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

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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

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From Talis: “Jim Hendler at the INSEMTIVE 2008 Workshop”

“that people will (and do) create metadata when there are obvious and immediate benefits in them doing so. No-one really consciously sits down to share or create metadata: they sit down to do a specific task and metadata drops out as a side-effect.”

I can not agree any more. I have tried to tag all my blogs once upon a time, after a few weeks, I found myself bored because there is no clear, immediate benefits for doing so. I would only tag things that I have to, like to tell my friends a list of posts of the same topic.

The only tagging system that is consistently successful upon me is the gmail labeling: I organize mails related to the same task (like writing a paper) on daily bases, because it is very useful, and immediately useful. Even though, I only label a tiny fragment of all my emails.

I have seen too many people have their desktop full of files and too lazy to organize them – myself is one of them. Every year I have to spare a day or two to reorganize my harddisk, and dig out the hidden treasures of my “Downloads” folder. I believe for semantic web to be successful, creating an ontology should be at least as easy as and as useful as organizing files on a harddisk.

In fact, people are creating meta data or even ontology everyday: every email sorting, every contact on the cell phone, every folder creating, every calender item, every wiki post, … We just need to make them explicit, and most of all, without bothering the user to click even one more button.

Jie Bao

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Stefan Decker raised a case “missing children” indicating that Description Logic, or more precisely open world assumption, maybe overkill because it is not needed in most real world applications even though AI researchers like it.

Michel Dumontier, as a researcher trying to adopt OWL, reviews the well-known semantic web benefits, again, from the SW developer community who hopes these nice features will be helpful to real world Web developers and users.

Tim Finin, “maybe we’re a victim of our own success”. Moving towards KR monoculture could be quite dangerous. He raises some examples that OWL does not fit, e.g. when encoding knowledge extracted from knowledge, a lot of information lots such as time, uncertainty, and provenance.

Ian Horrocks claims that OWL has good connection with other KR approaches, OWL is not going to solve all problems, but it is useful in general.

One biggest argument raised by many is that “is OWL useful?” not even “is OWL2 useful”. Of course there are both supportive and negative evidences, and neither side can convince the other side. Someone also argue that the learning curve of OWL will just stop potential user. (Industrial adoption is a better benchmark because researchers are more flexible).

Another issue is “scalability”. Jim Hendler tried to be even worse than Stefan, Twine is claimed to Semantic Web applications, it use a few pieces of OWL to scale up. In general, scalability is the non-negotiable requirement of Web data computation. That is database community avoids, for instance, recursion in relation algebra.

A third question, raised by David Karger, “what are we doing with OWL? Which pieces of OWL are actually being used, and Why?” (This is actually a motivation for OWL2, and why three OWL2 fragments are proposed. We are looking forward to see if OWL working group can give industrial users a good answer.)

Well, a fourth question is “OWL2 is KR, i.e. a family of Description Logics profiles that link to other KR languages?” and/or “OWL2 is trying to promote better web or semantic web applications?”.

Closing remarks (I did my best to keep it original)
* Ian, “choose hope, not fear”
* Tim, “I can see Russia from my house”
* Michel, “OWL is pretty good language”
* Stefan, “if you did not fix the little thing, you may miss the boat”

By Li Ding
Greetings from ISWC 2008

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