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May 12, 2010

RIF (Core) and LOD

Filed under: Semantic Web,Work Related — Ivan Herman @ 8:36
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Linked Data (Semantic Web) candies
Image by reedster via Flickr

W3C has just published a Proposed Recommendation for the Rule Interchange Format (RIF); this means, in the W3C jargon, that the technical work is done, and the W3C asks its members for a seal of approval to publish it as Recommendation.

Somehow the RIF development was not on the radar screen of the Semantic Web community. There may be many reasons for that, and I think we should just accept this as part of history. The future is much more important; we should indeed realize that RIF is an important piece of the Semantic Web technical architecture and let us do our best to get it embraced widely.

RIF Core is the simplest variant of RIF. It is not very complicated. It is a simple rule language; one can define a series of Horn rules, there are some safety features built in so that the rules can be executed, conceptually, by a forward chaining engine, it has the familiar XSD datatypes with the usual operations, it operates on URI-s, and it has a notion analogous to RDF blank nodes. There is a separate document that describes how RIF (Core) rules operate with RDF data and how the various semantics (RIF, RDF(S), OWL) work together. The details are not really important here, suffices it to say that it, essentially, works like one would expect as a layperson… The RIF syntax is a little bit convoluted for the moment, but there may be work coming up to improve that in form of alternative, more readable syntaxes.

So what can it be used for? At the W3C LOD Camp in Raleigh (held as part of the WWW2010 conference), Sandro Hawke already gave a simple example why RIF should be interesting for LOD applications. Let me add a few further examples that might be of interest.

Remember OWL-RL? The OWL Working Group has defined a subset of OWL that can be handled by rules. The rules themselves were also published by the OWL WG, albeit using an abstract notation. Those rules can be described in RIF Core as well; the RIF group has published this mapping in a separate document. Following those rules a RIF Core engine can handle OWL-RL directly.

Why is that interesting?—you might ask. Well, there has been quite some discussions when defining OWL RL on whether the features included in OWL RL represent the right set for users. Some claimed that there are other OWL features that could be added; others said that, on the contrary, the complexity of OWL RL is already too high and the features should be reduced to make them more palatable to users. In some ways, the usage of RIF Core may make this discussion moot. Indeed, users, or user communities, can define the rules they are interested in RIF by cherry picking the rules described by the RIF WG in the document cited above. They can send those rules to their RIF Core reasoner alongside their data, and get what they want. If that rule set consists only of 2-3 OWL rules, because that is all the application cares about, than all the better, the RIF inference engine will just do its job faster. If the user wants to add OWL features that are not in OWL RL, that may also be doable; the OWL 2 RDF-Based semantics specification is such that, in many cases, the extra rules can be extracted fairly easily from the OWL 2 Full semantics, using the patterns in the RIF/OWL RL document (although I have to emphasize that this does not work in all cases!). Note that this model of “sending” the RIF rule set alongside the RDF data to a reasoner is exactly the way RIF reasoning is being defined for SPARQL1.1 in the separate Entailment Regimes document (still in draft). Note also that I referred to OWL RL here, but the same approach could be used with RDFS with, obviously, a smaller RIF Rule set.

Another, albeit related application of RIF came to my mind reading an email discussion on whether inferences should be materialized for large LOD datasets or not and, if yes, which ones. As an answer to Vasiliy Faronov’s question, Leigh Dodds also proposed a text to be added to his Linked Data Patterns book. The resulting discussion thread was really about which inferences should really be materialized. Materializing them all may not be realistic; but if only a selection of the possible inferences is used (eg, subset of RDFS or OWL) how would consumers of the data know? It looks like RIF may come to rescue. Publishers could simply publish the rules they use for materializing their inferences in RIF. (Again, this is not always possible; RIF cannot cover the whole of OWL. But it does cover a very large percentage of the use cases.) Consumers may actually choose whether they want to download all the triples, including the inferenced triples, or whether they choose to download data from the “core” dataset only together with the RIF file, and materialize the inferences locally using a local RIF engine (or use the RIF file with an RIF Entailment aware SPARQL 1.1 engine).

RIF is and should be considered as integral and essential part of the Semantic Web Technology landscape. Let us hope many implementations of, at least, RIF Core will bloom to make this a reality! (There is a public list of existing implementations so far.)

April 17, 2010

AR and Linked Data

Filed under: Semantic Web,Work Related — Ivan Herman @ 16:56
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I had the pleasure to be at a an Augmented Reality (AR) Dev Camp today in Amsterdam. It was a very heterogeneous crowd, from Semantic Web people (after all, one of the organizers was Dan Brickley) to artists. But that is probably the nature of AR these days…

AR is of course not a new discipline; I guess the R&D in AR goes back at least 15 years. But the appearance of high-end mobile devices made this, suddenly, a viable business: the fact that the devices have location capabilities and as well as compasses make it possible to create really cool applications. Johannes la Poutré made a nice and short overview of what is happening in this area; another nice example is the “Berlin Wall is back” application.

What does this have to do with Linked Data, you might ask. Well the very essence of these applications is to use data to increase the visual experience of a mobile phone camera. And use lots of data. And use lots of up-to-date and semantically organized data, because applications have to have intelligent filtering to save bandwidth. This means that developers in AR look at linked data with lots of interest; they were pleased to hear about, eg, Dutch governmental data becoming (gradually…) available as linked data, about the LOD cloud, about technologies like Zemanta, Open Calais, RDFa… Yes, AR on mobile might become a significant application area for Linked Data. A space to watch!

(B.t.w., although it was not an augmented reality project, some of you might remember Christian Becker‘s and Chris Bizer‘s work on DBpedia Mobile: that was some sort of a precursor for some of the ideas that appear today as part of AR applications. Just imagine those Wikipedia/DBPedia data appearing on top of what you see with your camera!)

P.S. Putting my W3C hat on: W3C organizes a Workshop on Augmented Reality and Virtual Interactivity, to be held in June, in Barcelona. Interested?

February 13, 2010

Semantic 3D (Visit to the Fokus 3D workshop)

Filed under: Semantic Web,Work Related — Ivan Herman @ 8:26
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I had the pleasure, in the past two days, to participate at a workshop called Fokus3D. It was the closing event of a European R&D project of a similar name, concentrating on what is called Semantic 3D. I was invited because the project made use of certain types of Semantic Web technologies (e.g., OWL) and, also, because it is the community of my previous professional life: I did spent many years in Computer Graphics… (Which also meant that I met old friends and colleagues that I had not seen for many years, which was really very pleasant…)

So what is this “Semantic 3D”? What does it have to do with Semantic Web?

Here is a a crash course on 3D graphics: when systems display those beautiful graphics 3D objects that we are all used to, the underlying system transforms complex mathematical descriptions of shapes, surfaces, or 3D bodies into a load of (triangular) meshes that are displayed by the graphics hardware. The mathematical descriptions are purely geometrical and define, say, spline surfaces, planes, or some geometric transformations that place those surface description into space.

These 3D objects represent, usually, some real object. A chair, a car, a tree, or a house. The representation of a chair is a combination of several such shapes; some of those describe the arms, the back, etc. But this information, i.e., that this and this combination of shapes is actually the arm of a chair, is usually lost somewhere in the process. Modelers start with a concept, a “semantic”, and end up with shapes; information is gone on the way. This means that many things cannot be done well: one would like to have semantics based search (“searching for the arm of a chair”), one would like to know the origin of a a particular shape (i.e., how was it created, under what process and transformation), one would like to follow the evolution in time of a particular shape to retrace the designer’s actions, etc., etc. And, due to the huge number of shapes, managing this type (meta) data is far from obvious. Keeping that information in a manageable way together with the geometric processing: we get Semantic 3D.

There was, of course, a slight confusion of terms for me: this notion of semantics would be considered as (meta)data for Semantic Web people. That being said, such data requires controlled vocabularies, and very complicated ones at that, so there are strong connections nevertheless. But there is also semantics in terms of knowledge representation: There are relationships among, and classification of, shape elements, these relationships can represent constraints and other features that can be used for reasoning, for inference. So more complex ontologies come into the picture (and OWL is widely used in this space). These ontologies are often application dependent, reflecting the diversity of application areas from CAD to gaming, or from cultural heritage systems to medical and biological applications. In future, such ontologies should also incorporate features like uncertainty (reflecting the fact that, at least in some areas like protein modeling, those relationships are not necessarily crisp); they should also include features such as provenance or time relationships.

Last but not least: there are lots of data there. I mean lots, stored in biological databases, shape libraries, scanned historical artifacts, each representing an object (like the reproduction of the Ramses statue on the figure) with many many shapes. Integration of that data is a challenge even within one application area, let alone with data at large. It will take a long time when this data will be organized in a way that it could be, say, exposed and integrated as Linked Open Data. But we may get there, eventually (and your truly has done his best to convince the community of the value of doing that…). Standard representations have to be developed, algorithms crystallized, vocabularies and ontologies defined, etc. The good news is that there is a community that is determined to continue working in this direction. The workshop organizers plan to write down a research roadmap (to be put on line within 1-2 weeks), and a special issue of the journal “Computer & Graphics” has been announced, co-edited by Bianca Falcidieno, from the CNR in Genova, and myself. So… stay tuned.

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July 4, 2009

Dagstuhl Workshop on Semantic Web

Filed under: Semantic Web,Work Related — Ivan Herman @ 18:31
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Dagstuhl castleI have just come back from the Workshop “Semantic Web: Reflections and Future Directions”, held in Dagstuhl, Germany. Organized by John Domingue, Rudi Studer, Jim Hendler, and Dieter Fensel, the workshop positioned itself as the “second release” of a similar workshop that was held at the same place 10 years ago.

The first two days of the workshop were more traditional, in the sense that it was series of presentations and panels. This was the “reflection” part of the workshop: looking back to 10 years’ of history as well a peek into the current state of the art. It was interesting but, for my taste, a bit too long; the programme of the two days could have been compressed into one or, say, one and a half days. That would have given more time to the “future directions” part, ie, discussions in break out groups on various topics. I enjoyed those a lot: free flowing discussions on various topics, helping to exchange ideas, experiences, pointers at other works and results, and crystallizing possible future R&D issues. These discussions took place in a very pleasant, relaxed atmosphere among people who mostly knew one another already, ie, we could really concentrate on issues. Each group formulated a number of research goals for the years to come; some group also came up with more practical steps and goals.

As far as I know, the workshop organizers plan to collect all those research issues in some more coherent form, so we should watch this space. In what follows I just collect some issues that I took away from the workshop without the goal of being exhaustive; indeed, there were 6-7 parallel break out groups.

Issues around Web scale. This is clearly one of the major topics of the day. What happens when one has to deal with data containing billions of triples, when the data (ie, the triples) are “dirty”, ie, inconsistent, faulty, etc. Think of the Linked Open Data cloud, of data coming from sensor networks, mobiles, etc. Do we have to re-think all the notions that the Semantic Web inherited from the logic world, ie, completeness, meaning and consequences of consistency, what it means to get results for a query, etc? This is one area where opinions tend to diverge a lot. Some would prefer to completely put aside the traditional logic approaches (rules, descriptions logic, ontologies, OWL, etc), while others may argue that the advances in computing, in reasoning engines and methods are (and are expected to be) such that these methods should still be just as usable as before. As always, I hate any black-and-white statements… I do not think dismissing an area of technology is the right way but, also, other avenues, or new viewpoints should to be explored, too (e.g., how to react on inconsistencies, trying to get possibly incomplete results but whatever can be obtained within, say, 2 minutes, that sort of things). What approach would be used is very much dependent of the application. Anyway… Web scale is a major issue, everybody agrees on that!

Interaction. This is one of the break out groups that I did not attend, unfortunately. And obviously a hugely important direction of future R&D. Many Semantic Web applications today are such that their user interface is just standard because all Semantic Web related work happens behind the scenes, usually on the server side. However, on long term, there is a clear need for programs that could somehow directly show the data in some friendly way, programs that self-adapt themselves to the nature of the data. Not only for experts, but also for laypeople. Such environments may not only include extensions of current browsers but, eg, full desktop environments. Sort of intelligent, data-oriented user interfaces. A major research problem (user interface methodology is always a major problem, whether related to Semantic Web or not…), but also a hugely exciting research and development opportunities!

Vocabularies. There was a separate group on the management of vocabularies, which has identified a number of R&D issues: how does one describe a vocabulary, its interdependence with other vocabularies, how does one rank vocabularies… These are all fundamental question to solve to be able to find vocabularies for a specific purpose, to make specialized search. There are also issues around archiving, providing stable URI-s; last but not least (and this goes way beyond vocabularies only) major legal issues on what type of attribution, copyright or other legal machinery are to be used with vocabularies (it was good to have Tom Heath, who could tell us a bit about the datacommons’ approach). As an example of the many technological problems arising, the break-out groups coined the term “cherry picking of terms”. Although OWL has a mechanism for import, the practice of the RDF world is to use (ie, “cherry pick”) vocabulary terms (predicates, classes, etc) from various different vocabularies without necessarily taking the whole vocabulary, and certainly without using the owl:import predicates (think of routine usage of dc:title without importing the full Dublin Core vocabulary). How would a reasoner treat those? It may be a little bit easier to use a more rule based approach (like OWL RL) although it is not obvious how to cherry pick just the right amount of information on a, say, predicate. But Ian Horrocks also drew my attention on formal ontology modularization work that might be very relevant here; item added to my “to-be-read” list…

Provenance (and trust). One of the issues that popped up in all other break out groups; in consequence a separate one was formed on the second day of discussions. It is indeed one of the questions that anyone who talks about Semantic Web gets; in my personal view, having a clear “story” to tell about provenance is essential for a further deployment of this technology. The discussion in the group was really interesting because this issue raises a number of other questions, like the overall relationship of cryptographic techniques and the Semantic Web, what it means to have trust in context, what are the relationships to temporal or uncertainty reasoning, etc, etc, etc. It was also interesting for me to hear about other works, like the Open Provenance Model, albeit some of these were not necessarily done by Semantic Web people (eg, by the database community). We agreed that a Wiki page will be created (probably at RPI, set up by Deb McGuinnis) to collect information on this subject, and forming a W3C Incubator Group might also be in the books to provide a more thorough state-of-the-art. A long list of additional items to my “to-be-read” pile is coming…

And, of course, it was also good to meet a bunch of people, discuss things at lunch or dinner. This type of interaction is really fruitful. And there was also intensive twittering going on (using the #swdag2009 tag, pointing to a bunch of other reseources) although this time I did not twitter too much because I had problems with my wireless card:-(

It was a good meeting; thanks for the organizers. Would be good not to wait another 10 years for the next incarnation of this event…

June 20, 2009

SemTech2009 impressions (addendum)

Filed under: Semantic Web,Work Related — Ivan Herman @ 15:09
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I wrote a blog yesterday on my SemTech impressions; I realized this morning that I forgot to add an item although I intended to.  Peter Deitz did indeed a presentation on a site called “social actions”: essentially a specialized index and search engine on various social, non-governmental actions around the World that one might want to join, contribute to, etc.  (Eg, the search on climate change will point you to a number of corresponding actions aroud the globe.) The interesting aspect, from the Semantic Web point of view, is that Peter would like to integrate the data, the access, etc, to the rest of the SW, essentially to the LOD (although he did not use this term), but he needs (and asks for) help from the community. Beyond the clear value of this particular dataset this is becoming a pattern (the NYT example in my blog yesterday is similar): people realize the value of publishing their data in a Linked Data format, but it is difficult to make the first steps. Even more tutorials, descriptions, and mainly community help is needed. That is essential for the success of Linked Data!

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June 19, 2009

SemTech2009 impressions

Filed under: Semantic Web,Work Related — Ivan Herman @ 22:35
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The first and possibly most important aspect of SemTech 2009 is that… it happened! I must admit that back in April-May, when the conference’s Web Site did not include any news of the program yet, I was a bit concerned that the general economic malaise would kill this year’s conference. O.k., I might have been paranoiac, but I think some level of concern was indeed legitimate. And… not only did the conference happen as planned, but the numbers were essentially the same as last year’s (over 1000). I think that by itself is an important sign of the interest in Semantic Technologies. Kudos to the organizers!

A general trend that was reaffirmed this year: by now, Semantic Web technologies are the obvious reference points for almost all presentations, products, etc, that were presented at the event. RDF(S), RDFa, OWL, SPARQL, etc, have become household names; newer specs like SKOS or POWDER may not have been as widely referred to yet, but I am sure that will come, too. Linked Data (and, more specifically, the Linked Open Data cloud) were almost ubiquitous this year while I do not believe that it was even mentioned last year. That is a huge change (although I still miss real “user facing” applications of LOD to show up; some, like Talis’ system deployed at UK universities, were presented but not as part of the regular conference). All that being said, I somehow seem to have missed more sessions than last year, which make my impressions more patchy. There were several journal interviews that I could not escape, hallway discussions that were great but made me miss a presentation here and there… I guess this is what happens when you have such a number of people around!

Tom Tague (from Open Calais) gave a very nice opening keynote. His talk was actually not on Open Calais (he did that in 2008), but rather on his experience in talking to different people who tried to start up new ventures in the Semantic Web area (a quote from his talk: “in 80% of the discussions I did not understand what the vendors wanted, and I walked away with my cheque book intact… Simplify!”). The main areas that he looked at were tools, social, advertising, search, publishing, user interface. One of the remarks I liked was on search: in his view (and I think I agree with that) Semantic Technologies may not be really interesting for general search (where the statistical, i.e., brute force methods work well) but for specialized, area-specific search tools (things like GoPubMed or applications deployed at, eg, Eli Lilly or experimented with at Elsevier come to my mind as good examples). Similarly, these technologies are not necessarily of interest for general, “robotic” publication tools like Google’s news, but for high quality publishing, with possible editorial oversight (reducing costs and difficulties).

(He also had a nice text on one of his slides: “Web2.0: Take Web 1.0, add a liberal dash of social, generous amounts of user generated content, atomize your content assets and stir until fully confused”:-)

Tom Gruber talked about his newest project: SIRI. A super-duper personal assistant running on an iPhone with conversational (voice directed) interface. The group behind it integrates a bunch of info on the Web (the “usual” stuffs like restaurants and travel sites), categorize them, and hide the complexities behind a sexy user interface. The problem I have is that I just do not see how this would scale. I see one of the major promises of the Semantic Web getting data in RDF out there so that such, essentially mash-up applications would become much easier to create and maintain. Until then, it is really tedious… On a more personal note, I am not sure I would like the voice conversational interface. I know that I have never used the voice commands on my phone for example; I do not feel comfortable with it. But, well, that is probably only me…

Chime Ogbuji made a really nice presentation on the system they have developed at the Cleveland Clinic. Great combination of RDF, OWL, and SPARQL. The interesting aspect (for me) was that usage of a medical expert system called Cyc, which is used to convert the doctor’s question in natural language (insofar as a question full of medical jargon can be considered as “natural”:-) into, essentially, a SPARQL query. The medical ontologies are used to direct this conversion process, and then the triple store could be queried through the generated query. Impressive work. (Part of it was documented in a W3C use case, but this presentation had a different emphasis.)

Unfortunately, I had to skip Peter Mika’s presentation on the SearchMonkey experiences, I will have to look at his slides… But, as a last minute addition to the program, the organizers succeeded in getting Othar Hansson and Kavi Goel to talk about Google’s rich sniplets. I have already blogged on this a few weeks ago but this presentation made the goal of the project way more understandable. Essentially, by recognizing specific microformat or RDFa vocabularies, they can improve the user experience by adding extra information on the search result. It is interesting to observe the difference between Yahoo! and Google in this respect: both of them use microformats/RDFa for the same general goal but, whereas Yahoo! relies on the community providing applications and on users personalizing their own search result page, Google controls the output in a generic way that does not require further user actions. It will be interesting to see how these differences influence people’s usage patterns. There were some discussion on the Google’s choice on vocabularies; the presenters made it quite clear that they are perfectly happy using other vocabularies (eg, vCard or FOAF) if they become pervasive, and this is a discussion that Google plans to engage with the community. There is of course a chicken-and-egg issue there (if a vocabulary is known by Google, then it will be more widely used, too), and this is cleary an area to discuss further. But these are details. The very fact that both Yahoo! and Google look at microformats and RDFa is what counts! Who would have thought just about a year ago?

I was not particularl impressed by the Semantic Search panel. I had the impression that the participants did not really know what they should say and talk about:-(

Nice presentation by Jeffrey Smitz from Boeing on a system called SPARQL Server pages. Essentially: the user can use similar structures like, say, a PHP page, ie, a mixture of HTML tags and server “calls”, except that this “calls” refer to SPARQL queries against a triple store on the server. Their system also includes some rule based OWL reasoning on the server side, although I am not sure I got all the details. All in all, the system seemed a bit complex, but the general approach is interesting! And it is nice to see that a company like Boeing seems to make good use of RDF+OWL+SPARQL; it would be good to know more…

I missed Zepheira’s presentation on freemix which is a shame, but, well, it happens. But I did play with freemix before travelling to San Jose;  I called it “Exhibit for the masses”. And this, I think, is a fair characterization. David Huynh’s exhibit is a really nice tool, but it is not easy to use it. On the other hand, it took me about 2 minutes to make a visualization of a json data set I used for an exhibit page elsewhere…

Andraz Tori talked about Common tag, a small vocabulary that, for example, can be used when marking up texts with tags (something that engines like Zemanta or Open Calais do). Bringing the RDF and the tagging worlds together is really important; I am very curious how successful this initiative will be…

The keynote on the last day was from the New York Times (by Evan Sandhaus and Robert Larson). It was quite interesting to see how a reputable journal like the NYT has developed a tradition of indexing, abstracting, cataloging articles, how these are archived and searched. Impressive. It is also great that the NYT Annotated Corpus has been released to the Research community. I did not know about that and, I presume, this must be a great resource for a lot of people active in the are of, say, natural language processing. Finally they announced their intention to release their thesaurus in a Semantic Web format, to add a “blob” to the Linked Data Cloud. They still have to work out the details (and expect feedback from the community) and I would hope they would publish a SKOS thesaurus and might even annotate the news items on their web site using this thesaurus in RDFa. But something in this space will happen, that is for sure! Other reputable newspapers, like Le Monde, the Guardian, NRC Handelsblatt,  el Pais, will you follow?

I also had my share of talking: gave an intro tutorial to SW, gave an overview of what is happening at W3C (quite a lot this year, including the finalization of POWDER, OWL 2, and SKOS!) and participated at an OWL 2 panel (with Mike Smith, Zhe Wu, Deb McGuinnis, and Ian Horrocks). I was quite happy with the tutorial and the way the panel went; the audience for the talk could have been a bit larger. But, well…

It was a long week, long trips, not much sleep… but well worth it!

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June 1, 2009

PWC report on Semantic Web

Filed under: Semantic Web,Work Related — Ivan Herman @ 13:25
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There has already been a number of blogs and tweetes on PriceWaterhouseCoopers’ Spring ’09 Technology Forecast on Semantic Web, but it may still be worth writing about it. The document can be downloaded from the Web free of charge in return for a registration. It includes some of PWC’s own overview on the technology, plus interviews with Tom Scott (BBC), Uche Ogbuji (Zepheira), Lynn Vogel (University of Texas M.D. Anderson Cancer Center), and Frank Chum (Chevron).

The document is clearly not aimed at technologists of the Semantic Web. But there are number of well chosen wordings and quotes that might help us to talk to people around us who have to be convinced about the value of Linked Data/Semantic Web. Just a few of those:

PricewaterhouseCoopers believes a Web of data will develop that fully augments the document Web of today. You’ll be able to find and take pieces of data sets from different places, aggregate them without warehousing, and analyze them in a more straightforward, powerful way than you can now.

[…]

Let’s say your agency represents musicians, and you want to develop your own ontology […]. You might create your own ontology to keep better tabs on what’s current in the music world […]. You also can link your ontology to someone else’s and take advantage of their data in conjunction with yours. Contrast this scenario with how data rationalization occurs in the relational data world. Each time, for each point of data integration, humans must figure out the semantics for the data element and verify through time consuming activities that a field with a specific label […] is actually useful, maintained, and defined to mean what the label implies. Although an ontology-based approach requires more front-end effort than a traditional data integration program, ultimately the ontological approach to data classification is more scalable […]. It’s more scalable precisely because the semantics of any data being integrated is being managed in a collaborative, standard, reusable way.

[…]

With the Semantic Web, you don’t have to reinvent the wheel with your own ontology, because others […] have already created ontologies and made them available on the Web. As long as they’re public and useful, you can use those. Where your context differs from theirs, you make yours specific, but where there’s commonality, you use what they have created and leave it in place. Ideally, you make public the non-sensitive elements of your business-specific ontology that are consistent with your business model, so others can make use of them. All of these are linked over the Web, so you have both the benefits and the risks of these interdependencies. Once you link, you can browse and query across all the domains you’re linked to.

[…]

Traditional data integration methods have fallen short because enterprises have been left to their own devices to develop and maintain all the metadata needed to integrate silos of unconnected data. As a result, most data remain beyond the reach of enterprises, because they run out of integration time and money after accomplishing a fraction of the integration they need.[…] The most basic lesson is that data integration must be rethought as data linking—a decentralized, federated approach that uses ontology-mediated links to leave the data at their sources. The philosophy behind this approach embraces different information contexts, rather than insisting on one version of the truth, to get around the old-style data integration obstacles.

Yeah, we all know that, right? But can we really put it in succint terms for outsiders? That is not that easy… Ie, worth reading the report (and thanks to PWC!).

May 13, 2009

RDFa, Google

Filed under: Semantic Web,Work Related — Ivan Herman @ 8:31
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Imagine that you have a review of a restaurant on your page. In your HTML, you show the name of the restaurant, the address and phone number, the number of users who have provided reviews, and the average rating. People can read and understand this information, but to a computer it is nothing but strings of unstructured text. With microformats or RDFa, you can label each piece of text to make it clear that it represents a certain type of data: for example, a restaurant name, an address, or a rating. This is done by providing additional HTML tags that computers understand.

No, this is not an extract of a page at W3C explaining the role of RDFa, or some academics’ paper on the role of RDF and RDFa. This is an extract of a Google page written for webmasters and explaining why adding such information to a page is useful. It is followed by:

These don’t affect the appearance of your pages, but Google and any other services that look at the HTML can use the tags to better understand your information, and display it in useful ways—for example, in search results.

This was published while I was sleeping; by the time I woke up in Brisbane twitter, mailing lists, news sites, or the blogosphere already talked about the news: RDFa is adopted by Google! Ie, this blog is hardly a prime news any more:-( But this is such a good news that I still felt compelled to write. After Yahoo’s SearchMonkey announcement last year (gosh, what a news that was, too!), the fact that social sites like SlideShare, systems like Drupal, or public thesauri sites like the Library Congress’ Subject Heading page have all adopted all RDFa, this Google announcement means that RDFa is in the mainstream now, that all the work that people have put into this technology is now paying off at last. I must admit, it is a good feeling…

Of course, lot is still to be done. The quoted Google page refers to some specific vocabularies that, I presume, will be indexed explicitly at first (reviews, people, products, and business and organizations). I would expect other vocabularies will follow in due time, developed by various communities around the globe. (As a first step, it would be great if Google adopted some of the exisiting vocabularies like SIOC, DOAP, FOAF, DC…). Developing the right vocabularies for the right communities is still a challenge that the Semantic Web community has to work on. And what would make me even happier would be to welcome Google’s developers to participate in the definition of those, together with the rest of the community, in line with the decentralized nature of vocabulary definitions.

But this is for tomorrow and the day after tomorrow. Today, I am just happy to have this news, and worry about the next step later…

May 1, 2009

Library of Congress Subject Headings in SKOS on line

Filed under: Semantic Web,Work Related — Ivan Herman @ 14:47
Tags: , , , ,

We may remember the experimental lcsh.info site that published the LoC vocabularies on line in SKOS. Well, while lcsh.info was closed down at some point, the official version is now up and running at http://id.loc.gov/authorities/.

This is great news. This means that all items in the LoC subject heading have now a stable, dereferancable URI; the URI refers to a (SKOS) Concept and is linked to broader and narrower terms. The implementation follows the LOD principles; the URI can be dereferenced in an HTML browser providing an RDFa annotated HTML page. To take an example, the subject heading for “Semantic Web” has the URI: http://id.loc.gov/authorities/sh2002000569#concept; dereferencing it leads to an XHTML+RDFa page. The RDF content can be accessed describing the concept in SKOS, providing a link to, eg, the concept of World Wide Web. This vocabulary gives a stable target to characterize the subject of various entities using, eg, the Dublin Core “subject” term. The site provides a search page and the whole dataset can also be downloaded in RDF/XML or n triples.

This is a huge service of the Library of Congress to the Semantic Web community. Thanks to Ed Summers and anybody else who took an active role in it!

April 26, 2009

WWW2009 Impressions

Filed under: Semantic Web,Work Related — Ivan Herman @ 17:55
Tags: , , , , , , , , , , , , ,

As usual, when making notes of a conference like WWW2009, in Madrid, one has only a partial view. This is all the more true for a conference of the size of WWWW2009 with around 1000 attendees and with 5-6 parallel tracks. I must admit that I usually have difficulties with so many tracks at the same time; I obviously loose some of the events happening, which is a source of unavoidable frustration. With this caveat, just some of the topics that I will probably remember…

The power of Twitter. Although this was not a “topic” of the conference, this was the first WWW conference where twitter was king. Twitter was everywhere, the #www2009 topic was getting several new entries per second (it even got spammed:-(, and other twitter tags were used for some of the specialized events (like #w3ctrack or #ldow2009) One could get a glimpse of what was happening elsewhere just by following these topics. In fact, this report is much more sketchy than usual simply because my own tweetes from the conference or, of course, all tweetes of the #www2009 topic can very well replace some of the notes I wrote in blogs in earlier years.

Social networks. Going beyond twitter, the ubiquitous presence of social networks, their effect on just about anything is still a major topic, like the continuous flow of papers trying, eg, to extract semantics from tag clouds (eg, the paper of Benjamin Markines et al) or the Googles and Yahoo!-s of this World trying to exploit these tags to improve their search results. (Yahoo’s experimental tag explorer is a good example trying to exploit these further.) Nothing radically new here, but progress is reported on all conferences, and this one was no exception. One of the keynotes, by Pablo Rodriguez from Telefonica, actually claimed that the needs of social networks in terms of network infrastructure are so different that they are bound to require changes on the hardware/firmware level of networks. Posting, for example, a video on a social site may create a sudden peak of high volume access (for example if posted by a “celebrity”) that makes it very different from the more steady flow of data that more traditional sites provide and require. For example local caching in routers might be needed. I am no expert in this at all (anything that is close to hardware is sort of a black box to me) so I cannot judge these statements but it was interesting to hear. Another interesting point he made was that “celebrities” of a specific network may (not necessary intentionally) start a dos attack against a site: think of the amount of http requests flowing to a site mentioned by one of these social network stars!

Web Science. There was a panel (organized by Nigel Shadbold, with Tim Berners-Lee, Ricardo Baeza-Yates, and Mike Brodie). The whole topic is still fairly open (at least for me): what exactly is Web Science and where are the boundaries? What types of research belongs to WS, and what is better kept outside to be handled by other disciplines? What type of abstractions would be necessary to study the Web as a whole (just as chemistry can be seen as a set of abstractions on top of physics)? What type of interdisciplinary research groups should be established? As far as I am concerned, I do not have a response to any of these questions:-( What I could see happening is that under the banner “Web Science” many different sub-disciplines will appear very soon and gain independent life without too much relationships among themselves. As far as I am concerned, I would be more interested by the relationship between the Web and society at large than by the technical aspects, but that is only me. An interesting practical point for the future is that there are plans to combine (eg, co-locate) future WWW conferences with Web Science events; that would really be a gain for both event series in my view.

Computing cloud. Yep, this comes up more an more often. Obviously a big deal in the keynote of Alfred Spector, from Google, but came up elsewhere, too. The a mini-tutorial on Hadoop, MapReduce, and Hive, given by Tom White as part of the Developers’ track, was really interesting and instructive for me. We know that the computing cloud has a great interest for the Semantic Web community; it may indeed be a tool to handle the significant amount of data out there. The LOD data is already available on the Amazon services (thanks to OpenLink), Chris Bizer and friends’ Mobile DBpedia makes use of cloud facilities, the LarKC project also makes use of massively parallel computing (I am not sure they use the cloud), too. Something to keep an eye on, that is for sure; I am sure the topic will gain more importance in future conferences. (And one more technology I should familiarize myself with…)

Power of data. Issues around search have become the dominating theme of the WWW conferences, and this one was no exception. Many research try to exploit the sheer amount and variety of data that has been accumulated by the big search engines, for example. I have heard several talks over the years coming from Google’s R&D lab (including a keynote at this conference). I must admit the overall impression I get from these is that a more or less straightforward exploitation of a huge amount of data is used like a sledgehammer for all problems. (I am probably unfair.) Ricardo Baeza-Yates (from Yahoo!) also reported some work in his keynote on, eg, analyzing the search queries themselves, ie, the paths of different searches performed by users between the time they begin some search and the time they find what they were looking for. (Interesting stuff! By the way, there is also a conference on weblogs and social media, ICWSM; one more conference coming up around Web technologies.) I also listened to a presentation on Yahoo!’s Boss by Ted Drake (again on the Developers’ track): what is interesting is that one can access to (a part of) Yahoo!’s accumulated indexes to build, eg, one’s own search engines but, I presume, one could also use this data for other type of research exploiting the data. Power of data for the masses? (I have heard of Boss before and I would have welcome more technical details at the presentation but, well…)

Web of data, a.k.a. Semantic Web. The conference started by a great workshop on Linked Data. I again rely on twitter notes and the general twitter notes for more details, no need to repeat them here. Suffices it to say that, beyond the individual papers, there were a general “buzz” in the air, a general enthusiasm that was reflected by the high number of participants (over 100). For anybody interested, it is worth looking at all the papers, they were good! Having said that, what I am really waiting for is to see many real application of the LOD (and not only experimental, university usage) but that takes its time; there were no really breathtaking news on that at the workshop.

But, of course, the workshop was for the converted; what was more interesting is to see that the Linked Data concept, and the Semantic Web in general, created more and more interest at the conference proper and not only for the long time Semantic Web adepts. Jim Hendler did a surprise presentation at the Developers’ track (surprise, because a announced speaker could not come, so he took his place) talking to non-Semantic Web developers about what can be done already today with this technology, about the excitement that is out there, about the companies that have already picked up this technology. It was good to get these messages out there again and again. Georgi Kobilarov did also a great presentation on DBpedia at the track; there were several people I talked to afterward who were really carried away by the possibilities opened up by having access to a huge amount of data through the unifying abstraction of RDF, RDFS, and possibly (a little bit of:-) OWL.

I also went to the Semantic Web referreed paper track, obviously. I must admit I was a little bit disappointed because lots of colleagues that I would typically see on such event that were not around. I presume ISWC has now become major competition to WWW in this area and when money is tight, people have to make a choice. In earlier years ISWC was considered to be much more theoretical while WWW had more practical papers, but the last few ISWC’s I attended seemed to indicate that this is changing. I think any of the WWW papers could have been presented at the ISWC without any problems. As a consequence, I guess many people decided that ISWC is a better place to be. It will be interesting to see how things will evolve in future; it is not impossible that Semantic Web, as a topic, will gradually move away from WWW to ISWC. (I would expect specifically Linked Data papers to appear at ISWC very soon!)

That being said: it was nice to see a paper on DERI Pipes (by Danh Le-Phuoc et al) or on Triplify (by Sören Auer et al). This is not the first time I heard about these but it is good to have them more widely published. There was a paper on a rule system benchmark (by Senlin Liang et al); although I am no expert on this, with the advancement of RIF it will be good to have such benchmarks being put forward. The paper of Philippe Cudré-Mauroux et al on the disambiguation of ID’s on linked data issue caught my attention: with the advancement of linked data we enter (as the presenter put it) an “ID Jungle” with tons of URI-s referring, more or less, to the same concept (eg, a specific person), and a simple owl:sameAs is not an ideal solution to handle this. The idMesh system provides a mean to analyze relationships among those ID-s. I must admit I did not follow all details of the paper but it is certainly one of the papers I will have to study in more details when I get to it!

W3C’s “camps”. W3C tried another model this year, replacing the more traditional W3C tracks by two ‘camps’ on mobile web and on social web. But… this is where the large number of parallel track backfired: I could not go to any of them:-( There were all kinds of overlaps with other presentations (eg, the social web camp fully coincided with the Semantic Web paper track). Pity, because the feedback I heard from participants was very positive. Sigh. Well, actually, courtesy of Fabien Gandon, I was present on the social web camp virtually, witness this slide…

It was a slightly exhaustive but good week!

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