Semantic Technologies & Knowledge Management

Semantic Conference in March in San Francisco

2005-01-18T10:17:00.000-08:00

http://www.semantic-conference.com/

It does appear like the momentum is picking up. The brochure says the market for "semantic technologies" will be $63 Billion by year 2010. I haven't any idea what that means, I wish they could tell me where exactly the market is so that I can cash out.

"Semantics" has always been hot, so there isn't much new there. There will certainly be some progress in both exiplicit representation of semantics (using RDF/OWL/Rules) and derivation of semantics (from raw data) over the next decade, but there won't be miracles. VCs, use caution and tread carefully!

So, is it 2005? or 2050?

2005-01-05T15:40:00.000-08:00

Year 2004 generated considerable buzz/hype about the Semantic Web, but not much changed really. So, when is the liftoff? 2005 or 2050? Or is it going to be a slow toiling towards much more modest goals?

Well, may be the web is already "semantic" enough? What do we call what Google does? Or possibly futuristic web search engines like clusty.com? Except that they don't work on explicit semantic representations, which is their strength.

I don't expect much exciting news from the Semantic Web world in 2005 either, but I would be ecstatic to welcome any.

Semantic Web: The Next Wave? (contd)

2004-01-11T23:16:00.000-08:00

[previous post] I came across an interesting debate on Semantic Web, sparked by Clay Shirky's article, The Semantic Web, Syllogism, and Worldview, which generated many responses (Bb, Ayers, Bray, Ford). I like the last one from Paul Ford, not only because he writes well, but also because he has done some very interesting things with Semantic Web ideas.

Paul has several interesting articles that are worth reading on his web site, especially the 'Google takes it all' article. He designed and built Harper's Magazine website using the Semantic Web technologies with "3,000 facts, 6,000 events, 12,000 links, 500 topics, and over 939 separate HTML pages. 300,000 words." That's the first of a kind I have seen so far, and if nothing else, it gives us a glimpse of what is possible.

Shirky makes some important points, but misses many. I don't think the majority of the Semantic Web community believes in a single world view (global ontology) as suggested by him, and it is not necessarily a requirement for the success of Semantic Web. As I opined earlier, many interesting applications will evolve in specific contexts (mini / micro worldviews) rather than in the global context (one worldview). (more on the subject)

Topic Maps - What are they good for?

2004-01-02T11:49:00.000-08:00

Topic maps are inherently designed for back-of-the-book indexes and have been extended to encompass other kinds such as glossaries, thesauri and cross references. But, they are too general to limit their use to their initial intended purposes. They can be used to encode arbitrarily complex knowledge structures and link them to information assets, which brings up the debate - which of the two, topic maps and RDF/OWL better for a given task?

There are many informative articles (1, 2, 3) that discuss the differences between these two standards and how they can interoperate or even integrate. Most of the demonstrated applications of topic maps fall in the back-of-book indexing world for informational navigation (e.g., IRS Tax Map), and topic maps are a more natural choice for such applications. I wonder if one can build a good enough ontology in OWL to provide similar semantics for IRS Tax Map kind of applications - I haven't tried. Topics maps have no formal theory and don't guarantee computational completeness and decidability, which means one can shoot one's foot easily overusing topic maps for general knowledge representation.

I certainly wish there were only one set of standards, in stead of many, especially if the same purposes can be achieved with a minimal set of standards. Oh well, there is no ideal world.

Mine and Navigate Unstructured Information

2003-12-29T16:46:00.000-08:00

I think the stage is set for the technologies that help navigate and manage unstructured information in corporations. Many vendors sell products now including Autonomy, ClearForest, InXight, Stratify, SAS, Entrieva, Verity, and Vivisimo. Typical capabilities offered by these products include automatic classification, summarization, taxonomy generation, clustering and concept-based information retrieval. Eventually I think the core technologies themselves will get commoditized (even free and open source) though there will always be premier products.

The real challenge will be to roll out solutions based on these technologies, often combined with other systems such as business process management and collaboration systems, that address specific problems. For example, large engineering organizations can insert these capabilities in their PLM and benefit significantly. Or PLM vendors can integrate them in their products. For hiring managers, wouldn't they be happy to see a neat classification of resumes, preferrably ranked aginst job openings, in stead of requiring them to go through and manually classify them? Vivisimo already does a decent job of categorizing web search results obtained from multiple search engines - not good enough to be my default search engine, but do find it useful often.

The next level of technologies using metadata, topic maps, ontologies and such will take a bit longer considering the need for better planning and higher level of effort. Tools should help us adapt them faster (e.g., automatic metadata generation, automatic topic creation for topic maps, etc).

The Nonsense of Knowledge Management

2003-12-27T11:54:00.000-08:00

I recently came across the article, "The nonsense of knowledge management", which I both agree and disagree with. According to the author, what is today pushed as KM by the consulting companies and IT vendors is really information management. I mostly agree with that. A system that automatically categorizes documents and provides intuitive navigational schemes is more of an information system than a knowledge management system.

However, in the continuum of data, information, knowledge and wisdom, the boundaries are vague. If a star sales person with 30 years of experience tells a junior sales person, "if you propose this kind of a deal to a customer with such a cultural background, you are 95% likely to fail," is it a piece of information or a nugget of knowledge?

The author asserts that the tacit knowledge resides between two ears and cannot be shared. And that the knowledge can never be managed. That's a candidate for debate. I thought one of the purposes of organizational learning systems is to facilitate explication of tacit knowledge. And whatever happened to all those knowledge-based decision support systems - where does all that knowledge come from, if the tacit knowledge never becomes explicit? I am not a knowledge theorist, so I am unable to appreciate a purist's opinion.

I tend to use 'information management' and 'knowledge management' interchangeably, and as long as it serves the purpose, I am okay with such use. However, academicians do need to make finer distinctions.

References:

Wilson, T.D. (2002) "The nonsense of 'knowledge management'" Information Research, 8(1), paper no. 144.

Knowledge Management Capability Model?

2003-12-26T23:28:00.000-08:00

It is interesting that there is no "standard" capability model to measure how well an organization is doing its KM. The Capability Maturity Model (CMM) from Carnegie Mellon has become a de facto capability model for software engineering. Now, Carnegie Mellon is developing another model called eSourcing Capability Model (eSCM) for sourcing of services (IT and other business processes). May be it time for a KMCM. Actually, eSCM does have KM as one of its 5 dimensions of capabilities, but in the specific context of outsourced services delivery and management.

As suspected, I found, from my search, at least a couple who thought about it. Authors of this paper say, "Many KM approaches and tools exist, many claims are made, but what constitutes the essential core set of capabilities that truly represent KM proficiency? No industry-accepted model exists to assess the maturity of an organization’s KM program." And, in this paper, the authors propose a conceptual framework for such a capability model.

Semantic Integration Hope

2003-12-25T23:21:00.000-08:00

Semantic Integration could be the next big thing, if it can successfully integrate disparate applications and data sources easier as it promises to. It deals with how the meaning is changed when information is transferred from one application in one context, to another application in a different context. The basic idea behind Semantic Integration is rather simple - a domain ontology will act as a vehicle for integration by leveling out the semantic differences between different contexts. The technique involves building of a domain ontology and mapping various data sources and applications to the domain ontology. This is obviously superior to mappnig every application to every other application which results in n x n mappings. Adding another application is trivial if things are semantically integrated, as now all we need to do is a mapping between the new application and the domain ontology.

The main problem is to come up with a domain ontology that is complete enough and can be mapped to individual application concepts, which is not an easy task. There are other alternative achitectures possible, and some are discussed in this paper. So far, I have not seen any large scale Semantic Integration efforts (except in research), my hope is that Santa will bring us some by next Christmas.

Some References:

Proceedings of the Semantic Integration Workshop, Florida, 2003.
Proceedings of the ECAI-02 Workshop on Ontologies and Semantic Interoperability, France, 2002.
Semantic Integration: Strategies & Tools. TopQuadrant Technology Briefing, 2003.
Using Ontologies for Data and Semantic Integration, Monica Crubezy, Stanford Medical Informatics, Stanford University, November 2003.
Creating Semantically Integrated Communities on the World Wide Web, Michael Uschold and Michael Gruninger, Semantic Web Workshop, 2002.
Interoperability Standards in the Semantic Web, Steven Ray, NIST, Journal of Computing and Information Science in Engineering, March 2002.
Semantic Integration Sample from Intellidimension - describes a simple example of how Semantic Integration works.

Knowledge Management: Thinking Simple

2003-12-23T12:35:00.000-08:00

KM is about managing knowledge - it is that simple. For a business, the purpose of KM, as a business tool, is to fulfill business objectives (e.g, higher profits) - that too is simple. When properly implemented, KM can help a business innovate faster, boost employee productivity, adapt to changes quicker, target customers and their needs more accurately, among a zillion other things - leading to better sustainability and higher profits.

What does "implementing KM" mean? Is it a complex undertaking? In simple terms, "implementing KM" means employing proper processes and tools to: (1) catpure what you know; (2) organize, systematize, classify and categorize knowledge; (3) make relevant knowledge available to the right people and the right time in the right form to enable better actions; (4) evolve knowledge base as the organization and its people learn new things; and (5) empower people with knowledge by (just-in-time) training, coaching and self-learning, improving their productivity.

Every organization already "implements KM" to some extent - it is neither new nor complex (at least it doesn't have to be). If you are labelling engineering drawings and storing them, you are already doing KM. If you are organizing customer records by their profiles, that's KM. However, you can do KM better, even a lot better, by developing a proper approach, especially with the use of wide variety of technologies available today.

Like everything else, a KM implementation has a goal, and a more tangible goal is better than an intangible one. An implementation of KM in specific contexts with specific goals has better chances of delivering measurable results. It should also be remembered that the technology doesn't do KM, it helps us do KM better, sometimes in the ways never possible before.

A typical KM implementation framework involves several steps - establishment of business goals, context analysis, knowledge mapping, gap analysis, development of a KM architecture (processes and tools), implementation, deployment, measurement, refinement, and so on. Without following such a framework, just throwing a set of IT tools for KM will most likely not yield expected benefits. A "framework" may sound complex, but it is nothing more than formalized common sense.

There are various levels of capabilities one can introduce in an organization to fill the gaps identified, ranging from very simple (minor process changes and easy technology implementations) to very complex (major process changes and difficult technology implementations). Simple capabilities are often enough to fill significant gaps, they should be introduced first, and more complex capabilities should be introduced gradually.

Some References:

The Knowledge Management Toolkit: Orchestrating IT, Strategy, and Knowledge Platforms (2nd Edition) by Amrit Tiwana.
Interpreting Knowledge Management, The OR Society.

Semantic Web: The Next Wave?

2003-12-21T18:28:00.000-08:00

According to Tim Berners-Lee, the inventor of the dumb Web as we know it today, "The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation." link

There is much work being done, led by W3C, to define necessary standards and methods to realize the dream of Semantic Web. Unlike the current dumb Web, Semantic Web promises to deliver meaning ("semantics") along with the content as we download it.

I find it exciting, but am skeptical of all its glory promises. It sounds like AI of the past decades, promising, but no one knows where it is heading. A demonstration of small successes in limited contexts here and there lifts our hopes to the skies, only to get beaten down by the reality. There are hopes that the "network effects" will enable the Semantic Web proliferate, just like the dumb Web did in the past decade. Unless there is an agreement on the semantics, either predetermined or evolving, across the network, I don't see the network effects affecting anything. Luckily for the dumb Web, everyone readily agreed on its dumbness and embraced it quickly.

The dumb web accomplished trivial things, but offered greatest value. The semantic web is trying to acccomplish the hardest things, and the value it offers is not as great to ordinary beings. There the problem really lies - the 80/20 rule - 80% of the benefit came from the first 20% of efforts on the dumb Web, and now we will be trying to squeeze that additional 20% benefit with the remaining 80% effort. So, I expect the players to embrace it much more slowly than they did the dumb Web, which in turn will diminish the network effects. And, many just won't care for that additional 20% benefit.

That said, while I don't see wide ranging success of Semantic Web in the broadest terms in the near term, I do think many interesting applications will evolve in specific contexts. For example, comparative shopping could be a cake walk, if all vendors marked up their e-commerce sites with standardized ontologies and metadata (presumably using OWL and/or RDF). Similarly, news articles can be marked up with meaningful metadata to enable easy classification and categorization. The standardization of metadata and ontologies in specific domains and contexts could lead to very useful and interesting applications.

I also think the intra- and extranets of corporations can get very smart by offering targeted search, navigational and personanization capabilities. It is easier for a corporation to standardize on ontologies, controlled vocabularies, thesauri, and metadata to enable consistent markup of documents and to develop and deploy capabilities that use them.

I think Semantic Web technologies will complement other KM technologies (text mining, classification, taxonomies, topic maps, etc) very well in the corporate world.

Getting Started...

2003-12-21T13:19:00.000-08:00

A place to share and record my thoughts on things related to semantic technologies and knowledge management - semantic web, RDF, OWL, DAML, meta data, ontologies, semantic integration, text mining, classification, taxnomies, controlled vocabularies, first-order, horn and description logics, semantic technology tools, possible applications in wide variety of contexts, hype, myths, realities, and everything else.

Knowledge Management (KM), especially in the context of engineering knowledge, has been one of my fascinations for a while now. My doctoral dissertation addressed the KM issues, along with process collaboration issues, in the context of large, multi-disciplinary engineering organizations. Things have gotten even more complex now with the growth of extended enterprises and global value chains through out which the knowledge is spread. We have come a long way in terms of technological advancements over the last decade that can benefit KM. Recent advances in collaboration tools, intra- and extranets, document management systems, data and text mining, taxonomy and categorization algorithms, NLP, ontologies and Semantic Web are a few advances that are noteworthy.

This blog will try to capture any thoughts that cross my mind that relate to Semantic Web and KM. Please feel free to email me your comments.