With the vision of the web of data Topic Maps and the Semantic Web move closer over time. Anywhere URIs represent subjects, structured statements are gathered around them. In this context I see subj3ct.com as an interesting ventures. This recently launched service provides URIs for 15 million subjects to be used in structured data. Naturally, linked data hubs like dbpedia or geonames.org are part of it. The crowd is invited to contribute to this collection, also the Topic Maps Lab provides several feeds to register new URIs. Subj3ct.com turns out to be an infrastructure technology for Web 3.0 applications, regardless whether they are based on Topic Maps or other Semantic Web technologies.

Through this convergence the uniqueness of each technology sharpens. Reasoning is the strong point of the Semantic Web. But the strength of Topic Maps are semantic portals and the global federation of facts around subjects. Bringing together all and even contradictory information about each subject – and not building reasoning-ready consistent models of the world – is built into the genes of Topic Maps.

Read the full interview here.

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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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

Markus Luczak-Rösch and his team from FU Berlin have published loomp, a WYSIWYG annotation tool especially designed for inhouse use. loomp is aiming at the Corporate Semantic Web market, providing a semantic application with low entry barriers and high usability designed for non-techies.

When asked about the concrete application area Markus says:

We have found various use cases especially in knowledge and content intense domains. The most interesting one is the journalists use case. Consider journalists which research and write articles and editors which revise and publish the work of journalists.

Journalists research specific topics on demand and access various information sources for this purpose, e.g. websites, books, related articles, and human informants. Only few journalists use digital devices for this task and even fewer apply information management systems. To transfer the finished article to the responsible editor at the publishing house the people use free text documents and email communication. Finally, an editor revises and releases the articles for his department. loomp can help journalists to manage their notes, interview logs, references, addresses, etc. loomp helps to link an article to its information sources.

Read the full interview here.

As journalist and communications-professional I came acoss an article that I – although in German – have to recommend from the depth of my heart to everybody who is somehow concerned with communication. It´s an article on propaganda in the prestigious brandeins-magazine. Here´s a german commentary on it.

Communications and public relations are at least as complex as the Semantic Web is and it´s not accidental that both of them deal with language. Ludwig Wittgenstein had claimed comprehension by talking about truth tables and anybody who deals with communication should act more explicit in terms of getting more understanding.

Corporate Semantic Web addresses both the consumer and the produce side, where consumers and producers might be humans as well as automated services, e.g. in business processes and enterprise service networks. This also includes the adequate engineering, modelling, negotiation and controlling of the use of the (meta)data and meaning representations in a (collaborating) community of users or services in enterprise settings where the individual meanings as elements of the internal cognitive structures of the members become attuned to each others’ view in a communicative process. This allows dealing with issues like ambiguity of information and semantic choices, relevance of information, information overload, information hiding and strategic information selection, as well as positive and negative consequences of actions (e.g. in a decision making process).

But, CSW does not only address the technological aspect but also the pragmatic aspect of actually using Semantic Web technologies in enterprises, which includes learning and training aspects as well as economical considerations. Incentives need to be provided to encourage in-house adoption and integration of these new Corporate Semantic Web technologies into the existing IT infrastructures, services and business processes. Decision makers on the operation, tactical and strategic IT management level need to understand the impact of this new technological approach and its adoption costs and return on investment. Therefore, companies will have in mind the economical justifiability of the deployment of new technologies.

I think he addresses some really crucial aspects of this emerging application field. Read the full interview here.

Corporate Semantic Web will also be a major topic at this year’s I-Semantics Conference from Sept. 2 – 4, 2009 in Graz/Austria. Also check out the forthcoming Semantic Web Meetup in Berlin on March 20, 2009, which is organized by Adrian Paschke’s team and the Semantic Web Company.

People unable to attend physically, Christoph wrote, might consider participating in the Semantic Wiki Mini-Series Launch Event via ONTOLOG (= Open, International, Virtual Community of Practice on Ontology, Ontological Engineering and Semantic Technology), to take place online on Thursday, October 23, 2008, 10:30 AM PDT / 1:30 PM EDT / 7:30pm CEST / 17:30 UTC (click here for more details, time zones, registration procedures for first-time participants).

Here are some of the topics that have already been put on the wish-list for the Semantic Wiki Mini-Series (source):

• usability vs expressivity
• community building
• uncovering more implementations
• HCI: navigation of large, high-dimensional knowledge spaces
• e-science (especially pharma research & biomedicine)
• semantic wikis and mashups
• recommendation and personalization in semantic wikis,
• knowledge representation (expresivity vs. simplicity)
• how to make business subject matter experts able to enter, review and validate
  meaningful information without them having to learn new words
• what dialect of OWL supported
• integration of semantic resources (Protege / OOR / MW / …)
• content quality
• integration of external data
• a semantic wiki & OOR session
• experiences with distributed collaboration
• server-side infrastructure to support semantic wikis
• survey of semantic wikis for vertical domains (e.g. HCLS)
• integration with other tools / linking wiki content to other apps

If you ask me, there are more than enough topics not for a mini, but for a grand series of conferences on Semantic Wikis:) For updates, bookmark the homepage of the series.

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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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Alison Adam analyzed the well-known ontology CYC that was build to capture common sense knowledge from the 1980ies on. Her criticism focussed on the built-in assumption that we would all share a consensus reality: “be it a professor, a waitress, a six-year old child, or even a lawyer” (Lenat and Guha 1990). She revealed that the knowing subject implicitly assumed by the system is a white, middle-class male professional.

Hence, in contrast to its own agenda CYC ignores minority views, quieter voices, and allows the dominant voice to speak for everyone, which seems highly problematic. Other studies give more evidence for the highly problematic prerequisite of computer science modelling that rests on the Cartesian epistemology. Even the modelling concepts themselves should be questioned as Cecile Crutzen suggest, since e.g. the class concept and the inheritance concept lack to represent social processes, because of limited formal expressiveness for conflict, change and fluidity. Such an ontology abstracts from human sociality, situated action and real meaning construction processes.

This also made me think about my own role within and attachment to the Semantic Web Community – from a professional point of view, I see myself as a sort of mouthpiece for the Semantic Web (at least within the professional community that I am a part of), and while I am convinced that the movement is going to see its big break within the next five years, I don’t see myself as playing a significant role in it. And I’m always inclined to leave all the ‘hard stuff’, i.e. all the technology-related questions to the ‘boys’ in our team.

But one of the good things about the Semantic web is that it is actually EASY to understand – I’ve also been told by Henry Story for instance that N3 (Notation3, a shorthand non-XML serialization of Resource Description Framework models) is relatively easy to learn; and since I am one of the few women I know (sadly) who actually know what an ontology is, maybe it would be about time that I learned to model one myself.

Because we cannot expect that white, middle-class male professionals are going to be able to explore the feminine or queer knowledge in this world and mold it into a common knowledge base. Even if marginalized voiced can hardly expect that the hegemony is going to advocate their cause: The Semantic Web project itself is at stake if some voices, views and knowledge are excluded. This could indeed be a showstopper for the Semantic Web – not immediately on a technology level, but with regard to meeting the societal goals of its own agenda.

Read the entire interview with Corinna Bath here.

Alison Adam’s cited work is contained in: Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project (D.B. Lenat and R.V. Guha 1990).

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A Prototype Knowledge Base for the Life Sciences
W3C Interest Group Note 4 June 2008
Editors: M. Scott Marshall, Eric Prud’hommeaux
Contributors: Alan Ruttenberg, Jonathan Rees, Susie Stephens, Matthias Samwald, Kei-Hoi Cheung
Abstract: The prototype we describe is a biomedical knowledge base, constructed for a demonstration at Banff WWW2007 , that integrates 15 distinct data sources using currently available Semantic Web technologies such as the W3C standard Web Ontology Language [RDF]. This report outlines which resources were integrated, how the knowledge base was constructed using free and open source triple store technology, how it can be queried using the W3C Recommended RDF query language SPARQL [SPARQL], and what resources and inferences are involved in answering complex queries. While the utility of the knowledge base is illustrated by identifying a set of genes involved in Alzheimer’s Disease, the approach described here can be applied to any use case that integrates data from multiple domains.

Experiences with the conversion of SenseLab databases to RDF/OWL
W3C Interest Group Note 4 June 2008
Editors: Matthias Samwald, Kei-Hoi Cheung
Contributors: Alan Ruttenberg, Huajun Chen
Abstract: One of the challenges facing Semantic Web for Health Care and Life Sciences is that of converting relational databases into Semantic Web format. The issues and the steps involved in such a conversion have not been well documented. To this end, we have created this document to describe the process of converting SenseLab databases into OWL. SenseLab is a collection of relational (Oracle) databases for neuroscientific research. The conversion of these databases into RDF/OWL format is an important step towards realizing the benefits of Semantic Web in integrative neuroscience research. This document describes how we represented some of the SenseLab databases in Resource Description Framework (RDF) and Web Ontology Language (OWL), and discusses the advantages and disadvantages of these representations. Our OWL representation is based on the reuse and extension of existing standard OWL ontologies developed in the biomedical ontology communities. The purpose of this document is to share our implementation experience with the community.