How to model divergent views on one concept?

Such a central model is not only much harder to manage, but there is also the general problem that differerent departments like marketing, quality assurance, R&D, etc. will have divergent views on the model and its concepts. These different perspectives on one and the same concept are hard to unify in a single model.

Think of a company that sells mobile phones and wants to create a model of its line of products. It wants to utilize this model in the context of its online shop as well as in the context of its user support forum. While the structure of the model (i.e. the relationships between the products) might be very similar or the same in both contexts, there will be differences in which properties of the products are actually relevant in the respective contexts.

In the model of the marketing department there might be a concept for a “Phantastax StamiMaxx” cell phone with a definiton “The StamiMaxx has a powerful battery and is great for professionals who travel a lot”. They might relate it to manufacturer “ACME Corporation” and to several concepts representing different features like “Android OS”, “Multi-touch touchscreen”, etc.
The very same phone has different properties that are interesting from the Quality Assurance departement’s perspective. They might call it by a more specific name like “Phantastax i3000 StamiMaxx S”, have a different definition for it like “3G cell phone implementing the new WTF3000 protocol, …” and relate it to concepts representing known problems and their solutions.

Now they face the task to integrate these different models, as it is not desirable to use a bunch of isolated models within one company.

Support of collaborative work on distributed models

To support this kind of collaborative work on distributed knowledge models, we would like to link the concepts of the models, just as is we link documents in the World Wide Web. Fortunately the Simple Knowledge Organisation System (SKOS) offers mapping properties that can be used to define relationships between concepts from different knowledge models.

E.g. when we want to say that concept “Phantastax StamiMaxx” in the product line thesaurus refers to the same real world entity as concept “Phantastax i3000 StamiMaxx S” in the Quality Assurance thesaurus, then we can use skos:exactMatch to express that. If we want to express that the concepts are merly similar, skos:closeMatch could be used.

The other SKOS mapping properties express a hierarchical (narrowMatch, broadMatch) or an associative (relatedMatch) mapping relation between concepts from different concept schemes. With those we can say that my Samsung Galaxy concept has a skos:broadMatch “Smartphone” in the product line vocabulary and a skos:relatedMatch “ACME Corporation” in a controlled vocabulary about Tech companies.

Modularisation of knowledge models

In this way SKOS thesaurus management systems like PoolParty make it possible to modularise knowledge models, represent concepts in their different contexts and consequently enable collaborative work on those models: The marketing guy can work on his model with the concept properties focused on sales without disrupting the work of the quality assurance expert on her own thesaurus. Later one or both of them can create the skos:exactMatch link between the concepts that are the same, like seen in the “Exact Matching Concepts” box in screenshot of PoolParty below.

Enrich your knowledge: Get connected with the LOD Cloud

Going a step further the models could be connected to external knowledge, e.g. a source from the Linked Open Data (LOD) Cloud. Once we establish links to LOD hubs like DBpedia, we can import additional information for their concepts or use it to establish whether similar concepts from different models really refer to the same real world resource.

The survey results also show considerable variation by sector, both of policy and technology implementation. With respect to technologies, ICT companies are also the most willing to consider semantic approaches. The ICT sector has an unusually high interest in all ST components, with 20% or more being willing to consider all of them, and over half of IT respondents looking at Web 2.0 (social computing). [...]  The use of tagging technologies – which overall is the least mature approach in the survey – is most advanced in Life Sciences. The Life Sciences, Media & Entertainment, and ICT sectors all have a reasonably strong interest in Natural Language Processing (roughly 25% on average). Ontologies and RDF/OWL are the technologies least often considered, though the interest in these Semantic Technologies is not insignificant. Taxonomies are slightly more popular, perhaps indicating that companies are taking the first step to prepare for a more semantic approach to IT solutions. The ICT, Energy & Utilities, and Media & Entertainment sectors all have a reasonably strong interest in using taxonomies.

The 190 pages report gives an actual overview of the status quo on European Semantic Technology Market and is now available for download: Final demand driven mapping Report

Started in 2005 the Semantic Technology Conference has become one of the international community hot spots for the commercial application of and trend scouting in semantic technologies. Tassilo Pellegrini talked to the organizer Eric A. Franzon, VP of Wilshire Conferences and Semantic Universe, about what to expect from the upcoming event and how semantic technologies are becoming mainstream.

From June 21 – 25, 2010 the annual Semantic Technology conference will take place for the 6th time. Looking back: what has changed over time? What are the hot topics at this year’s conference?

We launched SemTech in 2005 in San Francisco.  It was a good turnout for a new event, with around 300 attendees.  By 2009, that number had grown to 1100, so audience size has been a significant change, certainly.  However, our interest all along was to grow an industry as well as an event, and I have absolutely seen that growth and maturation.  Ours was the first conference devoted to the commercialization of Semantic Technologies, and at that first conference, there was a predominant academic presence.  That’s not a bad thing – this, like so many technical industries, came out of academia.  Nonetheless, it’s nice to see that by 2010, there is significant adoption by businesses and organizations. I actually feel comfortable saying that Semantic Technologies are becoming mainstream; certainly not ubiquitous, but widely adopted.

The hot topics at the 2010 conference include exciting news in areas we have covered extensively before such as Linked Data, Semantic Search, Healthcare, and Publishing.  But we also are delving much more deeply into new domains that have received a lot of attention recently such as Open Government, Marketing & Advertising, and Social Networks.  There are new standards benchmarks to discuss such as SPARQL 1.1 and the business rules work that is being done with RIF.  Additionally, we are seeing a lot of traction in Semantics in the Enterprise, so SemTech will have quite a bit to offer in that area as well.

While semantic technologies have been around for quite some years now the advent of the Semantic Web added a new spin to the community. What do you expect for the future when it comes to the convergence of semantic technologies and the Semantic Web?

I see Semantic Technologies as a superset of the space that is the Semantic Web.  The Semantic Web is public; the area I call Semantic Technologies includes non-public, closed systems – behind firewalls.  We’ve actually seen this before.  At the same time that the World Wide Web really hit its stride in the mid-1990’s, we saw widespread adoption of portals and corporate intranets.  Even though they did not sit on the public Web, these systems used the technologies of the Web to link documents, enabling organizations to share those documents globally, quickly, and inexpensively.

As the tools become better and we see more use cases in the Semantic Web, I see parallel development of semantically enabled enterprise systems.  In the same way enterprises were using early Web technologies to share documents behind firewalls, they are now using semantic systems to share data globally, quickly, and inexpensively.  At first – and we are seeing this already – in-house systems will consume data from the public Web, essentially mixing public and private data.  This is relatively easy to do when both systems are built on a similar set of technologies, and there are an increasing number of rich data sets for companies to use.  Think of a corporate system that consumes real-time stock data, for example.  The system is not generating that information itself, but it might be using it in a corporate application.

One of the prominent topics at the moment is Linked Data which in connection with Semantic Web might evoke a paradigm shift in data integration issues. How do you experience this trend? How should companies react?

If you think about the ‘traditional’ challenges that enterprises have faced in managing data and meta data — issues like integration, disparate data, unstructured data, governance, legacy systems, and data quality (to name a few) — Semantic Technologies offer solutions.  They’re not always the best solution for every problem, and I don’t expect that RDBMS systems will go away, but there are companies using Semantic Technology today to make money and save money.

From your perspective: what are the most exciting things to look out for in the near future?

There is a great opportunity for tool developers to enter the marketplace. The community is hungry for new tools and for semantic development to be integrated into the tools and development environments they are already using.  Another area that I believe the industry is hungry for is good UI development.  Data is powerful, but its usefulness is often only seen in solid visualizations and reporting.  I expect that more of these tools will emerge in the very near future.

Tools for publishers like OpenCalais, Zemanta, and the rich semantics available in Drupal 7 are making it possible for less-technical people to include semantics in their web pages.

Another area to watch is consumer applications. Tripit, Siri, and Adaptive Blue’s Glue have shown that there is a market for data-driven applications for consumers.

About Eric A. Franzon

Over the last decade, Eric Franzon has served as VP of Wilshire Conferences, where he has been exploring the world of enterprise data. As VP of Semantic Universe, he has worked to raise awareness and explain the usage of Semantic Technologies and Web 3.0 in business and consumer settings.  A lifelong learner and teacher, Eric is frequently called on as a consultant, coach, and trainer around complex technical topics. He is an advisory committee representative with the World Wide Web Consortium and an Affiliate Analyst with Guidewire Group.  Eric has also taught improvisational comedy, early childhood education, blues harmonica, and gender studies.  A Chicago native, he now lives in Los Angeles.

I-Semantics, which started on Wednesday, September 2, and was colocated with I-Know, the International Conference on Knowledge Management, for the third time now, attracted 450 participants. As inteded by our original idea – bringing the Semantic Web out of the echo chamber – this colocation has proven to be absolutely fertile as the semantic systems community and the knowledge management community really fit well together and complement each other. So we had a rich program consisting of 64 scientific talks (30 I-Semantics / 34 I-Know), a poster session, an industry track and numerous mini tracks and discussion panels. Read a review of the first, second and third conference day on Harald Sack’s blog (with whom I enjoyed pondering about Net Neutrality and IPV6.)

For the first time we had the Pragmatic Web Community on board, which held a special track bringing in lots of new ideas and views on computational semantics. Beside that I recognized that in this track we had quite large amount of people from the social sciences and humanities among the audience, which is a promising signal and hopefully leads to new research and human-oriented technologies.

Another highlight was this year’s matchmaking event which aims at initiating business contacts between industry and academia. According to the organizers the Styrian Research Agency and the Enterprise Europe Network,  120 bilateral meetings took place. Astonishingly 56 of the 71 registered participants had a company background.

And finally we hosted the second Triplification Challenge where Chris Bizer gave a keynote and introduced quite a bunch of people to the idea of Linked Data. Unfortunatelly Michael Hausenblas who chaired this year’s challenge could not attend so I did the moderation during the award ceremony and Chris assisited me handing over the awards to the winners. For the results of the challenge go to Soeren Auer’s blog.

Wrapping up, all this would not have been possible without the great support of Prof. Klaus Tochtermann and his team from Know Center. Year after year they do a great job and it is a great opportunity and pleasure to work together with them. Big thanks also go to Adrian Paschke from Corporate Semantic Web of Free University of Berlin, Hans Weigand from Tilburg University and the guys from Salzburg New Media Lab, who helped to set up the I-Semantics conference this year.

The next I-Semantics will take place from September 1 – 3, 2010. Hope to see you next year in Graz!

My basic idea was very simple. When you read about the Semantic Web you are confronted right away with connections to creating knowledge and knowledge management. But in my understanding the Semantic Web is a technical thing and knowledge management is primarily a cultural and organisational thing. So the research questions for my thesis where:

• What relevance do knowledge management and semantic technologies have in the daily work of people working in knowledge intensive domains?
• Which possibilities lie in the adoption of knowledge management and semantic technologies?
• Are semantic technologies already fit for practical use?

The basis of the empirical part of my thesis are group discussions held in different organisations. As a result I developed starting points for an understanding of the topics “Knowledge Management” and “Semantic Web” and their relevance in organisations. The empirical results, in short, provide the following answers to the research questions:

• The “theoretical relevance” of both topics is high, the “practical relevance” on the other hand is rather low. Neither do structured concepts for knowledge management exist in the studied organisations, nor are there attempts at using semantic technologies
• Most of the participants have not heard of the “semantic web” prior to the discussions. After having been introduced to the topic, the relevance of the semantic web and of semantic technologies is rated high
• Possibilities are seen in a better management of information or knowledge in organisations and, especially for semantic technologies, in the improvement of search functionality’s and search results
• Semantic technologies are not yet seen as fit for practical use
• The connection between knowledge management and semantic web is taken as a fact without giving any justification for it.

In my conclusion I tried to match my results with the results of the Semantic Web Barometer 2009 and it was very interesting for me, that there were several similarities. I also found that talking to the people that have to work with technologies that are developed for them can be quite interesting and that group discussion are a great way to do that.

I wrote most parts of my diploma thesis in a wiki (and the rest is available as PDF) so you can find it on my wiki.

Your comments and annotations are very welcome!

Thanks for reading as far as this, Helmut

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Each of those services follow a slightly different approach, but in a nutshell: They all offer an API to provide “similarity search” around social media or also to enhance enterprise information management.

Like a magic bullet those services offer a relief from information overflow and seem to become kind of a “semantic web killer application“.

If you´re familiar with one or many of those services, drop a comment and let us know, what you´ve been experienced so far, or also if you can think of any applications or further developments you would like to see around these kind of services.

If you are not familiar with this stuff, for a quick demo go to

• Zemanta´s Demo zone,
• Calais Viewer or see the
• textwise widget below.

The widget uses text from this blog to calculate similar stuff from the web.

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• semantic technology conference 2009 (web2express.org)
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Luckily, times have come, where semantic search techniques have found their way to enhance knowledge providing theme portals. Nearly once a week a new knowledge portal with built-in semantic search pops up. They deal with environmental issues, health care, economy etc. These sites are good examples how the vision of a knowledge web is fostered by semantic technologies. Such focused approaches are great showcases for “a” semantic web (even if they are not based on “the” RDF semantic web) in the next few months besides general knowledge portals like Wolfram Alpha.

But the potential of these semantic theme portals is often reduced essentially by their bad usability. You get lost in categories and flags – you get puzzled by pulldowns, mouseovers and embedded hierachies – it’s sometimes a mess out off 1001 functions. You need to understand the underpinning semantic concept to get oriented within these applications – and this is not the goal of the exercise. Search has to be easy.

To show the potential of semantic technologies, we need good examples, which offer good usability. This is a call to everyone to provide such examples.

See my favorites:

• NextBio, a platform that enables life science researchers to search, discover, and share knowledge locked within public and proprietary data
• reegle, the Search Engine for Renewable Energy and Energy Efficiency
• CultureSampo, a Finnish cultural heritage platform for institutional organizations as well as private citizens

Sebastian Schaffert and his team demonstrated the latest version of this semantic based framework based on wiki principles and built on JBoss Seam.
You can take a look at the online showcase and download the one click installer of the pre-release.
Sebastian emphasised that KiWi will follow Linus Torvald’s maxim of releasing early and releasing often.
In June 2009 KiWi 1.0 should be ready, followed by 1.5 in December 2009, at which time Enabling Technologies and a first implementation of the uses cases will be included in the system.

After hearing talks about the KiWi User experience, data model and transaction management, we learned about the status of reasoning, querying, information extraction and personalisation of the Enabling Technologies groups (online slides forthcoming here).

Peter Reiser presented the Sun use case, in which the focus now is on realising an expert finder mechanism based on the “Community Equity” concept found in Sun Spaces (their highly popular, heavily customized version of Confluence).

In short Community Equity is a system for analysing the social activities in a community and measuring the value of the contributions to the community. Social activities are anything from creating content to simply viewing it. These activities are used to calculate the Community Equity (which is simply a number) of content, tags and people.
Consider this example for a content page: The more people view, download, reuse, comment on or rated the page positively, the higher the page’s Information Equity will be.
In turn the community members acquire Contribution Equity through the content items they create, i. e. the Information Equity of a content item “spills over” to its creator.
The same goes for Tag Equity: Each tag obtains the Equity from all the pages it is applied to. E.g. if there are 3 pages with the tag “JBoss” with Information equity of 10, 5 and 20, then the Tag Equity of JBoss is 35.
These things alone is very helpful for motivating people to contribute to the community and for judging the quality of content and ranking it accordingly.

On top of that, the Equity system allows for a expert finder system. People are related to all the tags that are used on the content items they created. Imagine a contributor has created several documents that were tagged with java and the sum of information equity of those pages is 550, then the person also has
That way a search for “Java” doesn’t only bring documents tagged with java, but also people with expertise in Java.
In KiWi this Community Equity system will be implemented and extended. For one, instead of flat tags KiWi will use concepts coming from SKOS thesauri, which will be managed using PoolParty.
These thesauri act as a shared knowledge model. In this way synonyms, parent/child concept relationships, etc. can be considered for Equity calculation, therby taking personalization, querying and expert finding to a whole new level.
Research will engage with questions like how should the Equity disperse through the graph: Imagine a community member with high Equity in “JBoss”. This means she probably has good expertise in Java too. As this subconcept relationship is expressed in the thesaurus, it is possible to transfer Equity from JBoss to Java, but one has to consider what percentage the equity will be transferred, if Equity only can only spread upwards from subconcept to parent concept or whether other kinds of relationships also warrant the transfer of some Equity.

Besides an insight in many aspects of the initiative, the interview provides thoughts on how connected business-models, in providing services, could look like.

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