Jana Herwig

Knowledge Management for Project Management: from unstructured to structured information

KiWi – Knowledge in a Wiki session, pt. 2: This afternoon, we turned to the Logica use case, which is dedicated to the development and optimization of KiWi as a knowledge management tool specifically tailored to the needs of project management.

Regarding the use case requirements: As Daniel Grolin, a process expert and business architect at Logica (formerly WM Data), pointed out, what is most required at the moment is an application for designing processes, i.e. for designing the ways that people do things. This can be a painful process, in particular if one group of people (consisting of process designers) thinks about the ways that another group of people (e.g. the project managers) are going to do certain things – a collaborative approach should be able to

1) alleviate this challenge
2) generate commitment among the involved parties.

The primary users will be on the one hand the process engineers, and on the other hand the project managers who are the recipients and users of these processes.

In his presentation, Daniel Grolin chose one of four scenarios in which KiWi would ideally be employed: the risk analysis process – which is a vital process for Logica, as the outcomes of this analysis influence the decision whether or not a project will be accepted. From an architectural point of view, KiWi is going to mediate between the process guidance column – which consists of process and workflow features – and the final work product, i.e the result of a process, in this case the report of the risk analysis.

In practice this means that if, for instance, a user has selected the risk analysis process, the Kiwi core system and enabling technologies will provide concepts related to risk analysis, supporting the user in the tagging process. Wiki technology is already being used in the industry, said Daniel, but what is lacking at the moment is the integration of structure, and this is also where he sees the potential of KiWi as a knowledge management tool, and as a means to move easily from unstructured to structured information (by the way, if you are interested in using wikis in the enterprise, I also recommend this article: Wikis for Knowledge Engineering, and in Global Businesses).

Karsten Jahn

Karsten Jahn (Aalborg University) then gave us a preview of a possible user interface (i.e. not of the screen design, but the functionalities) which seeks to address one particular problem: Many companies use many different, sophisticated tools which operate fine on their own, but are not integrated (i.e. there is no communication or exchange of data between them). With KiWi, the aim is to develop a tool that is going to be able to cover all features and processes currently being taken care of by individual tools, to allow for an optimum of data integration.

To conclude, Rolf Sint (Salzburg Research) showed us screens of the current configuration of KiWi for Logica’s needs – the example below is related to the risk analysis process outlined by Daniel Grolin above.

Logica Kiwi Wiki

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Tassilo Pellegrini

Is OpenCalais becoming a Search Engine?

Open Calais Logo

From the very beginning I was wondering, what Reuters is going to do with all that data generated by OpenCalais. So I took a moment and browsed through the Privacy Statement (formerly their Terms Of Use), stepping over an enlightning paragraph:

We may build a search capability in the future. This capability would allow users to search the metadata repository and receive back a list of entries that match that search criteria. Unless you have authorized it via an API parameter, this list would not include the original metadata contained in the document but would expose the URL and description of the original document if you have provided it to us. If you do not want your content included in the search functionality you should indicate so in the appropriate area of the API. If you want to maximize the exposure of your content on the web you should not opt out of inclusion in the search functionality.

Hypothetical in wording this paragraph states it very clear: engagement in the search market is definitely an option. But they even go one step further.

We may build a syndication capability in the future. This capability would allow us to generate feeds of content that match certain selection criteria based on the metadata. As with search, unless you have authorized it via an API parameter, these feeds will not expose the original metadata contained in the document but would expose the URL and description of the original document if you have provided it to us. If you do not want your content included in the syndication functionality you should indicate so in the appropriate area of the API. If you want to maximize the exposure of your content on the web you should not opt out of inclusion in the syndication functionality.

This sounds to me like content reselling business. In this regard it might be interesting to take a look at the latest developments from IPTC: a policy standard called ACAP, which stands for Automated Content Access Protocol. Its designed to express access policies for robots on content items. Coupling ACAP with (hypothetical) search capabilities of OpenCalais could result in a major commercial distribution engine especially for traditional media content owners. Especially with the following marketing capabilities in mind:

We may build other products in the future based on statistical or other analysis of the metadata, such as trend analysis, emerging topics or others. In no case will these products expose the original document’s metadata.

Finally a business model for the Semantic Web? Whatever … smart guys, great service!

Tassilo Pellegrini

Is Reuters unleashing the Semantic Web?

Open Calais LogoOpen Calais – a new and smart API from Reuters – finally does what critics say to be the greatest obstacle to the Semantic Web: Taking the metadata burden from the enduser by providing an automatic meta-tagging tool. The principle behind Open Calais is easy: Put in some unstructured text and get in return nicely structured RDF-data. Backed by powerful Text Mining and machine learning techniques the API automatically detects entities like persons, events, countries and other facts.

Open Calais takes account of the fact that the added value of content is hidden in its structure. Uncovering that structure and representing it in a interoperable format makes existing ressources more programmable and reusable.

But what is in for Reuters? Nothing less than the biggest structured content repository on the web. Should not we talk about this little fact aswell?

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