Abstract

This document defines the procedures and rules to be applied when mapping converting tabular data into JSON. Tabular data may be complemented with metadata annotations that describe its structure, the meaning of its content and how it may form part of a collection of interrelated tabular data. This document specifies the effect of this metadata on the resulting JSON.

Status of This Document

This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at http://www.w3.org/TR/.

The CSV on the Web Working Group was chartered to produce Recommendations for "Access methods for CSV Metadata", "Metadata vocabulary for CSV data" and "Mapping mechanism to transforming CSV into various Formats (e.g., RDF, JSON, or XML)". This document aims to satisfy the JSON variant of the mapping Recommendation.

Due to the limited resources available within the CSV on the Web Working Group, this document describes only a simple mapping —that is, where a single object is created for each row of tabular data that contains a single property per cell. The Working Group solicits input on the value of mapping a single row of tabular data into multiple inter-related objects. This document was published by the CSV on the Web Working Group as a First Public Working Draft. This document is intended to become a W3C Recommendation. If you wish to make comments regarding this document, please send them to public-csv-wg@w3.org ( subscribe , archives ). All comments are welcome.

Publication as a First Public Working Draft does not imply endorsement by the W3C Membership. This is a draft document and may be updated, replaced or obsoleted by other documents at any time. It is inappropriate to cite this document as other than work in progress.

This document was produced by a group operating under the 5 February 2004 W3C Patent Policy . W3C maintains a public list of any patent disclosures made in connection with the deliverables of the group; that page also includes instructions for disclosing a patent. An individual who has actual knowledge of a patent which the individual believes contains Essential Claim(s) must disclose the information in accordance with section 6 of the W3C Patent Policy .

This document is governed by the 1 August 2014 W3C Process Document .

Table of Contents

1. Introduction

This document describes the processing of tabular data to create a set of nested objects referred to as the output graph . The output graph SHALL that MUST be serialized as JSON [ json RFC7159 ].

Note

The conversion of CSV content to JSON encoding is intended for web developers who need not care about the complexities of RDF [ rdf11-concepts ]. Where the formality of RDF is required, [ csv2rdf ] provides the procedures for mapping from CSV content to RDF which may be serialized to [ json-ld ].

The Tabular Data Model [ tabular-data-model ] defines a core an annotated tabular data model consisting of tables , columns , rows , and cells . Tabular data may be , enriched with metadata annotations that describes its describe the structure of the tabular data and the meaning of its content. These metadata annotations are described in [ tabular-metadata ] and may be embedded within the CSV encoding itself as a header line or provided within a separate metadata document. The resulting annotated table conforms to the annotated tabular data model . The metadata annotations may describe how a table A group of tables relates to is a group collection of tables . Such collections conform to the grouped tabular data model . published as a single atomic unit.

The mapping conversion procedure described in this specification operates on the abstract annotated tabular data model; core , annotated or grouped . No discussion is given to model . This specification does not specify the processes needed to convert CSV-encoded data into tabular data form. Please refer to [ tabular-data-model ] for details of parsing tabular data . Further details on parsing cells within tabular data is provided in [ tabular-metadata

Conversion applications MUST provide at least two modes of operation: standard ]. and minimal .

Note

Adopting terminology Standard mode conversion frames the information gleaned from the Data Catalog Vocabulary [ vocab-dcat cells ], of the tabular data is considered to be a dataset , whilst with details of the CSV file rows , tables , and a group of tables within which that tabular data is encoded information is considered to be a distribution of that tabular data. provided.

Issue 93

Minimal mode conversion includes only the information gleaned from the cells Are of the abstract tabular data and the CSV that encodes it within the same thing? (Is DCAT distribution appropriate?) output.

The mapping procedure is intended to be simple; encouraging the provision of compliant mapping applications. The limitation of this simple mapping is that a single object is created for each row Standard of tabular data that contains a single property per cell and minimal conversion are described normatively below .

Note

An annotated table may include a reference to a template specification (see Conversion applications MAY offer additional implementation specific conversion modes.

Transformation definitions , as defined in [ tabular-metadata ]) that describes ] MAY be used to specify how tabular data can be transformed into another format using a template-based approach. Templating script or template. Such transformation definitions MAY facilitates far more sophisticated transformations than are possible using the simple mapping . There is no standard template syntax, therefore template specifications may be written using existing template languages, such as Mustache . The processing of template specifications during the mapping is yet to be determined by the Working Group and is, at least for the interim, beyond the scope of this document. Finally, note that the mapping procedure is considered to be entirely textual . There is no requirement on compliant mapping applications to check the semantic consistency of the data during the mapping, nor validate use the cell values against JSON syntax rules. Where cell values within CSV encoded content are improperly formatted, the output from the mapping is likely to include syntax errors. Downstream applications should be aware of described in this and take appropriate action. Issue 62 Should the RDF/JSON transformation check the values? specification as input.

2. Conformance

As well as sections marked as non-normative, all authoring guidelines, diagrams, examples, and notes in this specification are non-normative. Everything else in this specification is normative.

The key words MAY , and MUST , SHALL , and SHOULD are to be interpreted as described in [ RFC2119 ].

Tabular data MUST conform to the description from [ tabular-data-model ]. In particular note that each row MUST contain the same number of cells (although some of these cells may be empty). Given this constraint, not

Note

Not all CSV-encoded data can be considered to be parsed into a tabular data. As such, the procedures and rules defined in this document cannot be applied to all CSV files. This document relies on terms (e.g. group, table, column, row, cell) defined data model. An algorithm for parsing CSV-based files is described in [ tabular-data-model ].

3. Mapping Core Tabular Data Typographical conventions

The procedures following typographic conventions are used in this specification:

markup
Markup (elements, attributes, properties), machine processable values (string, characters, media types), property name, or a file name is in red-orange monospace font.
variable
A variable in pseudo-code or in an algorithm description is in italics.
definition
A definition of a term, to be used elsewhere in this or other specifications, is in bold and rules for mapping tabular data compliant with italics.
definition reference
A reference to a definition in this document is underlined and is also an active link to the core tabular data model definition itself.
markup definition reference are described below.
A references to a definition in this document , when the reference itself is also a markup, is underlined, red-orange monospace font, and is also an active link to the definition itself.
external definition reference
A reference to a definition in another document is underlined, in italics, and is also an active link to the definition itself.
markup external definition reference
A reference to a definition in another document , when the reference itself is also a markup, is underlined, in italics red-orange monospace font, and is also an active link to the definition itself.
hyperlink
A hyperlink is underlined and in blue.
[reference]
A document reference (normative or informative) is enclosed in square brackets and links to the references section.
Note

Core Tabular Data lacks any annotation; neither from the Notes are in light green boxes with a green left border and with a "Note" header line within in green. Notes are normative or informative depending on the CSV file nor from whether they are in a separate metadata document. normative or informative section, respectively.

Example 1
Examples are in light khaki boxes, with khaki left border, and with a 
numbered "Example" header in khaki. Examples are always informative. 
The
content
of
the
example
is
in
monospace
font
and
may
be
syntax
colored.

3.1 4. Generating Converting Tabular Data to JSON

The procedures for converting tabular data into JSON are described below for both standard and minimal modes.

3.1.1 4.1 Table-level processing Algorithm terms

about URL
The root object of the output graph about URL SHALL describe annotation on the table current cell . As defined in [ tabular-data-model ].
annotated table
The root annotated table is defined in [ tabular-data-model ] as describing a particular table and its annotations.
array
An array is defined in JSON ([ RFC7159 ]) as an ordered sequence of zero or more values, where a value is a string, number, boolean, null, object SHALL contain , or array .
cell
A cell is defined in [ tabular-data-model ] as the intersection of a reference row and a column within a table .
cell errors
Cell errors are defined in [ tabular-data-model ] as a (possibly empty) list of validation errors generated while parsing the literal content of a cell to generate the CSV-encoded distribution semantic value .
cell value
A cell value is defined in [ tabular-data-model ] as the semantic value of the tabular data. The distribution SHALL cell ; this MAY be described using an object with name distribution null or a sequence of values.
column
A column is defined in [ tabular-data-model ] as a vertical arrangement of cells within a table .
group of tables
A group of tables is defined in [ tabular-data-model ] as comprising a set of annotated tables and a set of annotations that contains the name/value pair "downloadURL": " [CSV-LOCATION] " where relate to that group.
[CSV-LOCATION] group of tables identifier
The group of tables identifier is the absolute URL id annotation on a group of tables . As defined in [ tabular-data-model ].
name
In the source CSV file. context of this specification, name is used as defined in JSON ([ RFC7159 Note ]); that is, that name is a string that provides a unique key within a set of name-value pairs within a JSON object .
non-core annotations The semantics
Core annotations are listed in [ tabular-data-model ]; groups of properties distribution tables and downloadURL correspond with the properties tables may also have other annotations that are not defined in that specification; these are known as non-core annotations .
dcat:distribution notes
A list of notes , as defined in [ tabular-data-model and ], attached to an annotated table or group of tables using the notes property. This may be an empty list.
dcat:downloadURL object
An object is defined in JSON ([ RFC7159 ]) as unordered collection of zero or more name-value pairs, where a name is a string and a value is a string, number, boolean, null, object , or array .
property URL
The property URL annotation on the current cell . As defined in [ vocab-dcat tabular-data-model ].
row
The row is defined in [ tabular-data-model Issue 93 ] as a horizontal arrangement of cells within a table .
row number
A row number is defined in [ tabular-data-model Are ] as the abstract position of the row within the table , starting from 1.
row source number
A row source number is defined in [ tabular-data-model ] as the position of the row within the source tabular data file . Provision of the row source number is dependent on parsing applications and may be reported as null .
subject
Within this algorithm, a subject is the CSV resource that encodes it the same thing? (Is DCAT distribution appropriate?) value of a given cell refers to. This may be specified using about URL .
table identifier
The root object SHALL contain an array named row containing one object for each of table identifier is the rows id within annotation on an annotated table . As defined in [ tabular-data-model ].
value URL
The value URL annotation on the tabular data. current cell . As defined in [ tabular-data-model ].

Issue 97 4.2 Generating JSON

A conformant JSON conversion application MUST produce output conforming to this algorithm according to the chosen mode of conversion: standard or minimal .

Note

What should Where an annotated table is defined in isolation (e.g. in the name absence of the property be a group of tables ), a default group of tables is provided with a single tables annotation that relates rows refers to the table? row is one option; hasRow is another. given table .

Refer to Section 3.1.2 Row-level processing for further details.

3.1.2 4.2.1 Row-level processing Minimal mode

Each row The steps in the tabular data is processed sequentially. algorithm defined here apply to minimal mode.

  1. Each object in Insert an empty array A into the output graph JSON output. The objects corresponding to a row containing the name-value pairs associated with the cell values will be subsequently inserted into this array .

  2. Each table is processed sequentially in the tabular data SHALL contain one name/value pair for order they are referenced in the group of tables . For each column table where the cell value suppress output annotation is not null (e.g. where the cell does not contain an empty string; "" ). false :

    1. The value of name SHALL be _col= [N] where [N] Each row within the table is processed sequentially in order. For each row in the column number current table :

      1. Generate a sequence of objects , whilst the value S 1 to S n , each of value SHALL be provided which corresponds to a subject described by the associated cell value current row , as described in 4.3 Generating Objects .

        Issue 33 Note

        What do The subject(s) described by each row are determined according to with conversion if no column name is given? Where the about URL annotation for each cell value is null , the name/value pair SHALL be omitted from in the output graph current row . Where about URL is undefined, a default subject for the row is used.

      2. Given As described in 4.4 Generating Nested Objects , process the absence sequence of metadata annotations objects , S 1 to indicate the type of data present in S n , to produce a given column, all cell values SHALL new sequence of root be treated as strings. objects , S R 1 to S R m , that MAY include nested objects .

        Issue 98 Note

        Should the mapping output for a given A row include a reference to MAY describe multiple interrelated subjects ; where the CSV source row? value URL annotation on one cell matches the about URL annotation on another cell in the same row .

      3. Insert each root object , S R 1 to S R m , into array A .

3.2 4.2.2 Examples Standard mode

The following example provides a numeric score for four fictional people. A row number is included for convenience. There are four columns and four rows. Given that no metadata annotations are provided, it is very difficult steps in the algorithm defined here apply to ascertain standard mode.

  1. Insert an empty object G into the subject of JSON output which is associated with the tabular data without additional insight. group of tables .

    1 Jill Smith 50 2 Eve 94 3 Adam Johnson

  2. If the group of tables has an identifier I G 4 John Doe 80 ; insert the following name-value pair into object G :

    name
    The CSV input (published at http://example.org/people-and-points.csv @id ): 1,Jill,Smith,50 2,Eve,,94 3,Adam,Johnson, 4,John,Doe,80 The resulting JSON output graph: { "distribution": { "downloadURL": "http://example.org/people-and-points.csv" }, "row": [{ "_col=1": "1", "_col=2": "Jill", "_col=3": "Smith", "_col=4": "50" },{ "_col=1": "2", "_col=2": "Eve", "_col=4": "94" },{ "_col=1": "3", "_col=2": "Adam", "_col=3": "Johnson" },{ "_col=1": "4", "_col=2": "John", "_col=3": "Doe", "_col=4": "80" }] }
    value
    I G

  3. Insert any notes and non-core annotations specified for the group of tables into object G according to the rules provided in 4. 5. Mapping Annotated Tabular Data JSON-LD to JSON .

  4. The procedures and rules for mapping annotated tabular data compliant with Insert the annotated tabular data model following name-value pair into object are described below. G :

    name
    table
    value
    A T

    The metadata for where A T is an array into which the objects describing the annotated tabular data MAY tables will be provided by either or both subsequently inserted.

  5. Each table is processed sequentially in the order they are referenced in the group of tables .

    For each table where the following sources: suppress output annotation is false :

    1. Insert an empty object T into the header line array within A T to represent the CSV file; and/or table .

    2. If the table description , schema and column descriptions has an identifier (as defined in [ I T tabular-metadata ; insert the following name-value pair into object T :

      name
      ]) within the associated metadata document. @id
      value
      I T

    3. Mapping applications SHALL establish a column description object Specify the source tabular data file URL for each column the current table based on the url within annotation; insert the annotated tabular data. The column description following name-value pair into object contains the aggregated set of metadata properties T :

      name
      url
      value
      URL

    4. Insert any notes and non-core annotations specified for a given column that affect how the cell values table within into object T according to the associated column are expressed rules provided in the output graph 5. JSON-LD to JSON . Metadata properties are sourced from the header line

      Note

      All other core annotations in for the CSV file and column description table in are ignored during the metadata document conversion; including information about table schemas and enriched with inherited properties columns from specified therein, foreign keys , direction , transformations etc.

    5. Insert the table description following name-value pair into object and schema . T :

      name
      row
      value
      A R

      The output graph where A R is an array MAY include some Direct Annotations into which the objects sourced from describing the metadata document. Where these are natural language properties , no locale information can rows will be provided given subsequently inserted.

    6. Each row within the lack of multi-lingual support table is processed sequentially in JSON. Where order. For each row in the current table :

      1. Insert an empty object R into the array of values A R to represent the row .

      2. Specify the row number n for a property are provided the row ; insert the following name-value pair into object R :

        name
        rownum
        value
        n

      3. Specify the row source number n source for the row within the source tabular data file URL using a language map (as defined fragment-identifier as specified in [ json-ld RFC7111 ]) the array of locale-specific values SHALL be included in the output graph ]; if row source number - albeit without is not null , insert the inferred semantics about language codes. following name-value pair into object R :

        name
        url
        value
        URL #row= n source

      4. Clearly, in order Insert any non-core annotations specified for the row into object R according to process annotated tabular data, a mapping application MUST have access the rules provided in 5. JSON-LD to JSON .

      5. Insert the full metadata description following name-value pair into object R :

        name
        describes
        value
        A

        where A is an array . The objects containing the name-value pairs associated with the tabular data. cell values will be subsequently inserted into this array .

      6. URL expansion behaviour Generate a sequence of relative URLs SHALL be consistent with Section 6.3 IRI Expansion objects , S 1 to S n , each of which corresponds to a subject described by the current row , as described in [ json-ld-api 4.3 Generating Objects ]. .

        Note

        The base URL provides subject(s) described by each row are determined according to the about URL against which relative URLs from annotated tabular data are resolved. The base annotation for each cell in the current row . Where about URL SHALL be that of is undefined, a default subject for the source CSV file. row is used.

      7. As described in 4.4 Generating Nested Objects , process the sequence of objects , S 1 to S n , to produce a new sequence of root objects , S R 1 to S R m , that MAY include nested objects .

        Issue 91 Note

        What is default A row MAY describe multiple interrelated subjects ; where the value if @base is not defined URL annotation on one cell matches the about URL annotation on another cell in the metadata description? same row .

      8. Insert each root object , S R 1 to S R m , into array A .

4.1 4.3 Generating JSON Objects

The steps in the algorithm defined here apply to both standard and minimal modes.

This algorithm generates a sequence of objects , S 1 to S n 4.1.1 Table-level processing , each of which corresponds to a subject described by the current row . The algorithm inserts name-value pairs into S i depending on the cell values as outlined in the following steps.

  1. Determine the unique subjects for the current row . The root object of subject(s) described by each row are determined according to the output graph about URL SHALL describe annotation for each cell in the annotated table current row . A default subject for the row is used for any cells where about URL is undefined.

  2. Where provided in For each subject that the table description , current row describes where at least one of the metadata property cells that refers to that subject has a value or value URL that is not @id SHALL be used null , and is associated with a column where suppress output annotation is false :

    1. Create an empty object S i to identify represent the root object. subject i .

      The root object SHALL be identified using ( i is the name/value pair "url": " [@id] " index number with values from 1 to n , where n is the number of subjects for the row )

      Subject i is identified according to the about URL annotation of its associated cells : I S . For a [@id] default subject where about URL is not specified by its cells , I S is the value of metadata property @id null .

    2. The root If the identifier for subject i , I S , is not null , then insert the following name-value pair into object SHALL contain a reference S i :

      name
      @id
      value
      I S

    3. Each cell referring to subject i is then processed sequentially according to the CSV-encoded distribution order of the tabular data. columns .

      The distribution SHALL be described using an object For each cell referring to subject i , where the suppress output annotation for the column associated with name distribution that contains the name/value pair "downloadURL": " [CSV-LOCATION] " where cell is false , insert a name-value pair into object S i [CSV-LOCATION] is as described below:

      1. If the absolute value of property URL for the cell is not null , then name N takes the value of property URL compacted according to the source CSV file. rules as defined in URL Compaction Note in [ tabular-metadata The semantics ].

        Else, name N takes the value of properties distribution and downloadURL correspond the name annotation for the column associated with the properties cell .

      2. If the value URL for the current cell is not dcat:distribution null , then insert the following name-value pair into object S i and :

        name
        dcat:downloadURL N
        value
        V url

        where V url is the value of value URL annotation for the current cell expressed as a string in the JSON output. If N is @type , compact V url according to the rules as defined in URL Compaction in [ vocab-dcat tabular-metadata ].

      3. Else, if the cell value is a list that is not empty, then the cell value provides a sequence of values for inclusion within the JSON output; insert an array A v containing each value V of the sequence into object S i :

        name
        N
        value
        A v Issue 93

        Each of the values V derived from the sequence MUST be expressed in the JSON output according to the datatype of V as defined below in section 4.5 Interpreting datatypes .

        Note

        Are the abstract tabular data and Since arrays are implicitly ordered in JSON, the CSV that encodes it ordered annotation has no effect on the same thing? (Is DCAT distribution appropriate?) JSON output.

      4. Where a header line Else, if the cell value is present in the CSV file then, for each column , not null , then the cell value provides a single value V for inclusion within the JSON output; insert the following name-value pair into object S i :

        name
        N
        value
        V

        Value V derived from the column header SHALL cell values MUST be assigned expressed in the JSON output according to metadata property name within the column description object datatype for that column of the value as defined in section 4.5 Interpreting datatypes .

    4. Where the column header is null , If name N occurs more than once within object S i , the value assigned to name-value pairs from each occurrence of name SHALL N MUST be _col= [N] compacted to form a single name-value pair with name N and whose value is an array containing all values from each of those name-value pairs.

where [N] 4.4 Generating Nested Objects is

The steps in the column number . algorithm defined herein apply to both standard and minimal modes.

Where present in the table description current row describes multiple subjects , the following metadata properties SHALL it MAY be included in possible to organise the output graph objects associated with those subjects such that some objects are nested within others; e.g. where the root object: notes - value URL annotation for one cell matches the array about URL annotation for another cell in the same row . This algorithm considers a sequence of objects representing structured annotations on generated according to 4.3 Generating Objects , S 1 to S n , each of which corresponds to a subject described by the tabular data SHALL current row . It generates a new sequence of root objects , S R 1 to S R m , that MAY be included verbatim. include nested objects .

Note

The Web Annotation Working Group Where the current row is developing describes only a vocabulary for expressing annotations which we anticipate referencing from single subject , this specification. Issues likely to algorithm may be covered therein include: how to anchor the annotation to bypassed as no nesting is possible. In such a target in the tabular data and/or CSV file, what form case, the annotations themselves may take (e.g. a simple literal annotation body, or whether additional formatting properties are required root object S R 1 is identical to indicate that the annotation is expressed in, say, Markdown or HTML). original object S 1 .

Issue 71 Note
Exact handling of annotations. Additionally, the mechanism to reference the annotation target (within tabular data)

This nesting algorithm is still unclear - especially based on the interrelationships between subjects described within a given row that are specified using the confusion on identifying value URL annotation. Cell values expressing the identity of a subject in the current row numbers ( ISSUE #68 refers). (i.e., as a simple literal) will be ignored by this algorithm.

Any Common Properties The algorithm uses the following terms:

child (as defined
If two vertices are connected in Section 3.3 Common Properties a tree , the one which is further away from the root of [ tabular-metadata the tree is referred to as the child of the other.
]). Any descendant
A vertex N is a descendant of a vertex M if either N is the inherited properties child null , separator , format , datatype , M , or default defined within the table description there are vertices and/or schema V 1 ,…,V k , such that V 1 =M , V k =N , and V k+1 is a child SHALL of V k .
edge
One of the main constituents of graphs ; in such data structures edges be added are used to establish relationships among vertices . In the column description context of this algorithm, edges are expressed in JSON using a name-value pair whose value is another object for each column or an array of objects . Where
forest
A collection of disjoint trees . For the same property is defined in both purpose of this algorithm, the table description order of the trees are important, i.e., forests can also be viewed as a sequence of roots .
graph
Data structure consisting of vertices (or "nodes") and edges . See, for example, [ Knuth ] for further details.
node
Synonym of vertex .
root
A dedicated vertex in a tree ; a root is not the schema child of any vertex .
tree
A tree (or rooted tree ) is a connected, acyclic graph where one vertex has been designated as the root , in which case the value edges have a natural orientation towards or away from the schema root .
vertex
One of the main constituents of graphs SHALL ; in such data structures a vertex take precedence. usually holds further information or data. In the context of this algorithm, vertices are used to represent the JSON objects .

The nesting algorithm is defined as follows:

  1. Each column description SHALL be matched to a column For all cells in the tabular data based on current row , determine the order value URLs , V url , that the description occur only once . The list of these uniquely occurring value URLs is listed referred to as the URL-list .

  2. Create an empty forest F . Vertices in the columns array trees of this forest represent the schema subjects described by the current row .

  3. For each column description object S i in the metadata document, the following metadata properties SHALL be added sequence S 1 to S n :

    1. Determine the relevant column description identity of object established by the mapping application: S i : I S . If present in object S i , the name-value pair with name . Where metadata property name @id is also provided via the header line provides the value from the column description of I S . Else, object in the metadata document SHALL take precedence. S i is not explicitly identified and I S is predicateUrl null .

    2. Check whether there is a vertex N in forest F that represents object S i urlTemplate . . If none of the existing vertices in forest F represent object S i , then insert a new tree into forest F whose root is a vertex N that represents object S i and has identity I S .

    3. For all cells associated with the current object S i Inherited properties (e.g. whose about URL null , separator , format , datatype , annotation matches I S ):

      1. If the value URL annotation of the current cell is defined and default are added to its value, V url , appears in the column description object , overwriting values added URL-list , then check each of the other objects in the previous step where properties are duplicated. sequence S 1 to S n to determine if V url identifies one of those objects .

        For each column description object where metadata property S j , if the name-value pair with name predicateUrl @id has not been assigned within is present and its value matches V url , then:

        1. If the column description , root of the value tree containing vertex N is a vertex that represents object S j , then object S i is already a descendant of predicateUrl SHALL object S j ; no further action should be set as taken for this instance of V url .

          Note

          This clause in the algorithm prevents circular loops being created.

          Furthermore, because the URL-list contains value URLs that occur only once for the current row , object S i cannot be a descendant of metadata property name . an intermediate vertices in the tree .

        2. The Else, if there is a root vertex M in forest F that represents object SHALL contain an array named row containing one object for each S j , then set vertex M as a child of vertex N and remove vertex M from the rows list of roots within in forest F (i.e., the tabular data. tree rooted by M becomes a sub-tree of N ).

        3. Refer to Section 4.1.2 Row-level processing Else, create a new vertex for further details. M that represents object S j as a child of vertex N .

  4. The output graph Each vertex MAY contain information about in forest F represents an object in the metadata documents original sequence of objects S 1 to S n and is associated with a subject described by the current row . Rearrange objects S 1 to S n such that were used when when creating they mirror the output graph structure of the trees using in forest F as follows: If vertex M , representing object S i , is a child of vertex N , representing object S j , then the following name/value name-value pair in object S j associated with the edge relating M and N MUST for each metadata document: be modifed such that the (literal) value, V url   "describedBy": " , from that name-value pair is replaced by object S i thus creating a [Metadata Location] nested " object .

    where
    Note

    Objects represented by root vertices are referred to as [Metadata Location] is root objects .

  5. Return the absolute URL sequence of the metadata document. root objects , S R 1 to S R m .

Note

An implementation may be able to optimize the algorithm by skipping branches (e.g. if URL-list is empty) or by other means.

4.1.2 4.5 Row-level processing Interpreting datatypes

Each row Cell values are expressed in the tabular data is processed sequentially. The behaviour exhibited when processing a given cell within JSON output according to the current row is dependent on cell value's datatype . The relationship between the metadata properties value of the column description object cell value's datatype for and the column that that cell primitive types supported by JSON (as specified in [ RFC7159 resides in. The effect of each metadata property ]) is provided in the table below.

Note

Instances of JSON reserved characters within string values MUST be escaped as defined in Section 4.1.3 Metadata property effects on row-level mapping behaviour [ RFC7159 ].

Each object in JSON has no native support for expressing language information; therefore the output graph language corresponding to of a row value has no effect on the JSON output.

Note

A datatype's format is irrelevant to the conversion procedure defined in this specification; the tabular data SHALL contain one name/value pair for each column cell value where has already been parsed from the contents the cell value is not null . according to the format annotation.

Where the metadata property urlTemplate is provided in the schema , each object in contents of the output graph cell corresponding to a row cannot be parsed, or other validation errors occur, cell errors in the tabular data SHALL will be explicitly identified using provided. It is an implementation decision to determine how conversion applications should proceed in the name/value pair event that cell errors are encountered.

"url": " [EXPANDED-URI-TEMPLATE] " datatype where JSON primitive type
anyAtomicType [EXPANDED-URI-TEMPLATE] string
anyURI is string
base64Binary string
boolean boolean
date string
dateTime string
dateTimeStamp string
decimal number
integer number
long number
int number
short number
byte number
nonNegativeInteger number
positiveInteger number
unsignedLong number
unsignedInt number
unsignedShort number
unsignedByte number
nonPositiveInteger number
negativeInteger number
double number
duration string
dayTimeDuration string
yearMonthDuration string
float number
gDay string
gMonth string
gMonthDay string
gYear string
gYearMonth string
hexBinary string
QName string
string string
normalizedString string
token string
language string
Name string
NMTOKEN string
xml string
html string
json string
time string

5. JSON-LD to JSON

This section defines a mechanism for transforming the value resulting [ json-ld ] dialect used for non-core annotations and notes originating from the expansion processing of the metadata (as defined in [ uri-template tabular-metadata ] specified in the urlTemplate property. ]) into JSON.

Note
The variables in the URI Template expression relate

Conversion applications may have other means to create annotated tables , e.g., through some application specific API-s. In such cases the name property specified exact format for each column . During template expansion, non-core annotations or notes may be different. Specifications for such annotation processes should specify how these annotations should be converted into RDF.

Name-value pairs from notes and non-core annotations annotations are generally copied verbatim from the variables evaluate metadata description subject to the cell exceptions below:

  1. Name-value pairs whose value is an object within using the row [ json-ld being processed that is associated with the named column . ] keyword @value , for example:

    The variable
    name
    N
    value
    _row { "@value": " evaluates to the number of the row being processed. V " }

    are transformed to:

    name
    N
    value
    V

    Once the URL has been generated via Name-value pairs occurring within the template expansion, relative URLs value object that use [ json-ld ] keywords @language and @type are resolved against ignored.

  2. Name-value pairs whose value is an object using the base URL [ json-ld ] keyword @id to create coerce a string-value to be interpreted as an absolute URL. IRI, for example:

    name
    N
    value
    { "@id": " V url " }

    are transformed to:

    name
    N
    value
    V url

Where In addition to compacting values of property URLs , URLs which ware the cell value is null , of @type used within the name/value pair SHALL be omitted from notes and non-core annotations are compacted according to the output graph rules as defined in URL Compaction unless a in [ tabular-metadata ].

6. Examples

default value This section is non-normative.

Note

Each of the examples expresses more complex conversions - it is specified for recommended that column readers of this specification work through the examples in sequential order.

6.1 Simple example

This example comprises a single annotated table (see metadata properties null containing information attributes about countries; country code, position (latitude, longitude) and name. Whilst the input tabular data file, published at default ). http://example.org/countries.csv , includes a header line , no further metadata annotations are given. The tabular data file is provided below:

Example 2: http://example.org/countries.csv
countryCode,latitude,longitude,name
AD,42.546245,1.601554,Andorra
AE,23.424076,53.847818,"United Arab Emirates"
AF,33.93911,67.709953,Afghanistan

The value of name annotated table generated from parsing the tabular data file is shown below and provides the basis for the name/value pair SHALL be provided by conversion to JSON.

Annotations for the resulting table T , with 4 columns and 3 rows, are shown below:

id core annotations
url columns rows
T predicateUrl http://example.org/countries.csv metadata property within C1 , C2 , C3 , C4 R1 , R2 , R3

Annotations for the column description object . columns , rows and cells in table T are shown in the tables below.

In accordance with [ json Column ], all unicode characters may be used. However, the following characters SHALL be escaped : annotations:

quotation mark;
id core annotations
table number source number cells name titles
C1 T 1 1 C1.1 , C2.1 , C3.1 " countryCode ( U+0022 countryCode ) reverse solidus;
C2 T 2 2 C1.2 , C2.2 , C3.2 \ latitude ( U+005C latitude ) control characters; (
C3 T 3 3 C1.3 , C2.3 , C3.3 U+0000 longitude through U+001F longitude )
C4 T 4 4 C1.4 , C2.4 , C3.4 name name

The value of Row annotations:

id core annotations
table number source number cells
R1 T 1 2 C1.1 , C1.2 , C1.3 , C1.4
R2 T 2 3 C2.1 , C2.2 , C2.3 , C2.4
R3 T 3 4 C3.1 , C3.2 , C3.3 , C3.4

Cell annotations:

id core annotations
table column row string value SHALL be provided by the associated cell value property URL
C1.1 T C1 R1 "AD" "AD" null
C1.2 T C2 R1 "42.546245" "42.546245" null
C1.3 T C3 R1 "1.601554" "1.601554" null
C1.4 T C4 R1 "Andorra" "Andorra" null
C2.1 T C1 R2 "AE" "AE" null
C2.2 T C2 R2 "23.424076" "23.424076" null
C2.3 T C3 R2 "53.847818" "53.847818" null
C2.4 T C4 R2 "United Arab Emirates" "United Arab Emirates" null
C3.1 T C1 R3 "AF" "AF" null
C3.2 T C2 R3 "33.93911" "33.93911" null
C3.3 T C3 R3 "67.709953" "67.709953" null
C3.4 T C4 R3 "Afghanistan" "Afghanistan" null

Minimal mode subject to the effect of the metadata properties output for that column (if any are specified). this example is provided below:

Example 3: http://example.org/countries-minimal.json
[{ 
  "countryCode": "AD", 
  "latitude": "42.546245", 
  "longitude": "1.601554", 
  "name": "Andorra" 
}, { 
  "countryCode": "AE", 
  "latitude": "23.424076", 
  "longitude": "53.847818", 
  "name": "United Arab Emirates" 
}, { 
  "countryCode": "AF", 
  "latitude": "33.93911", 
  "longitude": "67.709953", 
  "name": "Afghanistan" 


}]
Note

Given the lack of multi-lingual support The about URL annotation has not been set for cells in JSON, internationalized strings table T ( { "url": "http://example.org/countries.csv"} ); cells in a given row where about URL has not been specified are simply copied verbatim into assumed to refer to the output graph same subject without any additional locale information. Also note that and so the name-value pairs associated with the cell values of metadata property name must be unique that row occur within a table . Therefore if, say, English and French versions of the same object .

Given that the property are provided as complementary columns URL is null for cells in a CSV file then their table T ( name { "url": "http://example.org/countries.csv"} properties must be different; ), the simplified name is used in the name-value pairs; e.g. title_en countryCode and rather than titre_fr . It may be possible http://example.org/countries.csv#countryCode

Standard mode output for applications to infer a language from this example is provided below:

Example 4: http://example.org/countries-standard.json
{
  "table": [{
    "url": "http://example.org/countries.csv",
    "row": [{
      "url": "http://example.org/countries.csv#row=2",
      "rownum": 1,
      "describes": [{ 
        "countryCode": "AD", 
        "latitude": "42.546245", 
        "longitude": "1.601554", 
        "name": "Andorra" 
      }]
    }, {
      "url": "http://example.org/countries.csv#row=3",
      "rownum": 2,
      "describes": [{ 
        "countryCode": "AE", 
        "latitude": "23.424076", 
        "longitude": "53.847818", 
        "name": "United Arab Emirates"
      }]
    }, {
      "url": "http://example.org/countries.csv#row=4",
      "rownum": 3,
      "describes": [{  
        "countryCode": "AF", 
        "latitude": "33.93911", 
        "longitude": "67.709953", 
        "name": "Afghanistan" 
      }]
    }]
  }]

}
Note

Even though the name of table was defined in isolation, the annotated table is wrapped in a column group of tables .

The name-value pair with name url provides reference to the original tabular data file and to specific rows therein.

The row number - but this is entirely dependant on provided for each row using name-value pair with name rownum .

The object containing the syntax used by name-values pairs associated with the metadata author when defining cell values of a row are related to the object for that row using the name-value pair with name property. describes .

4.1.3 6.2 Metadata property effects Example with single table and rich annotations

This example is based on row-level mapping behaviour Use Case #11 - City of Palo Alto Tree Data and comprises a single annotated table describing an inventory of tree maintenance operations. The input tabular data file, published at http://example.org/tree-ops-ext.csv , and the associated metadata description http://example.org/tree-ops-ext.csv-metadata.json are provided below:

Example 5: http://example.org/tree-ops-ext.csv
GID,On Street,Species,Trim Cycle,Diameter at Breast Ht,Inventory Date,Comments,Protected,KML

1,ADDISON AV,Celtis australis,Large Tree Routine Prune,11,10/18/2010,,,"<Point><coordinates>-122.156485,37.440963</coordinates></Point>"
2,EMERSON ST,Liquidambar styraciflua,Large Tree Routine Prune,11,6/2/2010,,,"<Point><coordinates>-122.156749,37.440958</coordinates></Point>"
6,ADDISON
AV,Robinia
pseudoacacia,Large
Tree
Routine
Prune,29,6/1/2010,cavity
or
decay;
trunk
decay;
codominant
leaders;
included
bark;
large
leader
or
limb
decay;
previous
failure
root
damage;
root
decay;
beware
of
BEES,YES,"<Point><coordinates>-122.156299,37.441151</coordinates></Point>"
Example 6: http://example.org/tree-ops-ext.csv-metadata.json
{
  "@context": ["http://www.w3.org/ns/csvw", {"@language": "en"}],
  "@id": "http://example.org/tree-ops-ext",
  "url": "tree-ops-ext.csv",
  "dc:title": "Tree Operations",
  "dcat:keyword": ["tree", "street", "maintenance"],
  "dc:publisher": [{
    "schema:name": "Example Municipality",
    "schema:url": {"@id": "http://example.org"}
  }],
  "dc:license": {"@id": "http://opendefinition.org/licenses/cc-by/"},
  "dc:modified": {"@value": "2010-12-31", "@type": "xsd:date"},
  "notes": [{
    "@type": "oa:Annotation",
    "oa:hasTarget": {"@id": "http://example.org/tree-ops-ext"},
    "oa:hasBody": {
      "@type": "oa:EmbeddedContent",
      "rdf:value": "This is a very interesting comment about the table; it's a table!",
      "dc:format": {"@value": "text/plain"}
    }
  }],
  "dialect": {"trim": true},
  "tableSchema": {
    "columns": [{
      "name": "GID",
      "titles": [
        "GID",
        "Generic Identifier"
      ],
      "dc:description": "An identifier for the operation on a tree.",
      "datatype": "string",
      "required": true, 
      "suppressOutput": true
    }, {
      "name": "on_street",
      "titles": "On Street",
      "dc:description": "The street that the tree is on.",
      "datatype": "string"
    }, {
      "name": "species",
      "titles": "Species",
      "dc:description": "The species of the tree.",
      "datatype": "string"
    }, {
      "name": "trim_cycle",
      "titles": "Trim Cycle",
      "dc:description": "The operation performed on the tree.",
      "datatype": "string",
      "lang": "en"
    }, {
      "name": "dbh",
      "titles": "Diameter at Breast Ht",
      "dc:description": "Diameter at Breast Height (DBH) of the tree (in feet), measured 4.5ft above ground.",
      "datatype": "integer"
    }, {
      "name": "inventory_date",
      "titles": "Inventory Date",
      "dc:description": "The date of the operation that was performed.",
      "datatype": {"base": "date", "format": "M/d/yyyy"}
    }, {
      "name": "comments",
      "titles": "Comments",
      "dc:description": "Supplementary comments relating to the operation or tree.",
      "datatype": "string",
      "separator": ";"
    }, {
      "name": "protected",
      "titles": "Protected",
      "dc:description": "Indication (YES / NO) whether the tree is subject to a protection order.",
      "datatype": {"base": "boolean", "format": "YES|NO"},
      "default": "NO"
    }, {
      "name": "kml",
      "titles": "KML",
      "dc:description": "KML-encoded description of tree location.",
      "datatype": "xml"
    }],
    "primaryKey": "GID",
    "aboutUrl": "http://example.org/tree-ops-ext#gid-{GID}"
  }


}
Note

The notes annotation in the metadata description uses the Open Annotation data model currently under development within the Web Annotations Working Group . This is purely illustrative; no constraints are placed on the value of the notes annotation.

The following annotated table generated from parsing the tabular data file and associated metadata properties modify is shown below and provides the way that cell values basis for the conversion to JSON.

Core annotations for the resulting table T , with 9 columns and 3 rows , are incorporated into shown below:

id core annotations
id url columns rows notes
T <http://example.org/tree-ops-ext> http://example.org/tree-ops-ext.csv C1 , C2 , C3 , C4 , C5 , C6 , C7 , C8 , C9 R1 , R2 , R3 [{ "@type": "oa:Annotation", ... }]

Non-core annotations for the output graph : table T are:

null dc:title
By default, a cell value is deemed to be null if it contains an empty string. If specified, the metadata property null "Tree Operations" provides a token (string) that can be used to identify null values.
separator dcat:keyword
Where metadata property separator ["tree", "street", "maintenance"] is defined, the cell value SHALL be parsed into an ordered list of values, using the value of
separator dc:publisher as the delimiter. The list of values SHALL be expressed in the output graph as an array.
[{ "schema:name": "Example Municipality", "schema:url": { "@id": "http://example.org" } }]
datatype dc:license and
format { "@id": "http://opendefinition.org/licenses/cc-by/" }
dc:modified
Where metadata property datatype "2010-12-31" is undefined,
Note

The value of the column notes SHALL be inferred to hold values of datatype string . annotation has been shortened for clarity in the table above.

The following datatypes Annotations for the columns , rows and cells in table T are given special attention: shown in the tables below.

Datatypes with embedded syntax: Column annotations:

] refers. If a boolean type is declared, the cell value SHALL be processed as follows: if
id core annotations annotations
table number source number cells name titles required suppress output xml , dc:description
C1 T 1 1 C1.1 , C2.1 , C3.1 json GID and html . These datatypes are treated as literal values; no attempt SHOULD be made to 'unpack' the structured syntax to create sub-objects within the output graph GID , Generic Identifier Booleans: boolean . Metadata property true format true MAY be provided An identifier for the operation on a boolean-typed column ; providing non-standard tokens for true and false (e.g. tree.
C2 T 2 2 C1.2 , C2.2 , C3.2 Y|N . Section 3.12.3 Formats for booleans from [ on_street tabular-metadata On Street The street that the value tree is on.
C3 T 3 3 C1.3 , C2.3 , C3.3 true , species 1 Species or, if The species of the tree.
C4 T 4 4 C1.4 , C2.4 , C3.4 format trim_cycle property is defined, Trim Cycle The operation performed on the value tree.
C5 T 5 5 C1.5 , C2.5 , C3.5 dbh Diameter at Breast Ht Diameter at Breast Height (DBH) of true , then the output graph SHALL include the value tree (in feet), measured 4.5ft above ground.
C6 T 6 6 C1.6 , C2.6 , C3.6 true inventory_date ; else if Inventory Date The date of the value is operation that was performed.
C7 T 7 7 C1.7 , C2.7 , C3.7 false , comments 0 Comments or, if Supplementary comments relating to the operation or tree.
C8 T 8 8 C1.8 , C2.8 , C3.8 format protected property is defined, Protected Indication (YES / NO) whether the value tree is subject to a protection order.
C9 T 9 9 C1.9 , C2.9 , C3.9 kml KML KML-encoded description of false , then the tree location.
Note

In this example, output graph for column SHALL include the value C1 ( false GID ; else ) is not required; note the suppress output graph SHALL include the cell value annotation on this column .

Row verbatim. annotations:

id core annotations
table number source number cells primary key
R1 T 1 2 C1.1 , C1.2 , C1.3 , C1.4 , C1.5 , C1.6 , C1.7 , C1.8 , C1.9 C1.1
R2 T 2 3 C2.1 , C2.2 , C2.3 , C2.4 , C2.5 , C2.6 , C2.7 , C2.8 , C2.9 C2.1
R3 T 3 4 C3.1 , C3.2 , C3.3 , C3.4 , C3.5 , C3.6 , C3.7 , C3.8 , C3.9 C3.1

Numbers: Cell annotations:

id core annotations
table column row string value value about URL
C1.1 T C1 R1 number , "1" decimal , "1" integer , http://example.org/tree-ops-ext#gid-1
C1.2 T C2 R1 nonPositiveInteger , "ADDISON AV" negativeInteger , "ADDISON AV" long , <http://example.org/tree-ops-ext#gid-1>
C1.3 T C3 R1 int "Celtis australis" "Celtis australis" <http://example.org/tree-ops-ext#gid-1>
C1.4 T C4 R1 "Large Tree Routine Prune" "Large Tree Routine Prune" (English) <http://example.org/tree-ops-ext#gid-1>
C1.5 T C5 R1 "11" 11 <http://example.org/tree-ops-ext#gid-1>
C1.6 T C6 R1 "10/18/2010" 2010-10-18 <http://example.org/tree-ops-ext#gid-1>
C1.7 T C7 R1 "" null <http://example.org/tree-ops-ext#gid-1>
C1.8 T C8 R1 "" false <http://example.org/tree-ops-ext#gid-1>
C1.9 T C9 R1 "<Point><coordinates>-122.156485,37.440963</coordinates></Point>" "<Point><coordinates>-122.156485,37.440963</coordinates></Point>" (XML) <http://example.org/tree-ops-ext#gid-1>
C2.1 T C1 R2 "2" "2" <http://example.org/tree-ops-ext#gid-2>
C2.2 T C2 R2 "EMERSON ST" "EMERSON ST" <http://example.org/tree-ops-ext#gid-2>
C2.3 T C3 R2 "Liquidambar styraciflua" "Liquidambar styraciflua" <http://example.org/tree-ops-ext#gid-2>
C2.4 T C4 R2 "Large Tree Routine Prune" "Large Tree Routine Prune" (English) <http://example.org/tree-ops-ext#gid-2>
C2.5 T C5 R2 "11" 11 <http://example.org/tree-ops-ext#gid-2>
C2.6 T C6 R2 "6/2/2010" 2010-06-02 <http://example.org/tree-ops-ext#gid-2>
C2.7 T C7 R2 "" null <http://example.org/tree-ops-ext#gid-2>
C2.8 T C8 R2 "" false <http://example.org/tree-ops-ext#gid-2>
C2.9 T C9 R2 "<Point><coordinates>-122.156749,37.440958</coordinates></Point>" "<Point><coordinates>-122.156749,37.440958</coordinates></Point>" (XML) <http://example.org/tree-ops-ext#gid-2>
C3.1 T C1 R3 "6" "6" <http://example.org/tree-ops-ext#gid-6>
C3.2 T C2 R3 "ADDISON AV" "ADDISON AV" <http://example.org/tree-ops-ext#gid-6>
C3.3 T C3 R3 "Robinia pseudoacacia" "Robinia pseudoacacia" <http://example.org/tree-ops-ext#gid-6>
C3.4 T C4 R3 "Large Tree Routine Prune" "Large Tree Routine Prune" (English) <http://example.org/tree-ops-ext#gid-6>
C3.5 T C5 R3 "29" 29 <http://example.org/tree-ops-ext#gid-6>
C3.6 T C6 R3 "6/1/2010" 2010-06-01 <http://example.org/tree-ops-ext#gid-6>
C3.7 T C7 R3 "cavity or decay; trunk decay; codominant leaders; included bark; large leader or limb decay; previous failure root damage; root decay; beware of BEES" "cavity or decay" , short "trunk decay" , nonNegativeInteger "codominant leaders" , unsignedLong "included bark" , unsignedInt "large leader or limb decay" , unsignedShort "previous failure root damage" , positiveInteger "root decay" , float "beware of BEES" and double . <http://example.org/tree-ops-ext#gid-6> Cell
C3.8 T C8 R3 "YES" true <http://example.org/tree-ops-ext#gid-6>
C3.9 T C9 R3 "<Point><coordinates>-122.156299,37.441151</coordinates></Point>" "<Point><coordinates>-122.156299,37.441151</coordinates></Point>" (XML) <http://example.org/tree-ops-ext#gid-6>
Note

The lists of values from cells that in column C7 ( "name": "comments" ) are asserted assumed to be numeric shall be expressed in unordered as the output graph boolean ordered as numbers; double quotes will be omitted. It is not uncommon for numbers within tabular data to be formatted for human consumption, annotation, which may involve using commas for decimal points, grouping digits in the number using commas, or adding currency symbols or percent signs defaults to the number. Metadata property format MAY false , has not be provided to describe the formatting of the cell values to assist the mapping application convert set within the cell value metadata description.

Minimal mode to a number format readily consumable by downstream applications. output for this example is provided below:

Example 7: http://example.org/tree-ops-ext-minimal.json
[{
  "@id": "http://example.org/tree-ops-ext#gid-1",
  "on_street": "ADDISON AV",
  "species": "Celtis australis",
  "trim_cycle": "Large Tree Routine Prune",
  "dbh": 11,
  "inventory_date": "2010-10-18",
  "protected": false,
  "kml": "<Point><coordinates>-122.156485,37.440963</coordinates></Point>"
}, {
  "@id": "http://example.org/tree-ops-ext#gid-2",
  "on_street": "EMERSON ST",
  "species": "Liquidambar styraciflua",
  "trim_cycle": "Large Tree Routine Prune",
  "dbh": 11,
  "inventory_date": "2010-06-02",
  "protected": false,
  "kml": "<Point><coordinates>-122.156749,37.440958</coordinates></Point>"
}, {
  "@id": "http://example.org/tree-ops-ext#gid-6",
  "on_street": "ADDISON AV",
  "species": "Robinia pseudoacacia",
  "trim_cycle": "Large Tree Routine Prune",
  "dbh": 29,
  "inventory_date": "2010-06-01",
  "comments": [ "cavity or decay", 
    "trunk decay", 
    "codominant leaders", 
    "included bark",
    "large leader or limb decay", 
    "previous failure root damage", 
    "root decay", 
    "beware of BEES" ],
  "protected": true,
  "kml": "<Point><coordinates>-122.156299,37.441151</coordinates></Point>"


}]
Issue 54 Note

Describing The subject described by each row is explicitly defined using the formatting about URL annotation; e.g. the subject of numbers row R1 is currently unresolved and http://example.org/tree-ops-ext#gid-1 .

Output for column C1 ( { "name": "GID" } ) is likely to require information on decimal separator characters, grouping characters and possibly others such not included as Infinity, Nan, currency tokens, negative numbers appearing in parentheses etc. column suppress output annotation is true .

In the interim, mapping applications are not required to undertake any reformatting Cells C1.7 and may simply pass the cell value to C2.7 ( rows R1 and R2 ; column , { "name": "comments" } ) have null values - no output is included for these cells .

Cell C3.7 ( row R3 ; column , { "name": "comments" } ) contains a sequence of values; the set of values are included in an array .

Standard mode output graph verbatim. for this example is provided below:

Example 8: http://example.org/tree-ops-ext-standard.json
{
  "table": [{
    "@id": "http://example.org/tree-ops-ext",
    "url": "http://example.org/tree-ops-ext.csv",
    "dc:title": "Tree Operations",
    "dcat:keyword": [ "tree", "street", "maintenance" ],
    "dc:publisher": [{
      "schema:name": "Example Municipality",
      "schema:url": "http://example.org"
    }],
    "dc:license": "http://opendefinition.org/licenses/cc-by/",
    "dc:modified": "2010-12-31",
    "notes": [{
      "@type": "oa:Annotation",
      "oa:hasTarget": "http://example.org/tree-ops-ext",
      "oa:hasBody": {
        "@type": "oa:EmbeddedContent",
        "rdf:value": "This is a very interesting comment about the table; it's a table!",
        "dc:format": "text/plain"
      }
    }],
    "row": [{
      "url": "http://example.org/tree-ops-ext.csv#row=2",
      "rownum": 1,
      "describes": [{ 
        "@id": "http://example.org/tree-ops-ext#gid-1",
        "on_street": "ADDISON AV",
        "species": "Celtis australis",
        "trim_cycle": "Large Tree Routine Prune",
        "dbh": 11,
        "inventory_date": "2010-10-18",
        "protected": false,
        "kml": "<Point><coordinates>-122.156485,37.440963</coordinates></Point>"
      }]
    }, {
      "url": "http://example.org/tree-ops-ext.csv#row=3",
      "rownum": 2,
      "describes": [{ 
        "@id": "http://example.org/tree-ops-ext#gid-2",
        "on_street": "EMERSON ST",
        "species": "Liquidambar styraciflua",
        "trim_cycle": "Large Tree Routine Prune",
        "dbh": 11,
        "inventory_date": "2010-06-02",
        "protected": false,
        "kml": "<Point><coordinates>-122.156749,37.440958</coordinates></Point>"
      }]
    }, {
      "url": "http://example.org/tree-ops-ext.csv#row=4",
      "rownum": 3,
      "describes": [{  
        "@id": "http://example.org/tree-ops-ext#gid-6",
        "on_street": "ADDISON AV",
        "species": "Robinia pseudoacacia",
        "trim_cycle": "Large Tree Routine Prune",
        "dbh": 29,
        "inventory_date": "2010-06-01",
        "comments": [ "cavity or decay", 
          "trunk decay", 
          "codominant leaders", 
          "included bark",
          "large leader or limb decay", 
          "previous failure root damage", 
          "root decay", 
          "beware of BEES" ],
        "protected": true,
        "kml": "<Point><coordinates>-122.156299,37.441151</coordinates></Point>"
      }]
    }]
  }]


}
Note

Dates, times and durations: date , time , datetime , Table T ( dateTime { "url": "http://example.org/tree-ops-ext.csv"} and ) has been explicitly identified: duration { "@id": "<http://exmple.org/tree-ops-ext>"} .

A standard syntax for dates and times is defined by [ iso8601 Non-core annotations ]. This format can be readily consumed by software applications. However, dates and times notes specified for table T ( { "url": "http://example.org/tree-ops-ext.csv"} ) are often provided included in a locale-specific format, or use alternate calendars and/or eras. the output.

Metadata property format MAY

6.3 Example with single table and using virtual columns be provided to describe the formatting produce multiple subjects per row

This example uses a single annotated table describing a listing of cell values music events. Each row from the tabular data file corresponds to three resources; the music event itself, the location where that event occurs and assist the mapping application offer to sell tickets for that event. The goal is to convert the cell value CSV content into schema.org to markup that a date, time, date-time or duration format readily consumable by downstream applications. search engine such as Google can use to index music events. Details of how Google expects this information to be structured can be found here .

The input tabular data file, published at http://example.org/events-listing.csv , and the associated metadata description http://example.org/events-listing.csv-metadata.json are provided below:

Example 9: http://example.org/events-listing.csv
Name, Start Date, Location Name, Location Address, Ticket Url

B.B. King,2014-04-12T19:30,"Lupo’s Heartbreak Hotel","79 Washington St., Providence, RI",https://www.etix.com/ticket/1771656
B.B.
King,2014-04-13T20:00,"Lynn
Auditorium","Lynn,
MA,
01901",http://frontgatetickets.com/venue.php?id=11766
Example 10: http://example.org/events-listing.csv-metadata.json
{
  "@context": ["http://www.w3.org/ns/csvw", {"@language": "en"}],
  "url": "events-listing.csv",
  "dialect": {"trim": true},
  "tableSchema": {
    "columns": [{
      "name": "name",
      "titles": "Name",
      "aboutUrl": "#event-{_row}",
      "propertyUrl": "schema:name"
    }, {
      "name": "start_date",
      "titles": "Start Date",
      "datatype": {
        "base": "datetime",
        "format": "yyyy-MM-ddTHH:mm"
      },
      "aboutUrl": "#event-{_row}",
      "propertyUrl": "schema:startDate"
    }, {
      "name": "location_name",
      "titles": "Location Name",
      "aboutUrl": "#place-{_row}",
      "propertyUrl": "schema:name"
    }, {
      "name": "location_address",
      "titles": "Location Address",
      "aboutUrl": "#place-{_row}",
      "propertyUrl": "schema:address"
    }, {
      "name": "ticket_url",
      "titles": "Ticket Url",
      "datatype": "anyURI",
      "aboutUrl": "#offer-{_row}",
      "propertyUrl": "schema:url"
    }, {
      "name": "type_event",
      "virtual": true,
      "aboutUrl": "#event-{_row}",
      "propertyUrl": "rdf:type",
      "valueUrl": "schema:MusicEvent"
    }, {
      "name": "type_place",
      "virtual": true,
      "aboutUrl": "#place-{_row}",
      "propertyUrl": "rdf:type",
      "valueUrl": "schema:Place"
    }, {
      "name": "type_offer",
      "virtual": true,
      "aboutUrl": "#offer-{_row}",
      "propertyUrl": "rdf:type",
      "valueUrl": "schema:Offer"
    }, {
      "name": "location",
      "virtual": true,
      "aboutUrl": "#event-{_row}",
      "propertyUrl": "schema:location",
      "valueUrl": "#place-{_row}"
    }, {
      "name": "offers",
      "virtual": true,
      "aboutUrl": "#event-{_row}",
      "propertyUrl": "schema:offers",
      "valueUrl": "#offer-{_row}"
    }]
  }

}
Note
Where possible,

The CSV to JSON translation is limited to providing one statement, or triple, per column in the table . The target schema.org markup requires 10 statements to describe each event. As the base tabular data publishers SHOULD file contains 5 columns, an additional 5 virtual columns have been added in order to provide dates for the full complement of statements—including the relationships between the 3 resources (event, location, and times in offer) described by each row of the [ iso8601 table . Note that the virtual annotation is true for these virtual columns ] format. However, where data publishers choose .

Furthermore, note that no attempt is made to use locale-specific date and time formatting, they SHOULD also provide equivalent values in [ iso8601 reconcile between locations or offers that may be associated with more than one event; every row ] format (e.g. in the table will create both a complementary column). new location resource and offer resource in addition to the event resource. If considered necessary, applications such as OpenRefine may be used to identify and reconcile duplicate location resources once the JSON output has been generated.

Issue 54

Describing The annotated table generated from parsing the formatting of dates tabular data file and times is currently unresolved. The favoured option associated metadata is to defer the parsing of dates shown below and times to implementations based a picture string provided in provides the metadata. Unfortunately, there is no standard syntax basis for picture strings, therefore an array of picture strings relating to common implementations seems like the best option. For example: conversion to JSON.

Annotations for the resulting table T , with 10 columns and 2 rows , are shown below:

id core annotations
url columns rows
T "datatype": "date", http://example.org/events-listing.csv C1 , C2 , C3 , C4 , C5 , C6 , C7 , C8 , C9 , C10 R1 , R2

Annotations for the columns , rows and cells in table T are shown in the tables below.

Column annotations:

id core annotations
table number source number cells name titles virtual
C1 T 1 1 C1.1 , C2.1 "format": { name   "picture-strings": [ Name
C2 T 2 2 C1.2 , C2.2     "unicode": "dd MMM yyyy", start_date     "xpath": "[D01] [MN,*-3] [Y0001]" Start Date
C3 T 3 3 C1.3 , C2.3   ] location_name } Location Name
C4 T 4 4 C1.4 , C2.4 location_address Location Address
C5 T 5 5 C1.5 , C2.5 ticket_url Ticket Url
C6 T 6 6 C1.6 , C2.6 type_event true
C7 T 7 7 C1.7 , C2.7 type_place true
C8 T 8 8 C1.8 , C2.8 type_offer true
C9 T 9 9 C1.9 , C2.9 location true
C10 T 10 10 C1.10 , C2.10 offers true

Row annotations:

id core annotations
table number source number cells
R1 T 1 2 C1.1 , C1.2 , C1.3 , C1.4 , C1.5 , C1.6 , C1.7 , C1.8 , C1.9 , C1.10
R2 T 2 3 C2.1 , C2.2 , C2.3 , C2.4 , C2.5 , C2.6 , C2.7 , C2.8 , C2.9 , C2.10

Where an implementation is able to interpret one of the provided picture strings, the date-time value reformatted in [ iso8601 Cell annotations:

] format shall be included in the output graph, else the original cell Issue 65
id core annotations
table column row string value shall be included verbatim. In the interim, mapping applications are not required to undertake any reformatting and may simply pass the cell value to the output graph verbatim. about URL property URL value URL
C1.1 T C1 R1 "B.B. King" "B.B. King" <http://example.org/events-listing.csv#event-1> schema:name
C1.2 T C2 R1 "2014-04-12T19:30" 2014-04-12T19:30:00 <http://example.org/events-listing.csv#event-1> schema:startDate
C1.3 T C3 R1 "Lupo’s Heartbreak Hotel" "Lupo’s Heartbreak Hotel" <http://example.org/events-listing.csv#place-1> schema:name
C1.4 T C4 R1 "79 Washington St., Providence, RI" "79 Washington St., Providence, RI" <http://example.org/events-listing.csv#place-1> schema:address
C1.5 T C5 R1 "https://www.etix.com/ticket/1771656" <https://www.etix.com/ticket/1771656> <http://example.org/events-listing.csv#offer-1> schema:url
C1.6 T C6 R1 "" null <http://example.org/events-listing.csv#event-1> rdf:type schema:MusicEvent
C1.7 T C7 R1 "" null <http://example.org/events-listing.csv#place-1> rdf:type schema:Place
C1.8 T C8 R1 "" null <http://example.org/events-listing.csv#offer-1> rdf:type schema:Offer
C1.9 T C9 R1 "" null <http://example.org/events-listing.csv#event-1> schema:location <http://example.org/events-listing.csv#place-1>
C1.10 T C10 R1 "" null <http://example.org/events-listing.csv#event-1> schema:offers <http://example.org/events-listing.csv#offer-1>
C2.1 T C1 R2 "B.B. King" "B.B. King" <http://example.org/events-listing.csv#event-2> schema:name
C2.2 T C2 R2 "2014-04-13T20:00" 2014-04-13T20:00:00 <http://example.org/events-listing.csv#event-2> schema:startDate
C2.3 T C3 R2 "Lynn Auditorium" "Lynn Auditorium" <http://example.org/events-listing.csv#place-2> schema:name
C2.4 T C4 R2 "Lynn, MA, 01901" "Lynn, MA, 01901" <http://example.org/events-listing.csv#place-2> schema:address
C2.5 T C5 R2 "http://frontgatetickets.com/venue.php?id=11766" <http://frontgatetickets.com/venue.php?id=11766> <http://example.org/events-listing.csv#offer-2> schema:url
C2.6 T C6 R2 "" null <http://example.org/events-listing.csv#event-2> rdf:type schema:MusicEvent
C2.7 T C7 R2 "" null <http://example.org/events-listing.csv#place-2> rdf:type schema:Place
C2.8 T C8 R2 "" null <http://example.org/events-listing.csv#offer-2> rdf:type schema:Offer
C2.9 T C9 R2 "" null <http://example.org/events-listing.csv#event-2> schema:location <http://example.org/events-listing.csv#place-2>
C2.10 T C10 R2 "" null <http://example.org/events-listing.csv#event-2> schema:offers <http://example.org/events-listing.csv#offer-2>

A list of potential date-time formatting implementations needs to be defined. Minimal mode output for this example is provided below:

Example 11: http://example.org/events-listing-minimal.json
[{
  "@id": "http://example.org/events-listing.csv#event-1",
  "@type": "schema:MusicEvent",
  "schema:name": "B.B. King",
  "schema:startDate": "2014-04-12T19:30:00",
  "schema:location": {
    "@id": "http://example.org/events-listing.csv#place-1",
    "@type": "schema:Place",
    "schema:name": "Lupo’s Heartbreak Hotel",
    "schema:address": "79 Washington St., Providence, RI"
  },
  "schema:offer": {
    "@id": "http://example.org/events-listing.csv#offer-1",
    "@type": "schema:Offer",
    "schema:offer": "https://www.etix.com/ticket/1771656"
  }
}, {
  "@id": "http://example.org/events-listing.csv#event-2",
  "@type": "schema:MusicEvent",
  "schema:name": "B.B. King",
  "schema:startDate": "2014-04-13T20:00:00",
  "schema:location": {
    "@id": "http://example.org/events-listing.csv#place-2",
    "@type": "schema:Place",
    "schema:name": "Lynn Auditorium",
    "schema:address": "Lynn, MA, 01901"
  },
  "schema:offer": {
    "@id": "http://example.org/events-listing.csv#offer-2",
    "@type": "schema:Offer",
    "schema:offer": "http://frontgatetickets.com/venue.php?id=11766"
  }


}]
Note
Where

Three resources are defined for each row within the metadata property table; event, location and offer. Therefore three objects are created for each row .

Each column description explicitly defines both separator aboutUrl is specified (e.g. to indicate that a cell value is to be parsed into a list of values), the datatype specified by and datatype propertyUrl SHALL be inferred to apply properties which are used to create the members of about URL and property URL annotations on the resulting list. column's cells .

Columns C6 , C7 and C8 ( urlTemplate { "name": "type_event"} , { "name": "type_place"} If metadata property and urlTemplate { "name": "type_offer"} is specified, ) define the value used in semantic types of the output graph SHALL be resources described by each row : schema:MusicEvent , schema:Place and schema:Offer respectively—noting that the result use of rdf:type is converted to the URI Template expansion, as defined in Section 3.1 Property Syntax name of @type (as used in [ tabular-metadata json-ld ]. ]) by this conversion application.

Once Column C9 ( { "name": "location"} ) uses the about URL has been generated via the template expansion, relative URLs are resolved against the base , property URL and value URL to create an absolute URL. assert the relationship between the event and location resources.

Column C10 ( default { "name": "offer"} ) uses the about URL , property URL and value URL to assert the relationship between the event and offer resources.

If metadata property default Standard mode output for this example is specified provided below:

Example 12: http://example.org/events-listing-standard.json
{
  "table": [{
    "url": "http://example.org/events-listing.csv",
    "row": [{
      "url": "http://example.org/events-listing.csv#row=2",
      "rownum": 1,
      "describes": [{ 
        "@id": "http://example.org/events-listing.csv#event-1",
        "@type": "schema:MusicEvent",
        "schema:name": "B.B. King",
        "schema:startDate": "2014-04-12T19:30:00",
        "schema:location": {
          "@id": "http://example.org/events-listing.csv#place-1",
          "@type": "schema:Place",
          "schema:name": "Lupo’s Heartbreak Hotel",
          "schema:address": "79 Washington St., Providence, RI"
        },
        "schema:offers": {
          "@id": "http://example.org/events-listing.csv#offer-1",
          "@type": "schema:Offer",
          "schema:url": "https://www.etix.com/ticket/1771656"
        }
      }]
    }, {
      "url": "http://example.org/events-listing.csv#row=3",
      "rownum": 2,
      "describes": [{ 
        "@id": "http://example.org/events-listing.csv#event-2",
        "@type": "schema:MusicEvent",
        "schema:name": "B.B. King",
        "schema:startDate": "2014-04-13T20:00:00",
        "schema:location": {
          "@id": "http://example.org/events-listing.csv#place-2",
          "@type": "schema:Place",
          "schema:name": "Lynn Auditorium",
          "schema:address": "Lynn, MA, 01901"
        },
        "schema:offers": {
          "@id": "http://example.org/events-listing.csv#offer-2",
          "@type": "schema:Offer",
          "schema:url": "http://frontgatetickets.com/venue.php?id=11766"
        }
      }]
    }]
  }]

}
Note

The resources described by each row are explicitly defined using the about URL annotation—in this case three resources per row (event, location, and offer). The objects containing the name-values pairs associated with the cell value values is deemed of a row are related to be null , then the value of default SHALL be used object for each subject in that row using the output graph . name-value pair with name describes .

4.2 6.4 Examples Example with table group comprising four interrelated tables

This example is based on Use Case #4 - Publication of public sector roles and salaries and uses four annotated tables published as a group of tables . Information about senior roles and junior roles within a government department or organization are published in CSV format by each department. These are validated against a centrally published schema to ensure that all the data published by departments is consistent. Additionally, lists of organizations and professions are also published centrally, providing controlled vocabularies against which departmental submissions are validated.

Information published about junior and senior roles provides summary information for each post within the government department or organization. Whilst the junior role information is anonymous, providing only an indication of the number of full-time-equivalent (FTE) staff occupying a given post, the senior role information specifies the named individual occupying each post. As such, each row from the tabular data file describing senior roles corresponds to two resources; the post and the person occupying that post.

This example is concerned only with converting the information provided each government department or organization not the centrally published information listing organizations and professions.

The input tabular data files and associated metadata descriptions are provided below:

Example 13: http://example.org/gov.uk/data/organizations.csv
Organization Unique Reference,Organization Name,Department Reference

hefce.ac.uk,Higher Education Funding Council for England,bis.gov.uk
bis.gov.uk,"Department
for
Business,
Innovation
and
Skills",xx
Example 14: http://example.org/gov.uk/data/professions.csv
Profession
Finance
Information Technology
Operational Delivery
Policy
Example 15: http://example.org/senior-roles.csv
Post Unique Reference,Name,Grade,Job Title,Reports to Senior Post,Profession,Organization Reference

90115,Steve Egan,SCS1A,Deputy Chief Executive,90334,Finance,hefce.ac.uk
90334,Sir
Alan
Langlands,SCS4,Chief
Executive,xx,Policy,hefce.ac.uk
Example 16: http://example.org/junior-roles.csv
Reporting Senior Post,Grade,Payscale Minimum (£),Payscale Maximum (£),Generic Job Title,Number of Posts (FTE),Profession,Organization Reference

90115,4,17426,20002,Administrator,8.67,Operational Delivery,hefce.ac.uk
90115,5,19546,22478,Administrator,0.5,Operational
Delivery,hefce.ac.uk
Example 17: http://example.org/metadata.json
{
  "@type": "TableGroup",
  "@context": ["http://www.w3.org/ns/csvw", {"@language": "en"}],
  "tables": [{
    "url": "gov.uk/data/organizations.csv",
    "tableSchema": "gov.uk/schemas/organizations.json",
    "suppressOutput": true
  }, {
    "url": "gov.uk/data/professions.csv",
    "tableSchema": "gov.uk/schemas/professions.json",
    "suppressOutput": true
  }, {
    "url": "senior-roles.csv",
    "tableSchema": "gov.uk/schemas/senior-roles.json"
  }, {
    "url": "junior-roles.csv",
    "tableSchema": "gov.uk/schemas/junior-roles.json"
  }]

}
Example 18: http://example.org/gov.uk/schema/organizations.json
{
  "@id": "http://example.org/gov.uk/schema/organizations.json",
  "@context": "http://www.w3.org/ns/csvw",
  "columns": [{
    "name": "ref",
    "titles": "Organization Unique Reference",
    "datatype": "string",
    "required": true,
    "propertyUrl": "dc:identifier"
  }, {
    "name": "name",
    "titles": "Organization Name",
    "datatype": "string",
    "propertyUrl": "foaf:name"
  }, {
    "name": "department",
    "titles": "Department Reference",
    "datatype": "string",
    "null": "xx",
    "propertyUrl": "org:subOrganizationOf",
    "valueUrl": "http://example.org/organization/{ref}"
  }],
  "primaryKey": "ref",
  "aboutUrl": "http://example.org/organization/{ref}",
  "foreignKeys": [{
    "columnReference": "department",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/organizations.json",
      "columnReference": "ref"
    }
  }]

}
Example 19: http://example.org/gov.uk/schema/professions.json
{
  "@id": "http://example.org/gov.uk/schema/professions.json",
  "@context": "http://www.w3.org/ns/csvw",
  "columns": [{
    "name": "name",
    "titles": "Profession",
    "datatype": "string",
    "required": true
  }],
  "primaryKey": "name"

}
Example 20: http://example.org/gov.uk/schema/senior-roles.json
{
  "@id": "http://example.org/gov.uk/schema/senior-roles.json",
  "@context": "http://www.w3.org/ns/csvw",
  "columns": [{
    "name": "ref",
    "titles": "Post Unique Reference",
    "datatype": "string",
    "required": true,
    "propertyUrl": "dc:identifier"
  }, {
    "name": "name",
    "titles": "Name",
    "datatype": "string",
    "aboutUrl": "http://example.org/organization/{organizationRef}/person/{_row}",
    "propertyUrl": "foaf:name"
  }, {
    "name": "grade",
    "titles": "Grade",
    "datatype": "string",
    "propertyUrl": "http://example.org/gov.uk/def/grade"
  }, {
    "name": "job",
    "titles": "Job Title",
    "datatype": "string",
    "propertyUrl": "http://example.org/gov.uk/def/job"
  }, {
    "name": "reportsTo",
    "titles": "Reports to Senior Post",
    "datatype": "string",
    "null": "xx",
    "propertyUrl": "org:reportsTo",
    "valueUrl": "http://example.org/organization/{organizationRef}/post/{reportsTo}"
  }, {
    "name": "profession",
    "titles": "Profession",
    "datatype": "string",
    "propertyUrl": "http://example.org/gov.uk/def/profession"
  }, {
    "name": "organizationRef",
    "titles": "Organization Reference",
    "datatype": "string",
    "propertyUrl": "org:postIn",
    "valueUrl": "http://example.org/organization/{organizationRef}",
    "required": true
  }, {
    "name": "post_holder",
    "virtual": true,
    "propertyUrl": "org:heldBy",
    "valueUrl": "http://example.org/organization/{organizationRef}/person/{_row}"
  }],
  "primaryKey": "ref",
  "aboutUrl": "http://example.org/organization/{organizationRef}/post/{ref}",
  "foreignKeys": [{
    "columnReference": "reportsTo",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/senior-roles.json",
      "columnReference": "ref"
    }
  }, {
    "columnReference": "profession",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/professions.json",
      "columnReference": "name"
    }
  }, {
    "columnReference": "organizationRef",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/organizations.json",
      "columnReference": "ref"
    }
  }]

}
Example 21: http://example.org/gov.uk/schema/junior-roles.json
{
  "@id": "http://example.org/gov.uk/schema/junior-roles.json",
  "@context": "http://www.w3.org/ns/csvw",
  "columns": [{
    "name": "reportsToSenior",
    "titles": "Reporting Senior Post",
    "datatype": "string",
    "propertyUrl": "org:reportsTo",
    "valueUrl": "http://example.org/organization/{organizationRef}/post/{reportsToSenior}",
    "required": true
  }, {
    "name": "grade",
    "titles": "Grade",
    "datatype": "string",
    "propertyUrl": "http://example.org/gov.uk/def/grade"
  }, {
    "name": "min_pay",
    "titles": "Payscale Minimum (£)",
    "datatype": "integer",
    "propertyUrl": "http://example.org/gov.uk/def/min_pay"
  }, {
    "name": "max_pay",
    "titles": "Payscale Maximum (£)",
    "datatype": "integer",
    "propertyUrl": "http://example.org/gov.uk/def/max_pay"
  }, {
    "name": "job",
    "titles": "Generic Job Title",
    "datatype": "string",
    "propertyUrl": "http://example.org/gov.uk/def/job"
  }, {
    "name": "number",
    "titles": "Number of Posts (FTE)",
    "datatype": "number",
    "propertyUrl": "http://example.org/gov.uk/def/number_of_posts" 
  }, {
    "name": "profession",
    "titles": "Profession",
    "datatype": "string",
    "propertyUrl": "http://example.org/gov.uk/def/profession"
  }, {
    "name": "organizationRef",
    "titles": "Organization Reference",
    "datatype": "string",
    "propertyUrl": "org:postIn",
    "valueUrl": "http://example.org/organization/{organizationRef}",
    "required": true
  }],
  "foreignKeys": [{
    "columnReference": "reportsToSenior",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/senior-roles.json",
      "columnReference": "ref"
    }
  }, {
    "columnReference": "profession",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/professions.json",
      "columns": "name"
    }
  }, {
    "columnReference": "organizationRef",
    "reference": {
      "schemaReference": "http://example.org/gov.uk/schema/organizations.json",
      "columns": "ref"
    }
  }]

}
Issue Note
These

This example makes extensive use of the example.org domain. As described in [ RFC6761 ], this domain is used for illustrative examples don't really show within documentation. In reality, the edge cases - probably need to rework them resources described here with the URL path /gov.uk would be centrally published by the UK Government at, say, the domain data.gov.uk .

The first example illustrates how a CSV file Given that these resources are centrally published with an aspiration for reuse, the schema descriptions have been factored out into separate resources. As such, the top-level metadata annotations drawn description resource metadata.json simply provides the list of tables and binds each of them to the appropriate schema that is defined elsewhere.

Finally, note that because the centrally published metadata descriptions are intended to be reused across many government departments and organizations, extra consideration has been given to defining URIs for the only person and post resources defined in each row of the senior roles tabular data and subsequently referenced from the junior roles tabular data. To ensure that naming clashes are avoided, the unique reference for the organization to which the person or post belongs has been included in a header line path segment of the identifier. For example, the URI template property aboutUrl used to identify the senior post is processed. specified as http://example.org/organization/{organizationRef}/post/{ref} , thus yielding the URI http://example.org/organization/hefce.ac.uk/post/90115 for the post described in the first row of the senior roles tabular data.

The group of tables generated from parsing the tabular data describes lists countries, giving their country code files and name. There are two columns, named country associated metadata is shown below and name , provides the basis for the conversion to JSON.

Annotations for the group of tables G and the four rows. tables Ta , Tb , Tc , and Td are shown below.

Group of Tables annotations:

id core annotations
tables
G Ta , Tb , Tc , Td

Table annotations:

id core annotations
country url name columns rows suppress output foreign keys
AD Ta Andorra http://example.org/gov.uk/data/organizations.csv Ca1 , Ca2 , Ca3 Ra1 , Ra2 true Fa1
AF Tb Afghanistan http://example.org/gov.uk/professions.csv Cb1 Rb1 , Rb2 , Rb3 , Rb4 true
AI Tc Anguilla http://example.org/senior-roles.csv Cc1 , Cc2 , Cc3 , Cc4 , Cc5 , Cc6 Rc1 , Rc2 false Fc1 , Fc2 , Fc3
AL Td Albania http://example.org/junior-roles.csv Cd1 , Cd2 , Cd3 , Cd4 , Cd5 , Cd6 , Cd7 Rd1 , Rd2 false Fd1 , Fd2 , Fd3
The CSV input (published at
Note

In this example, output for the centrally published lists of organizations and professions, tables Ta and Tb ( http://example.org/country-codes-and-names.csv http://example.org/gov.uk/data/organizations.csv ): and http://example.org/gov.uk/data/professions.csv respectively), are not required; only information from the departmental submissions is to be translated to RDF. Note the suppress output annotation on this table .

country,name AD,Andorra AF,Afghanistan AI,Anguilla AL,Albania

The resulting JSON output graph: following foreign keys are defined:

{ "distribution": { "downloadURL": "http://example.org/country-codes-and-names.csv" }, "row": [{ "country": "AD", "name": "Andorra" },{ "country": "AF", "name": "Afghanistan" },{ "country": "AI", "name": "Anguilla" },{ "country": "AL", "name": "Albania" }] }
id columns in table columns in referenced table
Fa1 Ca3 Ca1
Fc1 Cc5 Cc1
Fc2 Cc6 Cb1
Fc3 Cc7 Ca1
Fd1 Cd1 Cc1
Fd2 Cd7 Cb1
Fd3 Cd8 Ca1

The second example illustrates how the mapping is modified with Annotations for the addition of metadata annotations columns , rows and cells in table T are shown in a metadata document. The CSV file is a small extract from a much larger Tree Inventory dataset from the City tables below.

Column annotations:

id core annotations
table number source number cells name titles required virtual
Ca1 Ta 1 1 Ca1.1 , Ca2.1 ref Organization Unique Reference true
Ca2 Ta 1 1 Ca1.2 , Ca2.2 name Organization Name
Ca3 Ta 1 1 Ca1.3 , Ca2.3 department Department Reference
Cb1 Tb 1 1 Cb1.1 , Cb2.1 , Cb3.1 , Cb4.1 name Profession true
Cc1 Tc 1 1 Cc1.1 , Cc2.1 ref Post Unique Reference true
Cc2 Tc 2 2 Cc1.2 , Cc2.2 name Name
Cc3 Tc 3 3 Cc1.3 , Cc2.3 grade Grade
Cc4 Tc 4 4 Cc1.4 , Cc2.4 job Job Title
Cc5 Tc 5 5 Cc1.5 , Cc2.5 reportsTo Reports to Senior Post
Cc6 Tc 6 6 Cc1.6 , Cc2.6 profession Profession
Cc7 Tc 7 7 Cc1.7 , Cc2.7 organizationRef Organization Reference true
Cc8 Tc 8 8 Cc1.8 , Cc2.8 post_holder true
Cd1 Td 1 1 Cd1.1 , Cd2.1 reportsToSenior Reporting Senior Post true
Cd2 Td 2 2 Cd1.2 , Cd2.2 grade Grade
Cd3 Td 3 3 Cd1.3 , Cd2.3 min_pay Payscale Minimum (£)
Cd4 Td 4 4 Cd1.4 , Cd2.4 max_pay Payscale Maximum (£)
Cd5 Td 5 5 Cd1.5 , Cd2.5 job Generic Job Title
Cd6 Td 6 6 Cd1.6 , Cd2.6 number Number of Palo Alto which supports the maintaining and tracking the city's public trees and urban forest. There are five columns, named Posts (FTE)
Cd7 Td 7 7 Cd1.7 , Cd2.7 GID , profession On Street , Profession
Cd8 Td 8 8 Cd1.8 , Cd2.8 Species , organizationRef Trim Cycle Organization Reference and Inventory Date true
Note

Column Cc8 , with the virtual annotation specified as true , and three rows. is used to relate the person resource, whose name is provided in column Cc2 , to the associated post resource within the current row of table Tc ( { "url": "http://example.org/senior-roles.csv" } ).

Row annotations:

GID
id core annotations
On Street table Species number Trim Cycle source number Inventory Date cells
Ra1 Ta 1 ADDISON AV 2 Celtis australis Ca1.1 , Ca1.2 , Ca1.3
Large Tree Routine Prune Ra2 10/18/2010 Ta 2 3 Ca2.1 , Ca2.2 , Ca2.3
Rb1 Tb 1 2 EMERSON ST Cb1.1
Liquidambar styraciflua Rb2 Large Tree Routine Prune Tb 6/2/2010 2 3 Cb2.1
Rb3 Tb 3 EMERSON ST 4 Liquidambar styraciflua Cb3.1
Large Tree Routine Prune Rb4 6/2/2010 Tb 4 5 Cb4.1
Rc1 Tc 1 2 Cc1.1 , Cc1.2 , Cc1.3 , Cc1.4 , Cc1.5 , Cc1.6 , Cc1.7 , Cc1.8
Rc2 Tc 2 3 Cc2.1 , Cc2.2 , Cc2.3 , Cc2.4 , Cc2.5 , Cc2.6 , Cc2.7 , Cc2.8
Rd1 Td 1 2 Cd1.1 , Cd1.2 , Cd1.3 , Cd1.4 , Cd1.5 , Cd1.6 , Cd1.7 , Cd1.8
Rd2 Td 2 3 Cd2.1 , Cd2.2 , Cd2.3 , Cd2.4 , Cd2.5 , Cd2.6 , Cd2.7 , Cd2.8

The CSV input (published at Cell annotations:

The procedures
id core annotations
table column row string value value about URL property URL value URL
Ca1.1 Ta Ca1 Ra1 http://example.org/tree-ops.csv "hefce.ac.uk" ): GID,On Street,Species,Trim Cycle,Inventory Date 1,ADDISON AV,Celtis australis,Large Tree Routine Prune,10/18/2010 2,EMERSON ST,Liquidambar styraciflua,Large Tree Routine Prune,6/2/2010 3,EMERSON ST,Liquidambar styraciflua,Large Tree Routine Prune,6/2/2010 The metadata description (published at http://example.org/tree-ops.csv-metadata.json "hefce.ac.uk" ): { "@id": "tree-ops", "@context": { "@language": "en" } "dcat:distribution": { "dcat:downloadURL": "tree-ops.csv" } "dc:title": "Tree Operations", "dc:keywords": ["tree", "street", "maintenance"], "dc:publisher": [{ "schema:name": "Example Municipality", "schema:web": "http://example.org" }], "dc:license": "http://opendefinition.org/licenses/cc-by/", "dc:modified": "2010-12-31", "schema": { "columns": [{ "name": "GID", "title": [ "GID", "Generic Identifier" ], "dc:description": "An identifier for the operation on a tree.", "datatype": "string", "required": true, "unique": true }, { "name": "on-street", "title": "On Street", "dc:description": "The street that the tree is on.", "datatype": "string" }, { "name": "species", "title": "Species", "dc:description": "The species of the tree.", "datatype": "string" }, { "name": "trim-cycle", "title": "Trim Cycle", "dc:description": "The operation performed on the tree.", "datatype": "string" }, { "name": "inventory-date", "title": "Inventory Date", "dc:description": "The date of the operation that was performed.", "datatype": "date" }] "primaryKey": "GID", "urlTemplate": "#gid-{GID}" } } The resulting JSON output graph: { "url": "tree-ops" "distribution": { "downloadURL": "http://example.org/tree-ops.csv" }, "dc:title": "Tree Operations", "dc:keywords": ["tree", "street", "maintenance"], "dc:publisher": [{ "schema:name": "Example Municipality", "schema:web": "http://example.org" }], "dc:license": "http://opendefinition.org/licenses/cc-by/", "dc:modified": "2010-12-31", "row": [{ "url": "http://example.org/tree-ops.csv#gid-1", "GID": "1", "on-street": "ADDISON AV", "species": "Celtis australis", "trim-cycle": "Large Tree Routine Prune", "inventory-date": "10/18/2010" },{ "url": "http://example.org/tree-ops.csv#gid-2", "GID": "2", "on-street": "EMERSON ST", "species": "Liquidambar styraciflua", "trim-cycle": "Large Tree Routine Prune", "inventory-date": "6/2/2010" },{ "url": "http://example.org/tree-ops.csv#gid-3", "GID": "3", "on-street": "EMERSON ST", "species": "Liquidambar styraciflua", "trim-cycle": "Large Tree Routine Prune", "inventory-date": "6/2/2010" }], "describedBy": "http://example.org/tree-ops.csv-metadata.json" } <http://example.org/organization/hefce.ac.uk> 5. Mapping Grouped Tabular Data dc:identifier
Ca1.2 Ta Ca2 Ra1 "Higher Education Funding Council for England" "Higher Education Funding Council for England" <http://example.org/organization/hefce.ac.uk> foaf:name
Ca1.3 Ta Ca3 Ra1 "bis.gov.uk" "bis.gov.uk" <http://example.org/organization/hefce.ac.uk> org:subOrganizationOf <http://example.org/organization/bis.gov.uk>
Ca2.1 Ta Ca1 Ra2 "bis.gov.uk" "bis.gov.uk" <http://example.org/organization/bis.gov.uk> dc:identifier
Ca2.2 Ta Ca2 Ra2 "Department for Business, Innovation and rules Skills" "Department for mapping a collection of tabular data compliant with the grouped tabular data model Business, Innovation and Skills" <http://example.org/organization/bis.gov.uk> foaf:name
Ca2.3 Ta Ca3 Ra2 "xx" null <http://example.org/organization/bis.gov.uk> org:subOrganizationOf
Cb1.1 Tb Cb1 Rb1 "Finance" "Finance"
Cb2.1 Tb Cb1 Rb2 "Information Technology" "Information Techology"
Cb3.1 Tb Cb1 Rb3 "Operational Delivery" "Operational Delivery"
Cb4.1 Tb Cb1 Rb4 "Policy" "Policy"
Cc1.1 Tc Cc1 Rc1 "90115" "90115" <http://example.org/organization/hefce.ac.uk/post/90115> dc:identifier
Cc1.2 Tc Cc2 Rc1 "Steve Egan" "Steve Egan" <http://example.org/organization/hefce.ac.uk/person/1> foaf:name
Cc1.3 Tc Cc3 Rc1 "SCS1A" "SCS1A" <http://example.org/organization/hefce.ac.uk/post/90115> <http://example.org/gov.uk/def/grade>
Cc1.4 Tc Cc4 Rc1 "Deputy Chief Executive" "Deputy Chief Executive" <http://example.org/organization/hefce.ac.uk/post/90115> <http://example.org/gov.uk/def/job>
Cc1.5 Tc Cc5 Rc1 "90334" "90334" <http://example.org/organization/hefce.ac.uk/post/90115> org:reportsTo <http://example.org/organization/hefce.ac.uk/post/90334>
Cc1.6 Tc Cc6 Rc1 "Finance" "Finance" <http://example.org/organization/hefce.ac.uk/post/90115> <http://example.org/gov.uk/def/profession>
Cc1.7 Tc Cc7 Rc1 "hefce.ac.uk" "hefce.ac.uk" <http://example.org/organization/hefce.ac.uk/post/90115> org:postIn <http://example.org/organization/hefce.ac.uk>
Cc1.8 Tc Cc8 Rc1 "" null <http://example.org/organization/hefce.ac.uk/post/90115> org:heldBy <http://example.org/organization/hefce.ac.uk/person/1>
Cc2.1 Tc Cc1 Rc2 "90334" "90334" <http://example.org/organization/hefce.ac.uk/post/90334> dc:identifier
Cc2.2 Tc Cc2 Rc2 "Sir Alan Langlands" "Sir Alan Langlands" <http://example.org/organization/hefce.ac.uk/person/2> foaf:name
Cc2.3 Tc Cc3 Rc2 "SCS4" "SCS4" <http://example.org/organization/hefce.ac.uk/post/90334> <http://example.org/gov.uk/def/grade>
Cc2.4 Tc Cc4 Rc2 "Chief Executive" "Chief Executive" <http://example.org/organization/hefce.ac.uk/post/90334> <http://example.org/gov.uk/def/job>
Cc2.5 Tc Cc5 Rc2 "xx" null <http://example.org/organization/hefce.ac.uk/post/90334> org:reportsTo
Cc2.6 Tc Cc6 Rc2 "Policy" "Policy" <http://example.org/organization/hefce.ac.uk/post/90334> <http://example.org/gov.uk/def/profession>
Cc2.7 Tc Cc7 Rc2 "hefce.ac.uk" "hefce.ac.uk" <http://example.org/organization/hefce.ac.uk/post/90334> org:postIn <http://example.org/organization/hefce.ac.uk>
Cc2.8 Tc Cc8 Rc2 "" null <http://example.org/organization/hefce.ac.uk/post/90334> org:heldBy <http://example.org/organization/hefce.ac.uk/person/2>
Cd1.1 Td Cd1 Rd1 "90115" "90115" org:reportsTo <http://example.org/organization/hefce.ac.uk/post/90115>
Cd1.2 Td Cd2 Rd1 "4" "4" <http://example.org/gov.uk/def/grade>
Cd1.3 Td Cd3 Rd1 "17426" 17426 <http://example.org/gov.uk/def/min_pay>
Cd1.4 Td Cd4 Rd1 "20002" 20002 <http://example.org/gov.uk/def/max_pay>
Cd1.5 Td Cd5 Rd1 "Administrator" "Administrator" <http://example.org/gov.uk/def/job>
Cd1.6 Td Cd6 Rd1 "8.67" 8.67 <http://example.org/gov.uk/def/number_of_posts>
Cd1.7 Td Cd7 Rd1 "Operational Delivery" "Operational Delivery" <http://example.org/gov.uk/def/profession>
Cd1.8 Td Cd8 Rd1 "hefce.ac.uk" "hefce.ac.uk" org:postIn <http://example.org/organization/hefce.ac.uk>
Cd2.1 Td Cd1 Rd2 "90115" "90115" org:reportsTo <http://example.org/organization/hefce.ac.uk/post/90115>
Cd2.2 Td Cd2 Rd2 "5" "5" <http://example.org/gov.uk/def/grade>
Cd2.3 Td Cd3 Rd2 "19546" 19546 <http://example.org/gov.uk/def/min_pay>
Cd2.4 Td Cd4 Rd2 "22478" 22478 <http://example.org/gov.uk/def/max_pay>
Cd2.5 Td Cd5 Rd2 "Administrator" "Administrator" <http://example.org/gov.uk/def/job>
Cd2.6 Td Cd6 Rd2 "0.5" 0.5 <http://example.org/gov.uk/def/number_of_posts>
Cd2.7 Td Cd7 Rd2 "Operational Delivery" "Operational Delivery" <http://example.org/gov.uk/def/profession>
Cd2.8 Td Cd8 Rd2 "hefce.ac.uk" "hefce.ac.uk" org:postIn <http://example.org/organization/hefce.ac.uk>
Note

Notice that value URL are described below. The metadata is not specified for a group of tables SHALL be provided by a table group description cells (as defined Ca2.3 and Cc2.5 because in [ tabular-metadata each case the cell value ]) within is null and the associated metadata document. virtual annotation of column Cb5 is not defined.

5.1 Minimal mode output for this example is provided below:

Example 22: http://example.org/public-sector-roles-and-salaries-minimal.json
[{
  "@id": "http://example.org/organization/hefce.ac.uk/post/90115",
  "dc:identifier": "90115",
  "org:heldBy": {
    "@id": "http://example.org/organization/hefce.ac.uk/person/1",
    "foaf:name": "Steve Egan"
  },
  "http://example.org/gov.uk/def/grade": "SCS1A",
  "http://example.org/gov.uk/def/job": "Deputy Chief Executive",
  "org:reportsTo": "http://example.org/organization/hefce.ac.uk/post/90334",
  "http://example.org/gov.uk/def/profession": "Finance",
  "org:postIn": "http://example.org/organization/hefce.ac.uk"
}, {
  "@id": "http://example.org/organization/hefce.ac.uk/post/90334",
  "dc:identifier": "90334",
  "org:heldBy": {
    "@id": "http://example.org/organization/hefce.ac.uk/person/2",
    "foaf:name": "Sir Alan Langlands"
  },
  "http://example.org/gov.uk/def/grade": "SCS4",
  "http://example.org/gov.uk/def/job": "Chief Executive",
  "http://example.org/gov.uk/def/profession": "Policy",
  "org:postIn": "http://example.org/organization/hefce.ac.uk"
}, {
  "org:reportsTo": "http://example.org/organization/hefce.ac.uk/post/90115",
  "http://example.org/gov.uk/def/grade": "4",
  "http://example.org/gov.uk/def/min_pay": 17426,
  "http://example.org/gov.uk/def/max_pay": 20002,
  "http://example.org/gov.uk/def/job": "Administrator",
  "http://example.org/gov.uk/def/number_of_posts": 8.67,
  "http://example.org/gov.uk/def/profession": "Operational Delivery",
  "org:postIn": "http://example.org/organization/hefce.ac.uk"
}, {
  "org:reportsTo": "http://example.org/organization/hefce.ac.uk/post/90115",
  "http://example.org/gov.uk/def/grade": "5",
  "http://example.org/gov.uk/def/min_pay": 19546,
  "http://example.org/gov.uk/def/max_pay": 22478,
  "http://example.org/gov.uk/def/job": "Administrator",
  "http://example.org/gov.uk/def/number_of_posts": 0.5,
  "http://example.org/gov.uk/def/profession": "Operational Delivery",
  "org:postIn": "http://example.org/organization/hefce.ac.uk"

Generating
JSON


}]
5.1.1 Group-level processing
Note The root object of the output graph SHALL describe the table group .

Where present in the table group description , any Common Properties (as Prefixes defined in Section 3.3 Common Properties within the RDFa 1.1 Initial Context of [ ([ tabular-metadata rdfa-core ]) SHALL be are not expanded; e.g. dc: for <http://purl.org/dc/terms/>.

Output for tables Ta and Tb ( { "url": "http://example.org/gov.uk/data/organizations.csv" } and { "url": "http://example.org/gov.uk/data/professions.csv" } ) are not included in as the suppress output graph within annotation has the root object. The root object SHALL contain an array named value table true containing one object for each of the tables listed in the resources array of the table group description .

Each table The property URL SHALL be processed sequentially according to the appropriate set of rules is specified for mapping core or annotated tabular data . Refer to Section 3 Mapping Core Tabular Data all cells and Section 4 Mapping Annotated Tabular Data in tables for further details. Tc and Td .

The JSON generated from processing Columns Cc5 and Cd1 ( { "name": "reportsTo" } and { "name": "reportsToSenior" } ) use the tables about URL , property URL SHALL be incorporated into and value URL annotations to assert the output graph relationship between the given post and the senior post it reports to for the cells as therein. However, since senior posts and junior posts are described in different tables it is not possible to create nested objects within the table array. for this particular case.

Any of the inherited properties Similarly, columns Cc7 and Cd8 (both with null , separator , format , datatype , or default { "name": "organizationRef" } defined within ) use the table group description about URL , property URL SHALL be used and value URL annotations to pre-populate assert the column description objects relationship between the given post and the organization to which it belongs for the cells those columns .

Finally, note that two resources are created for each row within table in Tc ( { "url": "http://example.org/senior-roles.csv" } ): the group. Where person and the same property post they occupy. The relationship between these resources is defined in specified via virtual column Cc8 ( { "name": "post_holder" } ) using the table group description , table description about URL , schema property URL or column description and value URL annotations. The person object provides the order value of precedence SHALL the name-value pair with corresponding name org:heldBy , thus nesting the person be: object within the post object .

column description schema description table description table group description

Issue Standard mode output for this example is provided below:

Example 23: http://example.org/public-sector-roles-and-salaries-standard.json
{
  "table": [{
    "url": "http://example.org/senior-roles.csv",
    "row": [{
      "url": "http://example.org/senior-roles.csv#row=2",
      "rownum": 1,
      "describes": [{ 
        "@id": "http://example.org/organization/hefce.ac.uk/post/90115",
        "dc:identifier": "90115",
        "org:heldBy": {
          "@id": "http://example.org/organization/hefce.ac.uk/person/1",
          "foaf:name": "Steve Egan"
        },
        "http://example.org/gov.uk/def/grade": "SCS1A",
        "http://example.org/gov.uk/def/job": "Deputy Chief Executive",
        "org:reportsTo": "http://example.org/organization/hefce.ac.uk/post/90334",
        "http://example.org/gov.uk/def/profession": "Finance",
        "org:postIn": "http://example.org/organization/hefce.ac.uk"
      }]
    }, {
      "url": "http://example.org/senior-roles.csv#row=3",
      "rownum": 2,
      "describes": [{ 
        "@id": "http://example.org/organization/hefce.ac.uk/post/90334",
        "dc:identifier": "90334",
        "org:heldBy": {
          "@id": "http://example.org/organization/hefce.ac.uk/person/2",
          "foaf:name": "Sir Alan Langlands"
        },
        "http://example.org/gov.uk/def/grade": "SCS4",
        "http://example.org/gov.uk/def/job": "Chief Executive",
        "http://example.org/gov.uk/def/profession": "Policy",
        "org:postIn": "http://example.org/organization/hefce.ac.uk"
      }]
    }]
  }, {
    "url": "http://example.org/junior-roles.csv",
    "row": [{
      "url": "http://example.org/junior-roles.csv#row=2",
      "rownum": 1,
      "describes": [{ 
        "org:reportsTo": "http://example.org/organization/hefce.ac.uk/post/90115",
        "http://example.org/gov.uk/def/grade": "4",
        "http://example.org/gov.uk/def/min_pay": 17426,
        "http://example.org/gov.uk/def/max_pay": 20002,
        "http://example.org/gov.uk/def/job": "Administrator",
        "http://example.org/gov.uk/def/number_of_posts": 8.67,
        "http://example.org/gov.uk/def/profession": "Operational Delivery",
        "org:postIn": "http://example.org/organization/hefce.ac.uk"
      }]
    }, {
      "url": "http://example.org/junior-roles.csv#row=3",
      "rownum": 2,
      "describes": [{ 
        "org:reportsTo": "http://example.org/organization/hefce.ac.uk/post/90115",
        "http://example.org/gov.uk/def/grade": "5",
        "http://example.org/gov.uk/def/min_pay": 19546,
        "http://example.org/gov.uk/def/max_pay": 22478,
        "http://example.org/gov.uk/def/job": "Administrator",
        "http://example.org/gov.uk/def/number_of_posts": 0.5,
        "http://example.org/gov.uk/def/profession": "Operational Delivery",
        "org:postIn": "http://example.org/organization/hefce.ac.uk"
      }]
    }]
  }]

}

The presence of foreign-key references within A. Acknowledgements

At the table descriptions may affect time of publication, the way following individuals had participated in the data is packaged Working Group, in the output graph. Reviewers are invited to comment on how grouped tabular data with foreign-key references might best be organised. order of their first name: Adam Retter, Alf Eaton, Anastasia Dimou, Andy Seaborne, Axel Polleres, Christopher Gutteridge, Dan Brickley, Davide Ceolin, Eric Stephan, Erik Mannens, Gregg Kellogg, Ivan Herman, Jeni Tennison, Jeremy Tandy, Jürgen Umbrich, Rufus Pollock, Stasinos Konstantopoulos, William Ingram, and Yakov Shafranovich.

5.2 B. Examples Changes since the first public working draft of 08 January 2015 Use Case 4: Publication of

The document has undergone substantial changes since the first public sector roles working draft . Below are some of the changes made:

A. C. References

A.1 C.1 Normative references

[RFC2119]
S. Bradner. Key words for use in RFCs to Indicate Requirement Levels . March 1997. Best Current Practice. URL: https://tools.ietf.org/html/rfc2119
[iso8601]
[RFC7159]
T. Bray, Ed.. ISO 8601:2004 Representation of dates and times . International Standard (IS). The JavaScript Object Notation (JSON) Data Interchange Format . March 2014. Proposed Standard. URL: https://tools.ietf.org/html/rfc7159
[json]
[csv2rdf]
D. Crockford. Jeremy Tandy; Ivan Herman; Gregg Kellogg. The application/json Media Type for JavaScript Object Notation (JSON) Generating RDF from Tabular Data on the Web . Informational RFC. W3C Working Draft. URL: http://www.ietf.org/rfc/rfc4627.txt http://www.w3.org/TR/2015/WD-csv2rdf-20150416/
[rdf11-concepts]
Richard Cyganiak; David Wood; Markus Lanthaler. RDF 1.1 Concepts and Abstract Syntax . 25 February 2014. W3C Recommendation. URL: http://www.w3.org/TR/rdf11-concepts/
[tabular-data-model]
Jeni Tennison; Gregg Kellogg. Model for Tabular Data and Metadata on the Web . W3C Working Draft. URL: http://www.w3.org/TR/tabular-data-model/ http://www.w3.org/TR/2015/WD-tabular-data-model-20150416/
[tabular-metadata]
Rufus Pollock; Jeni Tennison. Tennison; Gregg Kellogg. Metadata Vocabulary for Tabular Data . W3C Working Draft. URL: http://www.w3.org/TR/tabular-metadata/ [uri-template] Joe Gregorio; Roy T. Fielding; Marc Hadley; Mark Nottingham; David Orchard. URI Template . March 2012. RFC 6570. URL: http://www.rfc-editor.org/rfc/rfc6570.txt http://www.w3.org/TR/2015/WD-tabular-metadata-20150416/

A.2 C.2 Informative references

[json-ld]
[Knuth]
Manu Sporny; Gregg Kellogg; Markus Lanthaler. JSON-LD 1.0 The Art of Computer Programming Volume 1: Fundamental Algorithms (3rd ed.) .
[RFC6761]
S. Cheshire; M. Krochmal. Special-Use Domain Names . February 2013. Proposed Standard. URL: https://tools.ietf.org/html/rfc6761
[RFC7111]
M. Hausenblas; E. Wilde; J. Tennison. URI Fragment Identifiers for the text/csv Media Type . 16 January 2014. W3C Recommendation. Informational. URL: http://www.w3.org/TR/json-ld/ https://tools.ietf.org/html/rfc7111
[json-ld-api]
[json-ld]
Markus Lanthaler; Manu Sporny; Gregg Kellogg; Manu Sporny. Markus Lanthaler. JSON-LD 1.0 Processing Algorithms and API . 16 January 2014. W3C Recommendation. URL: http://www.w3.org/TR/json-ld-api/ http://www.w3.org/TR/json-ld/
[vocab-dcat]
[rdfa-core]
Fadi Maali; John Erickson. Ben Adida; Mark Birbeck; Shane McCarron; Ivan Herman et al. Data Catalog Vocabulary (DCAT) RDFa Core 1.1 - Third Edition . 16 January 2014. 17 March 2015. W3C Recommendation. URL: http://www.w3.org/TR/vocab-dcat/ http://www.w3.org/TR/rdfa-core/