Semantic Web Company

Sorry for still writing about last week, but the TRIPLE-I conference had far too many interesting topics to offer for me to be already through with them – promise, this blog post about wikis will be the last TRIPLE-I post.

An interesting use of wikis was introduced with the Moki plugin for Semantic Media Wiki, developed as a side product of the APOSDLE project. APOSDLE (EU-project leaders love their acronyms;-) aims to develop an Advanced Process-Oriented Self-Directed Learning Environment, which in plain language is a platform to support the process of learning at work. In the course of this project, a model of the enterprise knowledge had to be developed that was to be the collaborative result of domain experts within the enterprise and external knowledge engineers. The APOSDLE image video below conveys a sense of the complexity of the knowledge to be represented.

But on to Moki: As wikis are an ideal, readily available tool for collaboration, the simple solution was to build a plugin (Moki) for Semantic Media Wiki that allow to structure and engineer the domain knowledge. Moki is a hierarchy builder that supports drag and drop so that categories and relations can easily be fitted in place – the special benefit of using Semantic Media Wiki was that the structure of the generated knowledge can be exported in Semantic Web compliant formats. Apart from the browser, no further software is required.

The APOSDLE website doesn’t yet offer any information about Moki, but a description can be found in the conference proceedings: Collaborative Knowledge Engineering via Semantic MediaWiki, by Chiara Ghidini, Marco Rospocher (who gave the presentation), Luciano Serafini, Viktoria Pammer, Barbara Kump, Andreas Faatz, Andreas Zinnen, Joanna Guss, Stefanie Lindstaedt.

For those looking for good arguments for setting up a wiki in a global business environment: Peter Kemper’s keynote was the perfect primer for that. Peter, a Knowledge Management portfolio manager at Shell’s IT-Department, gave some insights into the process of their conversion to wikis. Before there were wikis at Shell, they had global discussion forums, connecting 20,000 people around topics and questions, which were intensively used – the question whether wikis should be adopted or not alone generated 800 responses in these forums.

Instead of going for team wikis, Shell opted for the encyclopedic approach and a wiki that would be accessible to anyone at Shell, and for using MediaWiki – which was, interestingly, the first open source software ever used at Shell. Peter Kemper named scalability and the lean architecture as prime arguments for MediaWiki, and they have indeed not had any technical hiccups so far. It was also an asset that people, being used to Wikipedia, know how to use the MediaWiki interface.

Examples of uses case with which the feasibility of wikis within Shell were tested were: Drilling salt, Geology of the Atlantic Margin, and Production Chemistry. Before that, the main media for maintaining and passing on knowledge had been emails and Powerpoint – not exactly because these were considered appropriate for knowledge management, but because of the effects these media had had on the communication within Shell:

With the advent of email, People wrote less and less memos. Less and less reports were sent to the archive, because people kept powerpoint presentations. If that same information, previously locked in emails and powerpoint, went now into wiki, it would finally be accessible to everyone in the company.

Peter Kemper allowed us a glimpse of the information their wiki held, for instance, about the Atlantic Margin – as geological structures are described, most of the information relies on images. It would be a nightmare to maintain this kind of information in Powerpoint! No offense meant: Powerpoint is good for presentations but not for creating and maintaining a knowledge base. According to Peter, with wikis Shell achieved six times the productivity in comparison to using Powerpoint, in particular due to the linkability of content.

Wikis also turned out to be the superior solution for the integration of curricula from an internal learning environment, as wikis support the modular structure of a learning curriculum. Furthermore, they are also a good means to sustain communication in the time between workshops or team meetings.

At shell, they even use wiki for instance for the translation of contracts into the requirements of day to day procedures – a typical contract in the business that Shell is in has around 400 pages, and it is probably not very likely that a single person is going to read (and immediately understand) the entire contract. In this regard, the wiki also serves as a tool to translate lawyer-readable prose into transparent instructions (and there are probably many more ways in which wikis can be used to support business processes, a statement also put forward by Rolf Sint from Salzburg Research; see his 12 seconds statement below).

Rolf Sint talks about workflows in wikis on 12seconds.tv

A noteworthy detail about the integration of wikis in Shell’s IT architecture: If a user logs onto the wiki for the first time and goes beyond the disclaimer, a new wiki account is automatically created that is identical with his or her windows account – this is not about checking on people, Peter Kemper said, but about creating organisational transparency.

On the one hand, this reveals whether there are organisational units within Shell where the wiki is not as intensively used as elsewhere, meaning that these units probably have specific needs which need to be addressed first. On the other hand, people can (and do) also contact each other via the wiki, e.g. one can contact the person who created an article if one is on need of further information.

About stimulating content production: 60% of Shell’s employees will go into retirement over the next eight years, and with them knowledge that is needed in the company. They even asked and paid former employees to come out of retirement to work on the wiki – that’s what I call commitment to content creation and knowledge preservation.

The Shell wiki already has more than 40,000 registered users (with 150,000 employees in the company, plus contract staff). What is interesting regarding user activation is that the number of active users stays relatively the same, even if the number of users in total increases. Peter Kemper’s account for this was that content comes in waves, meaning that users are activated in those areas where fresh knowledge is generated.

Kemper distinguished three types of users: content owners who create content from scratch; content editors who often just correct syntax or make things ‘look nicer’; and information consumers. Kemper rejected the term ‘lurkers’ for information consumers as looking for information is an activity in itself.

All in all, Peter Kemper’s talk confirmed many of the assumptions which have informed our own KiWi – Knowledge in a Wiki project, the aim of which is to merge the wiki philosophy with knowledge management, enhanced by semantic (web) technologies. Sebastian Schaffert (Salzburg Research) puts it in a nutshell in the video below. Featured in a cameo appearance: the KiWI!

Sebastian Schaffert about KiWi – Knowledge in a Wiki on 12seconds.tv

The TRIPLE-I 2008 conference ended three days ago, yet there are a couple of loose ends I’d still like to tie up. First of all: Linked Data. Tom Heath was invited to give a keynote on “Humans and the Web of Data” – there are a variety of roles in which people may come across Tom and his LOD related work:

He administrates the site LinkedData.org (on behalf of the Linked Data community), he is the creator of Revyu.com (“Review anything!”), which won him the 1st prize in the Semantic Web Challenge 2007, he was a co-organizer of the Linked Data on the Web Workshop at this year’s World Wide Web conference in Beijing, and he was an interviewee in my 12 seconds definitions mission @ TRIPLE-I – see his micro definition of Linked Data in the vid below. (To learn more about Tom and the different roles he fulfils, look here).

Tom Heath explains Linked Data TRIPLE-I 2008 on 12seconds.tv

His keynote was not so much an introduction to Linked Data (I should expect that a conference like TRIPLE-I/I-Semantics would typically attract people who at least have an idea of what Linked Data is about), but rather a confirmation that the Web of Data is no longer a fiction, but a fact. One of the often cited proofs is the growth of the LOD dataset cloud over the last year, as shown in the image below (clicky for biggy, visualization created by Richard Cyganiak).

At the same time – and this was accordingly acknowledged by a later presentation given by Wolfgang Halb which had been prepared collaboratively by Tom, Wolfgang, Michael Hausenblas and Yves Raimond – it’s not just the sheer number of triples on the web that counts. Over the course of one year, the efforts of the Linked Data community (who seek to populate the web with open data, data in RDF) generated 4 billion triples – but only 3 million interlinks.

Their paper was an attempt to measure the size of the Semantic Web based on interlinks. A brief excerpt from the conclusion:

We have identified two different types of datasets, namely single- point-of-access datasets (such as DBpedia), and distributed datasets (e.g. the FOAF-o-sphere). At least for the single-point-of-access datasets it seems that automatic interlinking yields a high number of semantic links, however of rather shallow quality. Our finding was that not only the number of triples is relevant, but also how the datasets both internally and externally are interlinked. Based on this observation we will further research into other types of Semantic Web data and propose a metric for gauging it, based on the quality and quantity of the semantic links. We expect similar mechanisms (for example regarding automatic interlinking) to take place on the Semantic Web.

Another point raised by Tom in his key note was the issue of trust: According to his research, there are five parameters that have an influence on whether we trust a source or recommendation on the web or not: experience , expertise, impartiality (we don’t trust a travel agent, because we can’t help but believe that she is mainly going to recommend the offer of her ‘favourite’ clients), affinity, and track record, with experience, expertise and affinity being the most important ones. A semantic people search engine Tom presented, Hoonoh.com (currently in alpha), thus allows to weight search results according to these three criteria.

Tom’s concluding statement emphasized that Linking Data makes sense not for the sake of it, but for the sake of being at the service of humans: “A web of machine-readable data is even more interesting from a human than from a machine perspective,” for instance in search engines like Hoonoh.com

This last day of TRIPLE-I, the conference consisting of three events (I-SEMANTICS,I-KNOW, I-MEDIA) was probably my favourite one, even though I am of course a bit biased: It was Linked Data day, with a keynote by Tom Heath which I will cover in more detail on Monday, but we need to be heading home now.

The key issue for me still is the quest for making the Web of Data a reality, and I once again noted that the main question raised within the Semantic Web community continues to be: “We have such a great technology – why isn’t everybody adopting?” I guess that the answers somewhere are along the lines of this comment from Greg Boutin:

Things will get better as more and more folks get interested in it, and “translators” from the early majority (see http://en.wikipedia.org/wiki/Diffusion_(business) ) start to kick in and explain what this is in plain language.

Defining a process for introducing Linked Data like a new product to the market – that is what I’d like!

The last keynote today was given by Dickson Lukose from the Research and Development agency MIMOS in Malaysia – the Malaysian government seems to be putting a lot of money into IT R & D at the moment. Anyone looking for a good place to get a startup funded might consider doing it in Malaysia!

This blog post concludes with a 12 seconds good-bye message from Michael Hausenblas, saying hello to the web of Data Practitioners Days in Vienna on Oct 22-23, the next SemWeb Community event here in Austria. See you there!

Michael Hausenblas says goodbye TRIPLE-I, c u at WebofData.info on 12seconds.tv

Sören Auer just announced the winners of the LOD Triplification Challenge at TRIPLE-I:

1. Linked Movie Data Base by Oktie Hassanzadeh, Mariano Consens (MacBook Air or € 1.000 )
2. DBTune by Yves Raimond (Asus EeePC or € 300 )
3. Semantic Web Pipes Demo by Danh Le Phuoc (iPod Touch or € 200

Congratulations! View a listing of all the nominees here, where you can also download the descriptions. Other good news: Roughly 80% (my guess) of the audience at this morning’s keynotes raised their hands when asked if they had not only heard about the term Semantic Web, but were also familiar with its concepts – not surprising probably for those interested in the I-SEMANTICS track, but good to get this feedback from the I-KNOW and I-MEDIA attendees. The Semantic breakthrough is nigh!

The challenge was called Triplification challenge as it was centred around Triplify and initiated by the Triplify Team. But what is Triplify? Sören Auer explains it in 12 seconds:

Sören Auer explains Triplify in 12 Seconds on 12seconds.tv

This second day of TRIPLE-I 2008 was my personal folksonomy day, even though the theme was already set yesterday, with Andreas Hotho’s invited talk about “Extracting Semantics from Folksonomies” which was the opening lecture of the workshop “Knowledge acquisition from the Social Web.”

Andreas Hotho is directing the Bibsonomy project at Kassel University’s Knowledge and Data Engineering resarch group; Bibsonomy is a social bookmark and publication sharing system catering especially for researchers who, next to bookmarkingm also wish to manage publications. Next to other interesting things, Bibsonomy supports the import of bookmarks from del.icio.us, Firefox bookmarks and local BibTex files. Being a project led by a university’s computer science department, Bibsonomy is at the same time the result, the object and a stimulus for research in the area of tagging and folksonomies. Andreas describes this double appeal of folksonomies to both ordinary people and researchers in a 12 seconds vlog post:

Andreas Hotho’s statement about folksonomies and research (see www.bibsonomy.org) on 12seconds.tv

One of the outcomes of the research into folksonomies is FolkRank, a search algorithm that exploits the structure of folksonomies; the name reveals that it was inspired by PageRank, but as the graph of folksonomy structures does not correspond to the web graph, some adaptations had to be made. The specifics of these adaptations can be found in an online article by Andreas and his colleagues: “FolkRank: A Ranking Algorithm for Folksonomies” (PDF, 268 KB).

Andreas Hotho’s talk more specifically addressed the search for methods to identify tags which describe the same concept (or a more specific / a more general concept respectively) within a folksonomy. He suggested two approaches:

1. Applying measures directly to folksonomy statistics, allowing to describe tags as a vector; e.g. co-occurrence frequency and FolkRank could serve as a similarity measure (with these two having a tendency towards high-frequency tags) or a cosine method (which is more likely to produce “siblings”)
2. Looking up tags in an external thesaurus/vocabulary (for instance achieving semantic grounding by mapping a tag and its most similar tags with Wordnet Synsets)

Future areas of interest within folksonomy research Andreas proposed were trend detection, tag recommendation, detecting spam (a major challenge!), logsonomies (i.e. the structure of search engine query log files) and learning synsets, hierarchies, and structures of folksonomies. Andreas Hotho can be contacted via his homepage, if you have any further questions regarding Bibsonomy, FolkRank or this present piece of research.

Another presentation dedicated to folksonomies – and the presentation that won my personal presentation design award – was “Seeding, Weeding, Fertilizing – Different Tag Gardening Activities for Folksonomy Maintenance and Enrichment” by Katrin Weller and Isabella Peters, both from the Dept. of Information Science at Heinrich Heine University in Düsseldorf. The entire presentation was designed to match the CI of Tagcare, a tag gardening tool that is hopefully going to go online soon.

The term “Tag Gardening” was borrowed from James Governor who wrote in a 2006 blogpost:

“Like plants or animals, tags evolve in an emergent fashion, open to hybridisation. Stewardship can help grow and put roots down.

Helping the darwinian process is tag gardening.

Tag gardening is about taking tags in the wild and tending to them, or identifying a wild tag that will do well in your south facing IT

garden. I am talking about domestication here.

Just like there are professional bloggers i am pretty sure some parties will emerge that get paid for their abilities.”

I seriously hope that the latter is going to come true, even though I have the feeling that most providers will continue to consider user input and effort pro bono work!

Katrin Weller’s intro (Isabella Peters had excused herself) focused on the well-known problems with tags and folksonomies, e.g. :

• spelling variants, synonyms, abbreviations, different natural languages
• adhoc or personal functions of tags other than content description (e.g. “toread”, “@Henry”, “nicepic”)
• flatness of tag clouds which allows for browsing by popularity, but not by semantic interrelations

She further distinguished three levels where tag or tag cloud improvement becomes relevant:

• single document vs document collection level
• Single user vs collaborative level
• intra- and cross plattform level (e.g. different tagging conventions, tag separation with comma or blank space, etc)

To push the gardening metaphor even further, Kathrin presented us their ideas of weeding, seeding, fertilizing etc.:

Weeding
The weeds in this case are “bad” tags like spam or misspelled tags (weed: any plant that crowds out cultivated plants)
Aim: enhancing recall and a consistent indexing vocabulary
Achieved by: type-ahead functionality, editing funcionalities, natural language processing, user guidelines for indexing and retrieval, nomination of authorized users as gardeners

Seeding
Seeding in folksonomies means to expand frequently used tags by more specific tags (called “baby tags” or “seedlings” by Katrin Weller; seedling: young plant or tree grown from a seed)

Landscaping
The idea of landscaping here means to create “flower beds” through identifying species of tags, e.g. by similarity.
Aim: enhancing precision and expressiveness

Fertilizing
Fertilizing in this context means to combine folksonomies with other knowledge organization systems (KOS): thesauri, controlled vocabularies, ontologies, etc. (fertilizer: any substance such as manure or a mixture of nitrates used to make soil more fertile). Fertilizing might work both ways, Katrin suggested: a folksonomy might be fertilized with the semantic structure of a KOS, or a KOS enhanced by terms from a folksonomy.

And finally TagCare: The ambitious plan is to have a system that allows to import tag clouds from Flickr, deli.icio.us and Bibsonomy, cleanse out dissimilarities between tags, add hierarchical structure to the tag clouds, allow the user to view tag statistics and probably also to have community features, such calibrating one’s tags with those of the chief gardener or to activate collaborative spam elimination. It is going to be a free service, and if you want to be notified when it goes live, you might want to send an email to Katrin.

This full-service proposal for tag gardening does of course sound brilliant – yet is it going to be feasible, on a technical level? In the post-presentation discussion, somebody mentioned Faviki, which relies on DBpedia concepts to solidify the tag cloud. It didn’t exactly seem as though the TagCare team had already thought along these (semantic web) lines, even though this perfectly corresponded to their ‘Fertilizing’ idea. But if TagCare solely relies on good human gardeners, how long will it take until they have gained a big enough community to stimulate someone’s altruism? The idea of tag gardening of course is beautiful, and I am curious to learn more about the technology it is going to use.

Other folksonomy and tag related presentations that I was unable to attend or am unable to describe now, after the 10th hour of my 2nd day at TRIPLE-I, with a band performing folkore music involving yodeling and probably Schuhplattler right outside of this room:

• Quality Metrics for Tags of Broad Folksonomies (Celine Van Damme, Martin Hepp, Tanguy, Coenen, University of Brussels, Universität der Bundeswehr München
• Providing Multi Source Tag Recommendations in a Social Resource Sharing Platform (Martin Memmel, Michael Kockler, Rafael Schirru, German Research Centre for Artificial Intelligence DFKI)
• Semantic Tagging and Inference in Online Communities, Yildirim Ahmet, Ãœsküdarli Suzan, BoÄŸaziçi University
• Using Visual Features to Improve Tag Suggestions in Image Sharing Sites (Mathias Lux, Oge Marques, Arthur Pitman, Klagenfurt University)
• Harnessing Wikipedia for Smart Tags Clustering (Maria Grineva, Maxim Grinev, Denis Turdakov, Pavel Velikhov, Russian Academy of Sciences)

Please leave a comment if you think that any of the above needs correction.

EDIT: I got the chance to record another 12 seconds definition (and am thinking of setting up a video glossary for the Semantic Web now): Rolf Sint from Salzburg Research explains what folksonomies are and why folksonomies and ontologies go together well in 12 seconds! Rolf is also involved in the KiWi project, which aims to develop a wiki-based knowledge management system boosted by semantic technologies.

Rolf Sint explains folksonomies and their relation to ontologies on 12seconds.tv

The TRIPLE-I conference in Graz today started with a keynote by Henry Lieberman, research scientist at the MIT Media Laboratory. Given that, nominally, at least a third of the conference is dedicated to knowledge managemen, Lieberman introduced an important, often overseen aspect of knowledge management right at the beginning: Managing knowledge that everybody knows already.

Knowledge management typically aims at knowledge that people do not know yet, e.g. (tacit) knowledge that people have acquired in a project and that is suppose to be made explicit and accessible to other people who don’t yet have this knowledge.

But what about the knowledge that everybody knows without them knowing they need to know it? Such as that an apple is a type of fruit, and is green and is red? Common sense knowledge?

I boldly asked Henry Lieberman for a 12 seconds definition of Common Sense Knowledge, a challenge he accomplished with perfect precision:

Henry Lieberman defines Common Sense Knowledge on 12seconds.tv

An intriguing MIT project I hadn’t yet heard about which Henry Lieberman introduced is the Common sense knowledge base Open Mind Common Sense – anyone can sign up to it and contribute. A total of 203 knowledge facts have, for instance, been accumulated about the concept “apple”, including facts such as these:

→ An apple is red
→ An apple is green
→ Apples grow in trees
→ an apple are food.
→ An apple has a core
→ An apple can fall from a tree
→ An apple is a type of fruit

Offered similar concepts are “egg, potato, steak, bread, spinach, frozen food, butter, appl [sic], leftover, grape”. The process of adding knowledge is guided by a list of questions that allow to conceptualize and structure the knowledge, e.g.

MadeOf
What is it made of?
IsA
What kind of thing is it?
UsedFor
What do you use it for?
CapableOf
What can it do?
PartOf
What is it part of?
DefinedAs
How do you define it?

But what are the roles that common sense knowledge can play in interactive applications? Henry Lieberman suggested using common sense knowledge, a system can e.g. anticipate what a user is most likely to do, or it can at least make most likely things easiest to do, e.g. by providing a map from goals to concrete actions in the interface, or by integrating appropriate applications.

Lieberman furthermore introduced a couple of tools which illustrated these benefits, e.g. the prototype for an Event Minder for improved scheduling driven by common sense knowledge. Entering a statement such as “Lunch with Charlie at Miracle next Friday” would for instance calculate the date of ‘next Friday’, call up a calendar application and also a web service to get directions for getting to Miracle.

Regarding the difference between CYC (the common sense knowledge ontology) and the MIT’s common knowledge base Open Mind Common Sense: CYC is an ontology organized by experts with a broader and deeper knowledge – the common knowledge base grants access to anyone and has, for instance, also information about kitten that might not be that relevant to experts. At this stage, there is no mapping to CYC.

Henry Lieberman’s keynote tied in nicely with a presentation by Andrew S. Gordon about “Envisioning with Weblogs”. According to Andrew Gordon, there have been three waves in the 50 year history of common sense knowledge in artifical intelligence:

First wave: Logical formalizations of commons sense knowledge (e.g. CYC)
Second wave: volunteer contributions from web communities (e.g. Open Mind Common Sense)
3rd wave: Knowledge acquisition from the social web (e.g. Envisioning with Weblogs)

First off, what is envisioning? Andrew Gordon described it as a form of reasoning about states and events in time and space, generating answers to questions such as “What’s happening in the world right now?”, or “What is going on in the audience’s mind right now?”, or “How did this person get into the room?”, or “What am I going to have for dinner tonight?”

At the Institute for Creative Technologies (University of Southern California), Andrew is involved in a project called Story Representation and Management, which among other things, is doing research on story interpretation, i.e. “techniques for integrating automated commonsense inference into the processing of narrative text documents, and methodologies for creating very large scale commonsense knowledge bases.”

One of the paths towards the creation of this knowledge base is gathering up stories on weblogs. But can we really gather up all stories ever written in a weblog? In the research conducted and cited by Andrew (Gordon 2007), 4,5 million stories, made up of 66,6 million sentences and 1,06 billion words were extracted from weblogs.

In Gordon’s recipe for envisioning with weblogs, the retrieval of the closest situation provides the best results. Take for instance the quest of formalizing this particular problem in common sense physical reasoning: cracking an egg into a bowl (as described by Morgenstern 1998, Lifschitz 1998, Shanahan 1998).

There are so many things to be considered: Is the bowl big enough? What if the bowl is made of cardboard? What of the egg is hardboiled? Common sense knowledge in stories on weblogs does offer many answers, for instance this story from Amit Asaravala – which also generates further knowledge as to what would happen to a person who does this:

Seeing the little weirdo reminded me of one Saturday morning, a year or so ago, when I cracked an egg into a bowl and found three yolks inside. After tossing the triplets, I cracked another egg from the batch and found yet another three yolks jiggling up at me. Another egg, another trio of blondes.

This continued through all twelve eggs — I kid you not.

Though the episode had me thoroughly creeped out, I must say that I am somewhat intrigued by the thought that, on some farm somewhere, there is a crotchety old hen that consistently lays triple-yolkers.

In the following discussion, some people wondered if weblogs aren’t an unreliable source for a common sense knowledge database. Andrew however doubted that the difference true/false or the difference true/fictitious did really matter. Instead he suggested that in 99% of the cases the same physical reasoning applies in, say, the Star Wars Universe as does apply in the real world.

Common sense knowledge is not about the velocity of spacecrafts crossing the milky way, it’s about what happens if Leia punches Han.

Which is yet another point sustaining that common sense knowledge is so obvious that most of the time we don’t even know we know it. And that’s a challenge to knowledge management.

Oh, and something very nice happened to me today: While I sat in our booth preparing this blog post, someone approached me very politely saying that he had read my name somewhere before, on some blog. Turns out this person – Stefano Bertolo, Project Officer at the Information Society Directorate of the European Commission – has in the past also left a comment on the Flickr page of our “Escape from the Data Silo” logo (which can be used freely by anyone on a CC license). It’s a small world, thanks to Social Media:-) We had a nice conversation at our booth, during which he also recommended the NeON project: Lifecyle Support for Networked Ontologies: a recommendation which I herewith pass on to you, reader of this blog:-)

P.S. There were many more interesting talks and sessions, but the scope of this blogpost is, sadly, limited by the rules of physics: I could only attend one talk at a time.

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