage "Greece";

Over time the developers of PRISM expect uses of the PRISM specification to become more sophisticated, moving from simple literal values to more structured values. In fact, that range of values is a situation being faced now. Some publishers already use sophisticated controlled vocabularies, others are barely using manually-supplied keywords. To illustrate this, some examples of the different kinds of values that can be given for the dc:coverage property are:

dc:coverage "Greece";
dc:coverage <http://prismstandard.org/vocabs/ISO-3166/GR>;

(i.e., using either a plain literal or a URIref to identify the country) and

dc:coverage <http://prismstandard.org/vocabs/ISO-3166/GR>.
<http://prismstandard.org/vocabs/ISO-3166/GR> rdf:type pcv:Descriptor;
<http://prismstandard.org/vocabs/ISO-3166/GR> pcv:label "Greece"@en;
<http://prismstandard.org/vocabs/ISO-3166/GR> pcv:label "Grèce"@fr.

(using a structured value to provide both a URIref and names in various languages).

Note also that there are properties whose meanings are similar, or subsets of other properties. For example, the geographic subject of a resource could be given with

prism:subject "Greece";
dc:coverage   "Greece";

or

prism:location "Greece";

Any of those properties might use the simple literal value, or a more complex structured value. Such a range of possibilities cannot be adequately described by DTDs, or even by the newer XML Schemas. While there is a wide range of syntactic variations to deal with, RDF's graph model has a simple structure - a set of triples. Dealing with the metadata in the triples domain makes it much easier for older software to accommodate content with new extensions.

This section closes with two final examples. Example 25 says that the image (.../Corfu.jpg) cannot be used (#none) in the tobacco industry (code 21 in SIC, the Standard Industrial Classifications).

@prefix prism: <http://prismstandard.org/namespaces/basic/1.0/>.
@prefix prl:   <http://prismstandard.org/namespaces/prl/1.0/>.
@prefix rdf:   <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix dc:    <http://purl.org/dc/elements/1.1/>.

<http://travel.example.com/2000/08/Corfu.jpg>
    dc:rights [
      prl:usage    <http://prismstandard.org/vocabularies/1.0/usage.xml#none>;
      prl:industry <http://prismstandard.org/vocabs/SIC/21>.
    ].

Example 26 says that the photographer for the Corfu image was employee 3845, better known as John Peterson. It also says that the geographic coverage of the photo is Greece. It does so by providing, not just a code from a controlled vocabulary, but a cached version of the information for that term in the vocabulary.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix pcv: <http://prismstandard.org/namespaces/pcv/1.0/>.
@prefix dc:  <http://purl.org/dc/elements/1.1/>.

</2000/08/Corfu.jpg>
   dc:identifier <http://travel.example.com/content/2357845> ;
   dc:creator    <http://travel.example.com/content/2357845> ;
   dc:coverage   <http://prismstandard.org/vocabs/ISO-3166/GR>.
  
</content/2357845> a pcv:Descriptor;
   pcv:label "John Peterson".
 
<http://prismstandard.org/vocabs/ISO-3166/GR>
   pcv:label "Greece"@en;
   pcv:label "Grèce"@fr.

7.1 RDF Semantics

As discussed in the preceding sections, RDF is intended to be used to express statements about resources in the form of a graph, using specific vocabularies (names of resources, properties, classes, etc.). RDF is also intended to be the foundation for more advanced languages, such as those discussed in Section 5.5. In order to serve these purposes, the "meaning" of an RDF graph must be defined in a very precise manner.

Exactly what constitutes the "meaning" of an RDF graph in a very general sense may depend on many factors, including conventions within a user community to interpret user-defined RDF classes and properties in specific ways, comments in natural language, or links to other content-bearing documents. As noted briefly in Section 2.2, much of the meaning conveyed in these forms will not be directly accessible to machine processing, although this meaning may be used by human interpreters of the RDF information, or by programmers writing software to perform various kinds of processing on that RDF information. However, RDF statements also have a formal meaning which determines, with mathematical precision, the conclusions (or entailments) that machines can draw from a given RDF graph. The RDF Semantics [RDF-SEMANTICS] document defines this formal meaning, using a technique called model theory for specifying the semantics of a formal language. [RDF-SEMANTICS] also defines the semantic extensions to the RDF language represented by RDF Schema, and by individual datatypes. In other words, the RDF model theory provides the formal underpinnings for all RDF concepts. Based on the semantics defined in the model theory, it is simple to translate an RDF graph into a logical expression with essentially the same meaning.

7.2 Test Cases

The RDF Test Cases [RDF-TESTS] supplement the textual RDF specifications with test cases (examples) corresponding to particular technical issues addressed by the RDF Core Working Group. To help describe these examples, the Test Cases document introduces a notation called N-Triples, which provides the basis for the triples notation used throughout this Primer. The test cases are published in machine-readable form at Web locations referenced by the Test Cases document, so developers can use these as the basis for automated testing of RDF software.

The test cases are divided into a number of categories:

• Positive and Negative Parser Tests: These test whether RDF/XML parsers produce a correct N-Triples output graph from legal RDF/XML input documents, or correctly report errors if the input documents are not legal RDF/XML.
• Positive and Negative Entailment Tests: These test whether proper entailments (conclusions) are or are not drawn from sets of specified RDF statements.
• Datatype-aware Entailment Tests: These are positive or negative entailment tests that involve the use of datatypes, and hence require additional support for the specific datatypes involved in the tests.
• Miscellaneous Tests: These are tests that do not fall into one of the other categories.

The test cases are not a complete specification of RDF, and are not intended to take precedence over the other specification documents. However, they are intended to illustrate the intent of the RDF Core Working Group with respect to the design of RDF, and developers may find these test cases helpful should the wording of the specifications be unclear on any point of detail.

8.1 Normative References

[RDF-CONCEPTS]

Resource Description Framework (RDF): Concepts and Abstract Syntax , Klyne G., Carroll J. (Editors), W3C Recommendation, 10 February 2004. This version is http://www.w3.org/TR/2004/REC-rdf-primer-20040210/. The latest version is http://www.w3.org/TR/rdf-concepts/.

[RDF-MIME-TYPE]

MIME Media Types , The Internet Assigned Numbers Authority (IANA). This document is http://www.iana.org/assignments/media-types/ . The registration for application/rdf+xml is archived at http://www.w3.org/2001/sw/RDFCore/mediatype-registration .

[RDF-MS]

Resource Description Framework (RDF) Model and Syntax Specification , Lassila O., Swick R. (Editors), World Wide Web Consortium, 22 February 1999. This version is http://www.w3.org/TR/1999/REC-rdf-syntax-19990222/. The latest version is http://www.w3.org/TR/REC-rdf-syntax/.

[RDF-PRIMER]

RDF Primer , Manola F., Miller E. (Editors), W3C Recommendation, 10 February 2004. This version is http://www.w3.org/TR/2004/REC-rdf-primer-20040210/. The latest version is http://www.w3.org/TR/rdf-primer/.

[RDF-SEMANTICS]

RDF Semantics , Hayes P. (Editor), W3C Recommendation, 10 February 2004. This version is http://www.w3.org/TR/2004/REC-rdf-mt-20040210/. The latest version is http://www.w3.org/TR/rdf-mt/.

[RDF-SYNTAX]

RDF/XML Syntax Specification (Revised) , Beckett D. (Editor), W3C Recommendation, 10 February 2004. This version http://www.w3.org/TR/2004/REC-rdf-syntax-grammar-20040210/. The latest version is http://www.w3.org/TR/rdf-syntax-grammar/.

[RDF-TESTS]

RDF Test Cases , Grant J., Beckett D. (Editors), W3C Recommendation, 10 February 2004. This version is http://www.w3.org/TR/2004/REC-rdf-testcases-20040210/. The latest version is http://www.w3.org/TR/rdf-testcases/.

[RDF-VOCABULARY]

RDF Vocabulary Description Language 1.0: RDF Schema , Brickley D., Guha R.V. (Editors), W3C Recommendation, 10 February 2004. This version is http://www.w3.org/TR/2004/REC-rdf-schema-20040210/. The latest version is http://www.w3.org/TR/rdf-schema/.

[UNICODE]

The Unicode Standard, Version 3, The Unicode Consortium, Addison-Wesley, 2000. ISBN 0-201-61633-5, as updated from time to time by the publication of new versions. (See http://www.unicode.org/unicode/standard/versions/ for the latest version and additional information on versions of the standard and of the Unicode Character Database).

[URIS]

RFC 2396 - Uniform Resource Identifiers (URI): Generic Syntax , Berners-Lee T., Fielding R., Masinter L., IETF, August 1998, http://www.isi.edu/in-notes/rfc2396.txt.

[XML]

Extensible Markup Language (XML) 1.0, Second Edition , Bray T., Paoli J., Sperberg-McQueen C.M., Maler E. (Editors), World Wide Web Consortium, 6 October 2000. This version is http://www.w3.org/TR/2000/REC-xml-20001006. The latest version is http://www.w3.org/TR/REC-xml.

8.2 Informational References

[ADDRESS-SCHEMES]

Addressing Schemes , Connolly D., 2001. This document is http://www.w3.org/Addressing/schemes.html.

[BATES96]

Indexing and Access for Digital Libraries and the Internet: Human, Database, and Domain Factors , Bates M.J., 1996. This document is http://is.gseis.ucla.edu/research/mjbates.html.

[BERNERS-LEE98]

What the Semantic Web can represent , Berners-Lee T., 1998. This document is http://www.w3.org/DesignIssues/RDFnot.html.

[CG]

Conceptual Graphs, Sowa J., ISO working document ISO/JTC1/SC32/WG2 N 000, 2 April 2001 (work in progress). Available at http://users.bestweb.net/~sowa/cg/cgstand.htm.

[DAML+OIL]

DAML+OIL (March 2001) Reference Description , Connolly D., van Harmelen F., Horrocks I., McGuinness D.L., Patel-Schneider P.F., Stein L.A., World Wide Web Consortium, 18 December 2001. This document is http://www.w3.org/TR/daml+oil-reference.

[DC]

Dublin Core Metadata Element Set, Version 1.1: Reference Description , 02 June 2003. This version is http://dublincore.org/documents/2003/06/02/dces/. The latest version is http://dublincore.org/documents/dces/.

[GRAY]

Logic, Algebra and Databases, Gray P., Ellis Horwood Ltd., 1984. ISBN 0-85312-709-3, 0-85312-803-0, 0-470-20103-7, 0-470-20259-9.

[HAYES]

In Defense of Logic, Hayes P., Proceedings from the International Joint Conference on Artificial Intelligence, 1975, San Francisco. Morgan Kaufmann Inc., 1977. Also in Computation and Intelligence: Collected Readings, Luger G. (ed), AAAI press/MIT press, 1995. ISBN 0-262-62101-0.

[KIF]

Knowledge Interchange Format, Genesereth M., draft proposed American National Standard NCITS.T2/98-004. Available at http://logic.stanford.edu/kif/dpans.html.

[LUGER]

Artificial Intelligence: Structures and Strategies for Complex Problem Solving (3rd ed.), Luger G., Stubblefield W., Addison Wesley Longman, 1998. ISBN 0-805-31196-3.

[NAMEADDRESS]

Naming and Addressing: URIs, URLs, ... , Connolly D., 2002. This document is http://www.w3.org/Addressing/.

[OWL]

OWL Web Ontology Language Reference , Dean M., Schreiber G (Editors); van Harmelen F., Hendler J., Horrocks I., McGuinness D.L., Patel-Schneider P.F., Stein L.A. (Authors), W3C Recommendation, 10 February 2004. The latest version is http://www.w3.org/TR/owl-ref/.

[PRISM]

PRISM: Publishing Requirements for Industry Standard Metadata , Version 1.1, 19 February 2002. The latest version of the PRISM specification is available at http://www.prismstandard.org/.

[RDF-S]

Resource Description Framework (RDF) Schema Specification 1.0 , Brickley D., Guha, R.V. (Editors), World Wide Web Consortium. 27 March 2000. This version is http://www.w3.org/TR/2000/CR-rdf-schema-20000327/.

[SOWA]

Knowledge Representation: Logical, Philosophical and Computational Foundations, Sowa J., Brookes/Cole, 2000. ISBN 0-534-94965-7.

[TURTLE]

@@@To be filled in@@@

[WEBDATA]

Web Architecture: Describing and Exchanging Data , Berners-Lee T., Connolly D., Swick R., World Wide Web Consortium, 7 June 1999. This document is http://www.w3.org/1999/04/WebData.

[XML-SCHEMA2]

XML Schema Part 2: Datatypes , Biron P., Malhotra A. (Editors), World Wide Web Consortium. 2 May 2001. This version is http://www.w3.org/TR/2001/REC-xmlschema-2-20010502/. The latest version is http://www.w3.org/TR/xmlschema-2/.