János Bólyai’s seminal work on non-Euclidean geometry was published as an “Appendix” to his father’s mathematical textbook. Would hardly be considered as an academic publication today…

Yesterday a colleague in the UK, Jeni Tennison, published a great blog on her site. The title is probably very much unclear for the non-initiated (“Using “Punning” to Answer httpRange-14”) and the details are not of relevance for now. Suffices it to say that she touches on one of the “permathread” discussions that regularly rages on the various technical mailing lists related to Semantic Web. Jeni’s blog offers a very clear explanation of the problem and offers a way forward.

Apart from the technical content I was wondering: would that blog ever be considered as part of Jeni’s academic achievements if she was working at an academic institution? And the answer is, sadly, a clear “no”. “No”, because she “just” wrote it is a personal communication, and she did not go through the time consuming road of “official” publications in a journal or a conference. ”No”, because she does not have formal scientific references, “just” references to mailing lists, wiki pages and the like. ”No”, because the blog was not officially peer reviewed; alas! the fact that she had very long and discussions on some of her ideas on public mailing list with some of the best known experts in the field does not count. “No”, in spite of the fact that, if her ideas are accepted by the community (which is, of course, in no way sure), these would influence the technical direction for the work of hundreds of people, as well as practically deployment of systems, software, etc; at the minimum, there will be dozens if not hundreds of reactions and references to this blog in the days and weeks to come. I can easily make the bet that her piece will have a greater influence in the advancement of a particular area of science and technology than many of the hundreds of academically high valued papers that are published this year.

Is this Jeni’s loss? If she is to pursue an academic career then, of course it is. But it is a much greater loss for science that ignores such intellectual achievements by keeping to its outdated scholarly commutation rules. In fact, it shows that science may have to go back to its old traditions of communication: after all, in the good old times, many of the greatest achievements of science were first published as personal letters or journals. Something have been lost…

(If you are interested in these issues, you may consider looking at the Force11 Community’s Web site and the Force11 Manifesto… that community will, hopefully, evolve significantly in the months to come.)

Although part of the RDFLib project on GitHub, the two modules are pretty much independent of the core RDFLib library, although they are built on top of it. I hope that, with the help of people who know the RDFLib internal structures better, both modules can become, eventually, part of the core. But this may take some time…

I was at Chris Welty’s keynote yesterday at the WWW2012 Conference. His talk was on Jeopardy/Watson and, although this is not the first time I heard/saw something on Watson, some things really became clear only at his keynote. Namely: what is really the central paradigm that made the question answering mechanism so successful in the case of Watson?

Well… query answering in Watson is not some sort of a deterministic algorithm that turns a natural language question into a query into a huge set of data. This approach does not work. Instead, a question is analyzed and, based on search in various set of data, a large set of possible answers is extracted. These “candidate” answers are analyzed separately along a whole series of different dimensions (geographical or temporal dimensions, or, which I found the most interesting, putting back candidate answers into the original question and search that again against various sources of information to rank them again). The result is a vector of numerical values representing the results of the analysis along those different dimensions. That “vector” is summed up into one final value using a weight values for each dimension. The weights themselves are obtained through a prior training process (in this case using a number of stored Jeopardy question/answers). Finally, the answer with the highest value (I presume over a certain threshold value) is returned.

I hope I got it right:-). But the mechanism is certainly something like that. And it is interesting: it is different from the traditional question/answer approaches which is, usually, much more “deterministic”. This is some sort of a new computing paradigm (not necessarily invented by the Watson team, but used by them). Is it a really important new paradigm? Well… to quote Chris: “We won!”.

Although there are some controversies as for the usability of these crawls as well as the interpretation of their results (see Martin Hepp’s mail, and the answer by Peter Mika as well as the resulting thread on the mailing list) I think what is really important is the big picture which emerges from both set of results: no one can reasonably dispute the importance of structured data in HTML any more. Although I vividly remember a time when this was was a matter of bitter discussions, I think we can put this issue behind us now. I do not think I can summarize it better than Peter did in another of his emails:

…both studies confirm that the Semantic Web, and in particular metadata in HTML, is taking on in major ways thanks to the efforts of Facebook, the sponsors of schema.org and many other individuals and organizations. Comparing to our previous numbers, for example we see a five-fold increase in RDFa usage with 25% of webpages containing RDFa data (including OGP), and over 7% of web pages containing microdata. These are incredibly impressive numbers, which illustrate that this part of the Semantic Web has gone mainstream.

The LDOW20** series have become more than workshops; they are really a small conferences. I did not count the number of participants (the meeting room had a fairly odd shape which made it a bit difficult) but I think it was largely over a hundred. Nice to see…

The usual caveat applies for my notes below: I am selective here with some papers which is no judgement on any other paper at the workshop. These are just some of my thoughts jotted down…

Giuseppe Rizzo made a presentation related to all the tools we know have to tag texts and thereby being able to use these resources in linked data (“NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud”), i.e., the Zemanta or Open Calais services of this World. As these services become more and more important, having a clear view of what they can do, how one can use them individually or together, etc., is essential. Their project, called NERD, will become an important source for this community, bookmark that page:-)

Jun Zhao made a presentation (“Towards Interoperable Provenance Publication on the Linked Data Web”) essentially on the work of the W3C Provenance Working Group. I was pleased to see and listen to this presentation: I believe the outcome of that group is very important for this community and, having played a role in the creation of that group, I am anxious to see it succeed. B.t.w., a new round of publication coming from that group should happen very soon, watch the news…

Another presentation, namely Arnaud Le Hors’ on “Using read/write Linked Data for Application Integration — Towards a Linked Data Basic Profile” was also closely related to W3C work. Arnaud and his colleagues (at IBM) came to this community after a long journey working on application integration; think, e.g., of systems managing software updates and error management. These systems are fundamentally data oriented and IBM has embarked into a Linked Data based approach (after having tried others). The particularity of this approach is to stay very “low” level, insofar as they use only basic HTTP protocol reading and writing RDF data. This approach seems to strike chord at a number of other companies (Elsevier, EMC, Oracle, Nokia) and their work form the basis of a new W3C Working Group that should be started this coming summer. This work may become a significant element of palette of technologies around Linked Data.

Luca Costabello talked about Access Control, Linked Data, and Mobile (“Linked Data Access Goes Mobile: Context-Aware Authorization for Graph Stores”). Although Luca emphasized that their solution is not a complete solution for Linked Data access control issues in general, it may become an important contribution in that area nevertheless. Their approach is to modify SPARQL queries “on-the-fly” by including access control clauses; for that purpose, an access control ontology (S4AC) has been developed and used. One issue is: how would that work with a purely HTTP level read/write Linked Data Web, like the one Arnaud is talking about? Answer: we do not know yet:-)

Igor Popov concentrated on user interface issues (“Interacting with the Web of Data through a Web of Inter-connected Lenses”): how to develop a framework whereby data-oriented applications can cooperate quickly, so that lambda users could explore data, switching easily to applications that are well adapted to a particular dataset, and without being forced to use complicated programming or use too “geeky” tools. This is still an alpha level work, but their site-in-development, called Mashpoint is a place to watch. There are (still) not enough work on user-facing data exploration tools, I was pleased to see this one…

What is the dynamics of Linked Data? How does it change? This is the question Tobias Käfer and his friends try to answer in future (“Towards a Dynamic Linked Data Observatory”). For that, data is necessary, and Tobias’ presentation was on how to determine what collection of resources to regularly watch and measure. The plan is to produce a snapshot of the data once a week for a year; the hope is that based on this collected data we will learn more about the overall evolution of linked data. I am really curious to see the results of that. One more reason to be at LDOW2013:-)

Tobias’ presentation has an important connection to the last presentation of the day, made by Axel Polleres (OWL: Yet to arrive on the Web of Data?) insofar as what he presented was based on the analysis of the Linked Data out there. The issue has been around, with lots of controversy, for a while: what level of OWL should/could be used for Linked Data? OWL 2 as a whole seems to be too complex for the amount of data we are talking about, both in terms of program efficiency and in terms of conceptually complexity for end users. OWL 2 has defined a much simpler profile, called OWL 2 RL, which does have some traction but may be still too complex, e.g., for implementations. Axel and his friends analyzed the usage of OWL statements out there, and also established some criteria on what type of rules should be used to make OWL processing really efficient; their result is another profile called OWL LD. It is largely a subset of OWL 2 RL, though it does adopt some datatypes that OWL 2 RL does not have.

There are some features that are left out of OWL 2 RL which I am not fully convinced of; after all their measurement was based on data in 2011, and it is difficult to say how much time it takes for new OWL 2 features to really catch up. I think that keys and property chains should/could be really useful on the Linked Data, and can be managed by rule engines, too. So the jury is still out on this, but it would be good to find a way to stabilize this at some point and see the LD crowd look at OWL (i.e., the subset of OWL) more positively. Of course, another approach would be to concentrate on an easy way to encode Rules into RDF which might make this discussion moot in a certain sense; one of the things we have not succeeded to do yet:-(

The day ended by a panel, on which I also participated; I would let others judge whether the panel was good or not. However, the panel was preceded by a presentation of Chris on the current deployment of RDFa and microdata which was really interesting. (His slides will be on the workshop’s page soon.) The deployment of RDFa, microdata, and microformats has become really strong now; structured data in HTML is a well established approach out there. RDFa and microdata covers now half of the cases, the other half being microformats, which seems to indicate a clear shift towards RDFa/microdata, ie, a more syntax oriented approach (with a clear mapping to RDF). Microdata is used almost exclusively with schema.org vocabularies (which is to be expected) whereas RDFa makes use of a larger palette of various other vocabularies. All these were to be expected, but it is nice to see being reflected in collected data.

It was a great event. Chris, Tim, and Tom: thanks!

One of the “associations” I had, maybe somewhat surprisingly, is with another paper I read lately, namely a report on basic profiles for Linked Data[2]. In that paper Nally et al. look at what “subsets” of current Semantic Web specifications could be defined, as “profiles”, for the purpose of publishing and using Linked Data. This was also a general topic at a W3C Workshop on Linked Data Patterns at the end of last year (see also the final report of the event) and it is not a secret that W3C is considering setting up a relevant Working Group in the near future. Well, the experiences of an engine like SWSE might come very handy here. For example, SWSE uses a subset of the OWL 2 RL Profile for inferencing; that may be a good input for a possible Linked Data profile (although the differences are really minor, if one looks at the appendix of the paper that lists the rule sets the engine uses). The idea of “Authoritative Reasoning” is also interesting and possibly relevant; that approach makes a lot of pragmatic sense, I wonder whether this is not something that should be, somehow, documented for a general use. And I am sure there are more: In general, analyzing the experiences of major Semantic Web search engines on handling Linked Data might provide a great set of input for such pragmatic work.

I was also wondering about a very different issue. A great deal of work had to be done in SWSE on the proper handling of owl:sameAs. On the other hand, one of the recurring discussions on various mailing list and elsewhere is on whether the usage of this property is semantically o.k. or not (see, e.g., [3]). A possible alternative would be to define (beyond owl:sameAs) a set of properties borrowed from the SKOS Recommendation, like closeMatch, exactMatch, broadMatch, etc. It is almost trivial to generalize these SKOS properties for the general case but, reading this paper, I was wondering: what effect would such predicates have on search? Would it make it more complicated or, in fact, would such predicates make the life of search engines easier by providing “hints” that could be used for the user interface? Or both? Or is it already too late, because the ubiquitous usage of owl:sameAs is already so prevalent that it is not worth touching that stuff? I do not have a clear answer at this moment…

Thanks to the authors!

1. A. Hogan, et al., “€œSearching and Browsing Linked Data with SWSE: the Semantic Web Search Engine”€, Journal of Web Semantics, vol. 4, no. December, pp. 365-401, 2011.
2. M. Nally and S. Speicher, “Toward a Basic Profile for Linked Data”, IBM developersWork, 2011.
3. H. Halpin, et al. “When owl:sameAs Isn’t the Same: An Analysis of Identity in Linked Data”, Proceedings of the International Semantic Web Conference, pp. 305-320, 2010

Image via Wikipedia

There has been a flurry of activities around RDFa 1.1 in the past few months. Although a number of blogs and news items have been published on the changes, all those have become “officialized” only the past few days with the publication of the latest drafts, as well as with the publication of RDFa 1.1 Lite. It may be worth looking back at the past few months to have a clearer idea on what happened. I make references to a number of other blogs that were published in the past few months; the interested readers should consult those for details.

The latest official drafts for RDFa 1.1 were published in Spring 2011. However, lot has happened since. First of all, the RDFWA Working Group, working on this specification, has received a significant amount of comments. Some of those were rooted in implementations and the difficulties encountered therein; some came from potential authors who asked for further simplifications. Also, the announcement of schema.org had an important effect: indeed, this initiative drew attention on the importance of structured data in Web pages, which also raised further questions on the usability of RDFa for that usage pattern This came to the fore even more forcefully at the workshop organized by the stakeholders of schema.org in Mountain View. A new task force on the relationships of RDFa and microdata has been set up at W3C; beyond looking at the relationship of these two syntaxes, that task force also raised a number of issues on RDFa 1.1. These issues have been, by and large, accepted and handled by the Working Group (and reflected in the new drafts).

What does this mean for the new drafts? The bottom line: there have been some fundamental changes in RDFa 1.1. For example, profiles, introduced in earlier releases of RDFa 1.1, have been removed due to implementation challenges; however, management of vocabularies have acquired an optional feature that helps vocabulary authors to “bind” their vocabularies to other vocabularies, without introducing an extra burden on authors (see another blog for more details). Another long-standing issue was whether RDFa should include a syntax for ordered lists; this has been done now (see the same blog for further details).

A more recent important change concerns the usage of @property and @rel. Although usage of these attributes for RDF savy authors was never a real problem (the former is for the creation of literal objects, whereas the latter is for URI references), they have proven to be a major obstacle for ‘lambda’ HTML authors. This issue came up quite forcefully at the schema.org workshop in Mountain View, too. After a long technical discussion in the group, the new version reduces the usage difference between the two significantly. Essentially, if, on the same element, @property is present together with, say, @href or @resource, and @rel or @rev is not present, a URI reference is generated as an object of the triple. I.e., when used on a, say, <link> or <a> element, @property  behaves exactly like @rel. It turns out that this usage pattern is so widespread that it covers most of the important use cases for authors. The new version of the RDFa 1.1 Primer (as well as the RDFa 1.1 Core, actually) has a number of examples that show these. There are also some other changes related to the behaviour of @typeof in relations to @property; please consult the specification for these.

The publication of RDFa 1.1 Lite was also a very important step. This defines a “sub-set” of the RDFa attributes that can serve as a guideline for HTML authors to express simple structured data in HTML without bothering about more complex features. This is the subset of RDFa that schema.org will “accept”,  as an alternative to the microdata, as a possible syntax for schema.org vocabularies. (There are some examples on how some schema.org example look like in RDFa 1.1 Lite on a different blog.) In some sense, RDFa 1.1 Lite can be considered like the equivalent of microdata, except that it leaves the door open for more complex vocabulary usage, mixture with different vocabularies, etc. (The HTML Task Force will publish soon a more detailed comparison of the different syntaxes.)

So here is, roughly, where we are today. The recent publications by the W3C RDFWA Working Group have, as I said, ”officialized” all the changes that were discussed since spring. The group decided not to publish a Last Call Working Draft, because the last few weeks’ of work on the HTML Task Force may reveal some new requirements; if not, the last round of publications will follow soon.

And what about implementations? Well, my “shadow” implementation of the RDFa distiller (which also includes a separate “validator” service) incorporates all the latest changes. I also added a new feature a few weeks ago, namely the possibility to serialize the output in JSON-LD (although this has become outdated a few days ago, due to some changes in JSON-LD…). I am not sure of the exact status of Gregg Kellogg’s RDF Distiller, but, knowing him, it is either already in line with the latest drafts or it is only a matter of a few days to be so. And there are surely more around that I do not know about.

This last series of publications have provided a nice closure for a busy RDFa year. I guess the only thing now is to wish everyone a Merry Christmas, a peaceful and happy Hanukkah, or other festivities you honor at this time of the year.  In any case, a very happy New Year!

The main hall of the Library of Congress

There was an official news a few days on the publication of the W3C Library Linked Data Incubator Group final report. The report is an interesting read even though I am probably not part of the “typical” target readership. After all, the primary goal of this report is really to convince the reader on the interest and importance of combining the activities of libraries with Linked Data… But the key recommendations of the report are worth repeating:

• That library leaders identify sets of data as possible candidates for early exposure as Linked Data and foster a discussion about Open Data and rights;
• That library standards bodies increase library participation in Semantic Web standardization, develop library data standards that are compatible with Linked Data, and disseminate best-practice design patterns tailored to library Linked Data;
• That data and systems designers design enhanced user services based on Linked Data capabilities, create URIs for the items in library datasets, develop policies for managing RDF vocabularies and their URIs, and express library data by re-using or mapping to existing Linked Data vocabularies;
• That librarians and archivists preserve Linked Data element sets and value vocabularies and apply library experience in curation and long-term preservation to Linked Data datasets.

However, what was not absolutely clear from the original announcement is that the official report also has two “companion” documents, namely a Use Case collection, and a list of references to metadata element sets in RDF, to relevant vocabularies, and to published element sets (e.g., the sets of URI-s, set up by the US Library of Congress, listing all countries in the World). This document, entitled “Datasets, Value Vocabularies, and Metadata Element Sets” is a real, somewhat hidden gem: a possible starting point for practitioners who wants to work with Library Linked Data! Thanks to Antoine Isaac and his friends for collecting these. I wonder how we could get it regularly updated…

Zhishi.me is the outcome of the work of a group from the APEX lab in Shanghai and Southeast University: it is, in some ways, the Chinese DBPedia. “In some ways” because it is actually a mixture of three different Chinese, community driven encyclopedia, namely the Chinese Wikipedia, Baidu Baike and Hudong Baike. I am not sure of the exact numbers, but the combined dataset is probably a bit bigger than DBpedia. The goal of Zhishi.me is to act as a “seed” and a hub for Chinese linked open data contributions, just like DBpedia did and does for the LOD in general.

It is great stuff indeed. I do have one concern (which, hopefully, is only a matter of presentation, i.e., may be a misunderstanding on my side). Although zhishi.me is linked to non-Chinese datasets (DBPedia and others), the paper talks about a “Chinese Linked Open Data (COLD)”, as if this was something different, something separate. As a non-English speaker myself I can fully appreciate the issues of language and culture differences but I would nevertheless hate to see the Chinese community develop a parallel LOD, instead of being an integral part of the the LOD as a whole. Again, I hope this is just a misunderstanding!

There were a number of ontology or RDF graph visualization presentations, for example from the University of Southampton team (“Connecting the Dots”), on the first results of an exploration done by a Magnus Stuhr and his friends in Norway, called LODWheel (the latter was actually at the COLD2011 Workshop), or another one from a mixed team, led by Enrico Motta, on a visualization plugin to the NeOn toolkit called KC-Viz. I have downloaded the latter, and have played a bit with it already, but I haven’t had the time to have a really informed conclusion on it yet. Nevertheless, KC-Viz was interesting for me for a different reason. The basic idea of the tool is to use some sort of an importance metric attached to each node in the class hierarchy and direct the visualization based on that metric. It was reminiscent to some work I did in my previous life on graph visualization, though the metric was different, the graph was only a tree, the visualization approach was different, but nevertheless, there was a similar feel to it… Gosh, that was a long time ago!

The paper of John Howse et al. on visualizing ontologies was also interesting. Interesting because different: the idea is a systematic usage of Euler diagrams to visualize class hierarchies combined with some sort of a visual language for the presentation of property restrictions. In my experience property restrictions is a very difficult (maybe the most difficult?) OWL concept to understand without a logic background; any tool, visual or otherwise, that helps teaching and explaining this can be very important. Whether John’s visual language is the one I am not sure yet, but it may well be. I will consider using it the next time I give a tutorial…

I was impressed by the paper of Gong Cheng and his friends from Nanjing, “Empirical Study of Vocabulary Relatedness…”. Analyzing the results of a search engine (in this case Falcons) to draw conclusion on the nature, the usage, the mutual relationship, etc., of vocabularies is very important indeed. We need empirical results, bound to real life usage. This is not the first work in this direction (see, for example, the work of Ghazvinia et al, from ISWC2009), but there is still much to do. Which reminds me of some much smaller scale work Giovanni, Péter and I didon determining the top vocabulary prefixes for the purpose of the RDFa 1.1 initial context (we used to call it default profile back then). I should probably try to talk to the Nanjing team to merge with their results!

I think the vision paper of Marcus Cobden and his friends (again at the COLD2011 Workshop) on a “Research Agenda for Linked Closed Data” is worth noting. Although not necessarily earthshaking, the fact that we can and we should speak about Linked Closed Data alongside Linked Open Data is important if we want the Semantic Web to be adopted and used by the enterprise world as well. One of the main issue, which is not really addressed frequently enough (although there have been some papers published here and there) is access control. Who has the right to access data? Who has the right to access a particular ontology or rule set that may lead to the deduction of new relationships? What are the licensing requirements, how do we express them? I do not think our community has a full answer to these. B.t.w., W3C organizes a Workshop concentrating on the enterprise usage of Linked Data in December…

Speaking about research agenda… I really liked Frank van Harmelen’s keynote on the second day of the conference. His approach was fresh, and the question he asked was different: essentially, after 10 or more years of research in the Semantic Web area, can we derive some “higher level” laws that describe and govern this area of research? I will not repeat all the laws that he proposed, it is better to look his Web with the HTML version of his slides. The ones that is worth repeating again and again are that “Factual knowledge is a graph”, “Terminological knowledge is a hierarchy”, and “Terminological knowledge is much smaller than the factual knowledge”. Why are these important? To quote from his keynote slides:

1. traditionally, KR has focussed on small and very intricate sets of axioms: a bunch of universally quantified complex sentences
2. but now it turns out that much of our knowledge comes in the form of very large but shallow sets of axioms.
3. lots of the knowledge is in the ground facts, (not in the quantified formula’s)

Which is important to remember when planning future work and activities. “Reasoning”, usually, happens on a huge set of ground facts in a graph, with a shallow hierarchy of terminology…

I was a little bit disappointed by the Linked Science Workshop; probably because I had wrong expectations. I was expecting a workshop looking at how Linked Data in general can help in the renewal of the scientific publication process as a whole (a bit along the lines of the Force11 work on improving the future of scholarly communication). Instead, the workshop was more on how different scientific fields use linked data for their work. Somehow the event was unfocussed for me…

As in some previous years, I was again part of the jury for the Semantic Web Challenge. It was interesting how our own expectations have changed over the years. What was really a wow! a few years ago, has become so natural that we are not excited any more. Which is of course a good thing, it shows that the field is maturing further, but we may need some sort of a Semantic Web Super-Challenge to be really excited again. That being said, the winners of the challenge really did impressive works, I do not want to give the impression of being negative about them… It is just that I was missing that “Wow”.

Finally, I was at one session of the industrial track, which was a bit disappointing. If we wanted to to show the research community that the Semantic Web technologies are really used by industry, then the session did not really make a good job on that. With one exception, and a huge one at it: the presentation of Yahoo! (beware, the link is to a PowerPoint slidedeck). It seems that Yahoo! is building an internal infrastructure based on what they call “Web of Objects”, by regrouping pieces of knowledge in a graph-like fashion. By using internal vocabularies (superset of schema.org) and using the underlying graph infrastructure they aim at regrouping similar or identical knowledge pieces harvested on the Web. I am sure we will hear more about this.

Yes, it was a full week…

Indeed, this document stands a little bit apart. Instead of adding to the query (and now also update) language, it concentrates on how the HTTP protocol should be used in conjunction with graph stores. I.e., what is the meaning of the well known HTTP verbs like PUT, GET, POST, or DELETE  for graph stores, what should be the response codes, etc. It is important to emphasize that this HTTP behaviour is not bound to SPARQL endpoints; instead, it is valid for any Web sites that serve as a graph store. This could include, for example, a Web site simply storing a number of RDF graphs with minimal services to get or change the content of those. (In this respect, this document is closer to, e.g., the Atom Publishing Protocol which includes similar features for ATOM data, and which also plays an important role for technologies like, for example, OData.) Because such setups, i.e., “just” stores of RDF graphs without a SPARQL endpoint, are fairly frequent, it is important to have these HTTP details set. So… worth looking at this document and send feedbacks to the Working Group! (Use the public-sparql-dev@w3.org mailing list for comments.)