What will I talk about?
- The history of the Semantic Web goes back to several years now
- It is worth looking at what has been achieved, where we are, and where we might be going…
Let us look at some results first!
The basics: RDF(S)
- We have a solid specification since 2004: well defined (formal) semantics, clear RDF/XML syntax
Lots of tools are available. Are listed on W3C’s wiki:
- RDF programming environment for 14+ languages, including C, C++, Python, Java,
- 13+ Triple Stores, ie, database systems to store (sometimes huge!) datasets
- converters to and from RDF
- Some of the tools are Open Source, some are not; some are very mature, some
it is the usual picture of software tools, nothing special any more!
Anybody can start developing RDF-based applications today
The basics: RDF(S) (cont.)
- There are lots of tutorials, overviews, and books around
- Active developers’ communities
- Large datasets are accumulating
- Some mesaures claim that there are over 107 Semantic Web documents… (ready to be integrated…)
- This is also a stable specification since 2004
- Separate layers have been defined, balancing expressibility vs. implementability (OWL-Lite, OWL-DL, OWL-Full)
- Looking at the tool list on W3C’s wiki again:
- a number programming environments (in Java, Prolog, …) include OWL reasoners
- there are also stand-alone reasoners (downloadable or on the Web)
- ontology editors come to the fore
- OWL-DL and OWL-Lite relies on Description Logic, ie, can use a large body of accumulated research knowledge
- Large ontologies are being developed (converted from other formats or defined in OWL)
- eClassOwl: eBusiness
ontology for products and services, 75,000 classes and 5,500
the Gene Ontology: to
describe gene and gene product attributes in any organism
BioPAX, for biological pathway data
sequence and annotation terminology and data
- There are also a number “core vocabularies” (not necessarily OWL based)
- SKOS Core:
about knowledge systems, thesauri, glossaries
Dublin Core: about
information resources, digital libraries, with extensions for rights,
permissions, digital right management
FOAF: about people and
DOAP: on the descriptions
of software projects
Music Ontology: on
the description of CDs, music tracks, …
SIOC: Semantically-Interlinked Online Communities
vCard in RDF
- One should never forget: ontologies/vocabularies must be shared and reused!
Querying RDF: SPARQL
- Querying RDF graphs becomes essential
- SPARQL is almost here
- query language based on graph patterns
- there is also a protocol layer to use SPARQL over, eg, HTTP
- hopefully a Recommendation end 2007
- There are a number of implementations already
- There are also SPARQL “endpoints” on the Web:
- send a query and a reference to data over HTTP GET, receive the result in XML or JSON
applications may not need any direct RDF programming any more, just a SPARQL endpoint
- SPARQL can also be used to construct graphs!
Of course, not everything is so rosy…
- There are a number of issues, problems
- how to get RDF data
- missing functionalities: rules, “light” ontologies, fuzzy reasoning, necessity to review RDF and OWL,…
- misconceptions, messaging problems
- need for more applications, deployment, acceptance
How to get RDF data?
- Of course, one could create RDF data manually…
- … but that is unrealistic on a large scale
- Goal is to generate RDF data automatically when possible and “fill in” by hand only when necessary
Data may be around already…
- Part of the (meta)data information is present in tools … but thrown away at output
- e.g., a business chart can be generated by a tool: it “knows” the structure, the
classification, etc. of the chart, but, usually, this information is lost
- storing it in web data would be easy!
- “SW-aware” tools are around (even if you do not know it…), though more would be good:
- Photoshop CS stores metadata in RDF in, say, jpg files (using
RSS1.0 feeds are
generated by (almost) all blogging systems (a huge amount of RDF data!)
Data may be extracted (a.k.a. “scraped”)
- Different tools, services, etc, come around every day:
- get RDF data associated with images, for example:
- XSLT scripts to retrieve microformat data from XHTML files
- scripts to convert spreadsheets to RDF
- Most of these tools are still individual “hacks”, but show a general tendency
- W3C’s new GRDDL technology is a formal way of doing this for XML/XHTML
Linking to SQL
- A huge amount of data in Relational Databases
- Although tools exist, it is not feasible to convert that data into RDF
- Instead: SQL ⇋ RDF “bridges” are being developed:
- a query to RDF data is transformed into SQL on-the-fly
- the modalities are governed by small, local ontologies or rules
- An active area of development, on the radar screen of W3C!
- There are a number of projects “harvesting” and linking data to RDF (e.g., “Linking Open Data on the Semantic Web” community project)
SPARQL as a unifying point?
Missing features, functionalities…
- Everybody has a favorite item, ie, the list tends to infinite…
- W3C is a standardization body, and has to look at where a consensus can be found
- OWL-DL and OWL-Lite are based on Description Logic; there are things that DL cannot express
- a well known examples is Horn rules:
- there are a number of attempts to combine these: RuleML,
- There is also an increasing number of rule-based system that want to interchange rules
- a new type of data (potentially) on the Web to be interchanged…
- Some typical use cases
- Negotiate eBusiness contracts across platforms: supply vendor-neutral representation of your business rules so that others may find you
- Describe privacy requirements and policies, and let clients “merge” those (e.g., when paying with a credit card)
- Medical decision support, combining rules on diagnoses, drug prescription conditions, etc,
- Extend RDFS (or OWL) with rule-based statements (e.g., the uncle example)
- The “Rule Interchange Format” Working Group is working on this problem as we speak…
- For a number of applications RDFS is not enough, but even OWL Lite is too much
- There may be a need for a “light” version of OWL, just a few extra possibilities v.a.v. RDFS
- There are a number of proposals, papers, prototypes around: EL++, RDFS++, OWL Feather, pD*, DL Lite,…
- This might consolidate in the coming years
New versions of RDF and OWL?
- Such specifications have their own life
- Missing features come up, errors show up
- There may be a next version at some point
- but: it is always a difficult decision; introducing a new version creates uncertainty in the developers’ community
- Revision of the RDF model (eg, no restriction on predicates and literals)
- Revision of OWL (you may have heard of OWL1.1…)
- Fuzzy logic
- look at alternatives of Description Logic based on fuzzy logic
- alternatively, extend RDF(S) with fuzzy notions
- Probabilistic statements
- Security, trust, provenance
- combining cryptographic techniques with the RDF model, sign a portion of the graph, etc
- Ontology merging, alignment, term equivalences, versioning, development, …
A major problem: messaging
- Some of the messaging on Semantic Web has
gone terribly wrong . See these statements:
- “the Semantic Web is a reincarnation of Artificial Intelligence on the Web”
- “it relies on giant, centrally controlled ontologies for "meaning" (as opposed to
a democratic, bottom–up control of terms)”
- “one has to add metadata to all Web pages, convert all relational databases, and XML data to
use the Semantic Web”
- “it is just an ugly application of XML”
- “one has to learn formal logic, knowledge representation techniques, description logic, etc,
to use it”
- “it is, essentially, an academic project, of no interest for industry”
- Some simple messages should come to the fore!
RDF ≠ RDF/XML!
RDF is a model, and RDF/XML is only one possible serialization thereof
- lots of people prefer, for example, Turtle
- a good percentage of the tools have Turtle parsers, too!
- The model is, after all, simple: interchange format for Web resources.
That is it !
RDF is not that complex…
- Of course, the formal semantics of RDF is complex
- But the average user should not care, it is all “under the hood”
- how many users of SQL have ever read its formal semantics?
- it is not much simpler than RDF…
People should “think” in terms of graphs, the rest is syntactic sugar!
Semantic Web ≠ Ontologies on the Web!
- Formal ontologies (like OWL) are important, but use them only when necessary
- you can be a perfectly decent citizen of the Semantic Web if you do not use Ontologies, not even RDFS…
- remember the “light ontologies” issue?
SW Ontologies ≠ some central, big ontology!
- The “ethos” of the Semantic Web is on sharing, ie, sharing ontologies (small or large)
- A huge, central ontology would be unmanageable
- OWL includes statements for versioning, for equivalence and disjointness of terms
- a revision of those may be necessary, but the goal is clear
- The practice:
- SW applications using ontologies always mix large number of ontologies and vocabularies (FOAF, DC, and others)
- the real advantage comes from this mix: that is also how new relationships may be discovered
Semantic Web ≠ an academic research only!
- SW has indeed a strong foundation in research results
- But remember:
- (1) the Web was born at CERN…
- (2) …was first picked up by high energy physicists…
- (3) …then by academia at large…
- (4) …then by small businesses and start-ups…
- (5) “big business” came only later!
- network effect kicked in early…
- Semantic Web is now at #4, and moving to #5!
Some Semantic Web deployment communities
- The technology is picked up by specialized communities
- just like the high energy physics community did for the original Web…
- Some examples: digital libraries, defence, eGovernment, energy sector, financial services, health care, life sciences…
- Health care and life science sector is now very active
- also at W3C, in the form of an Interest Group
The “corporate” landscape is moving
- Major companies offer (or will offer) Semantic Web tools or systems using Semantic
Web: Adobe, Oracle, IBM, HP, Software AG, webMethods, Northrop Gruman, Altova,…
- Some of the names of active participants in W3C SW related groups: ILOG, HP, Agfa, SRI International, Fair Isaac Corp., Oracle, Boeing, IBM, Chevron, Siemens, Nokia, Merck, Pfizer, AstraZeneca, Sun,…
- “Corporate Semantic Web” listed as major technology by
Gartner in 2006
- Data integration comes to the fore as one of the SW Application areas
- Very important for large application areas (life sciences, energy sector, eGovernment, financial institutions),
as well as everyday applications (eg, reconciliation of calendar data)
- Life sciences example:
- data in different labs…
- data aimed at scientists, managers, clinical trial participants…
- large scale public ontologies (genes, proteins, antibodies, …)
- different formats (databases, spreadsheets, XML data, XHTML pages)
- Map the various data onto RDF
- assign URI-s to your data
- “mapping” may mean on-the-fly SPARQL to SQL conversion, “scraping”, etc
- Merge the resulting RDF graphs (with a possible help of ontologies, rules, etc, to combine the terms)
- Start making queries on the whole!
Remember the role of SPARQL?
A number of projects in the area
Example: ontology controlled annotation
Example: find the right experts at NASA
Expertise locator for nearly 20,000 NASA civil servants using RDF integration techniques over 6 or 7 geographically distributed databases, data sources, and web services…
(Courtesy of Clark & Parsia, LLC)
Other Application Areas Come to the Fore
- Knowledge management
- Business intelligence
- Linking virtual communities
- Management of multimedia data (e.g., video and image depositories)
- Content adaptation and labeling (e.g., for mobile usage)
Thank you for your attention!
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