The Tetherless World Weblog

Two complimentary strands of semantic web

Strand 1: “semantic” aspect, powerful knowledge representation, database quality data, centralized workflows for knowledge management. E.g. oracle triple store. It has enterprise uses case, e.g. bio-medial study.

Strand 2: “web” aspect. Publish knowledge rather than text on the Web. Rooted in the original vision of the Semantic Web. while the promise look great, the real world use cases are fairly poorly understood.

Challenge: “Can strand 2 semantic web applications overcome the data chaos of the emergence semantic web”

Semantic Wiki lives in both strands. It inherits the web 2.0 nature from wiki and is quite easy to be adopted, and in the mean time, it has pretty good support to encode structured data using RDF.

On promising potential is that semantic wiki may enable ontology convergence. Note that without convergence, semantic data may be in chaos and thus less useful. In halo experiment, ontology convergence has been observed in collaborative annotation contributed by college students.

Several findings learned from

* user interface matters, (sure, semantic web developers should pay more attention to UI for better adoption)

* gardening matters (wikibots works, so does semantic wiki bots)

* user created ontology are not always well-designed (that’s why administrators are needed to clean up, but how to deal with such imperfectness and will that cause data chaos? )

* natural language is necessary to augment bare RDF(S) semantics (the “situation calculus” problem indeed is a good justification, as we cannot encode all in semantic web way, some free text may help fix the empty space in the absence of semantic wiki. )

Digital Aristotle for scientific knowledge - Halo project (2006): to build a question answer system that allows domain experts to build robust system for answering challenging and complex questions.

Conclusions

* the two strands of semantic web should meet each other.

* semantic wiki is one the applications that can bridge both strands

* halo demonstrated that by addressing hard AI problem using semantic wiki.

By Li Ding, Greetings from ISWC 2008

The ISWC 2008 keynote was presented by John Giannandrea (Metaweb Technologies Inc)

Semantic Web is based on a graph database which is not natively supported by relational database or column store. (More accurately, graph database is brought back by semantic web community while it was quite prospective in database community ten years ago.)

Ontology creation is a social process, and both freebase and semantic wiki are tools that enable users to create ontological vocabulary without worrying too much on building a comprehensive ontology. With such open-ended ontology, and effective query language is very important. Interesting enough, the query language of Freebase and Semantic Wiki shares similar flavor - they envision the semantic web as a instance store: where-clause simply describes a filter for instances, select-clause focus on retrieving the properties of the result instances.

Here are some facts about freebase:

* Scale of freebase: 156,000,000 assertions made; 1370 published types; 75 domains. (well, it is easy to see that most published types are well populated)

* view about the Semantic Web

Yes: graph model, identity, web based.

No: no description log; schema not ontology; a writable database!

* Freebase is not formal system cyc, OWL, sumo, true knowledge, and halo; nor google base.

* An industrial view on the relation between audience and complexity (inverse)

Google > Wikipedia > Del.icio.us > NY Times > dbpedia > cyc, OWL2

(Well, industrial people only care and learn what is needed to achieve their goals. They care more on functions, adoption and profits, and they are less picky on soundness and completeness.)

Freebase is dealing with an “identifier” web. While one thing may have quite some name, the names collaboratively contribute the semantics too. (yes, identity is a key problem for web application)

Greetings from ISWC 2008 by Li Ding