Danny Ayers posted the link to The ultimate mashup — Web services and the semantic Web, Part 1: Use and combine Web services over at IBM’s developerWorks. I am allready curious about the other 5 parts of this tutorial series: In Part 6, the fun increases. At this point, you have a working application and the framework in place so that the system can use semantic reasoning to understand the services at its disposal. In this part, you give the user control, enabling him or her to map new services into the ontology and to pick and choose the data that is used for a custom mashup.

Recently I read about Semantic Radar over at Frédérick Giasson’s weblog. Semantic Radar is a plug-in for Firefox, notifying the user if it finds SIOC, FOAF or DOAP data referenced by the page he or she is currently viewing. When such data is detected a little icon will appear on the bottom right side of you browser, which lets you access the embedded data easily. I really like this little helper!

I previously blogged about a very comprehensive survey-paper on semantic annotation. Besides the survey the paper also lists seven requirements for semantic annotation systems in the context of a document centred knowledge management approach and reviews them in the light of the annotation tools surveyed. Here are the seven requirements from Uren et al. (2006):

• Requirement 1—standard formats: … Using standard formats is preferred, wherever possible, because the investment in marking up resources is considerable and standardization builds in future proofing because new tools, services, etc., which were not envisaged when the original semantic annotation was performed may be developed. Compliance with standards also frees companies from the constraints of proprietary formats when choosing knowledge management software. It is the activity of the W3C in developing and promoting international standards for the SemanticWeb that has convinced us that this route is worth following in knowledge management. Two types of standard are required, standards for describing ontologies such as the Web Ontology Language OWL and standards for annotations such as the W3C’s RDF annotation schema.
  Many of the reviewed tools already use W3C standards.
• Requirement 2—user centered/collaborative design: … Annotation can potentially become a bottleneck if it is done by knowledge workers with many demands on their time. Since few organizations have the capacity to employ professional annotators, it is crucial to provide knowledge workers with easy to use interfaces that simplify the annotation process and place it in the context of their everyday work. A good approach would be a single point of entry interface, so that the environment in which users annotate documents is integrated with the one in which they create, read, share and edit them. System design also needs to facilitate collaboration between users, which is a key facet of knowledge work with experts from different fields contributing to and reusing intelligent documents. …
  … More attention needs to be paid to build in or plug-in semantic annotation facilities in commonly used packages to encourage knowledge workers to view annotation as part of the authoring process not as an afterthought, and also to supporting annotation in collaborative environments, …
• Requirement 3—ontology support (multiple ontologies and evolution): … annotation tools need to be able to support multiple ontologies. For example, in a medical context, there may be one ontology for general metadata about a patient and other technical ontologies that deal with diagnosis and treatment. … In addition, systems will have to cope with changes made to ontologies over time, such as incorporating new classes or modifying existing ones. In this case, the problem is ensuring consistency between ontologies and annotations with respect to ontology changes. …
  … Ontology maintenance, which directly affects the maintenance of annotations, is poorly supported, or not supported at all, by the current generation of tools. This perhaps reflects the intended user groups; with the assumption being that knowledge workers will use existing ontologies rather than editing or creating them. … A genuinely integrated semantic annotation environment should give the user automatic support for ontology maintenance, for example, using text mining methods to suggest new classes as they emerge in documents and spotting inconsistencies between new and existing annotations. …
• Requirement 4—support of heterogeneous document formats: … Documents will be in many different formats including word processor files, spreadsheets, graphics files and complex mixtures of different formats. This presents a technical challenge rather than a research challenge, but dealing with multiple document formats is a prerequisite for integrating annotation into existing work practices.
• Requirement 5—document evolution (document and annotation consistency): Ontologies change sometimes but some documents change many times. … What should happen to the annotations on a document when it is revised, poses both technical and application specific questions. … Annotation environments need to help knowledge workers maintain appropriate annotations as documents change.
  The survey did not discover any concerted work on these lines.
• Requirement 6—annotation storage options: The Semantic Web model assumes that annotations will be stored separately from the original document, whereas the “word processor” model assumes that comments are stored as an integral part of the document, which can be viewed or not as the reader prefers. …
  … However, separate storage of annotations has advantages for KM. … It also makes it easy to produce different views of a document for users with different roles in an organization or different access rights, thus facilitating knowledge sharing and collaboration. We therefore argue that separate storage is the better model, even when extra overheads are required to maintain links between a document and its annotations.
• Requirement 7—automation: Another aspect of easing the knowledge acquisition bottleneck is the provision of facilities for automatic mark-up of document collections to facilitate the economical annotation of large document collections. To achieve this, the integration of knowledge extraction technologies into the annotation environment is vital. …
  Language technologies present usability challenges when deployed for knowledgeworkers since most are research tools or designed for use by specialists. … In addition to the usability challenges there are also research challenges, among which we have highlighted the extraction of relations as important for semantic annotation.

These are directions for next generation Semantic Web applications (NGSWA) summarized from Language Technologies and the Evolution of the Semantic Web (Motta and Sabou 2006a):

• Decoupling the process of engineering from that of exploiting the Semantic Web. NGSWA assume that they operate in an environment characterized by large scale, distributed semantic markup.
• Operating with heterogeneous semantic markup and multiple ontologies. NGSWA have to deal with heterogeneous semantic markup.
• Openness with respect to semantic resources. NGSWA allow to add new sources or integrate new ontologies
• Scale more important than quality. While a lot of the emphasis in first-generation tools was on quality, NGSWA move away from traditional quality centered expert systems, just as the Web differentiated itself from hypertext, by allowing broken links.
• WWW – We Want Web! Early Semantic Web applications are far more similar to the classic knowledge-based systems, than to the Semantic Web applications of the future. NGSWA try to bring the Semantic Web closer to the Web and also integrate Web Services in their functionalities.
• From intelligent applications to harvesting collective intelligence. In NGSWA intelligence is also a byproduct of operating with large amounts of data. The users act as catalysts in deriving value from collectively gathered, tagged and shared semantic data, thus using the system to harvest collective intelligence.

See also my previous post on Characterizing Semantic Web Applications.

This seems to be the mother of all survey papers on Semantic Annotation. I have never seen an overview on this topic being that complete: Semantic annotation for knowledge management: Requirements and a survey of the state of the art (Uren et al. 2006)

Beside the detailed survey on Semantic Annotation they also present seven requirements for Semantic Annotation in a document centric approach to Knowledge Management.

Enrico Motta from KMI held a talk at the The Fourth Summer School on Ontological Engineering and the Semantic Web (SSSW’06) called Characterizing Semantic Web Applications were he listed several (desired) characteristics of a (typical) Semantic Web application. I wrote him an email regarding his talk and asked if he had any additional resources on this topic. He kindly pointed me to the following two papers written by him and Marta Sabou:

• Language Technologies and the Evolution of the Semantic Web (Motta and Sabou 2006a)
• Next Generation Semantic Web Applications (Motta and Sabou 2006b)

These are the (my) key-points of the second paper (Motta and Sabou 2006b).
Properties of Next generation Semantic Web applications (NGSWA) are:

• Semantic data generation vs reuse. NGSWA are designed to operate with the semantic data that already exist. In other words, they worry less about bootstrapping a Semantic Web, than about providing mechanisms to exploit available semantic markup.

• Single-ontology vs multi-ontology systems. NGSWA can consume any number of ontologies at the same time. It does not make much sense to make a ‘closed domain’ assumption.

• Openness with respect to semantic resources. NGSWA take into account RDF data available from a particular Web site, in response to a request from a user who wish to use them.

• Scale as important as data quality. NGSWA are designed to operate at scale.NGSWA do not require any extra effort to bring in new sources.

• Openness with respect to Web (non-semantic) resources. NGSWA integrating data acquisition mechanisms in their architecture.

• Compliance with the Web 2.0 paradigm. NGSWA need to provide mechanisms for users to add and annotate data. NGSWA support user annotation are still rather primitive, and better tools are badly needed.

• Open to services. NGSWA seamlessly integrate scraping services into their data acquisition architectures.

James Hendler of Mindswap spreads the news of the paper Creating a Science of the Web he published together with Tim Berners-Lee, Wendy Hall, Nigel Shadbolt, and Daniel J. Weitzner.
In the paper they argue for a science of the web dealing with both technical and societal aspects of the web. Regarding to them this science “has its own ethos: decentralization to avoid social and technical bottlenecks, openness to the reuse of information in unexpected ways, and fairness.” (Berners-Lee et al. 2006)

A fellow-worker of mine pointed me to the following article: Domain Specific Searches using Conceptual Spectra by Bonino et al. (2004). What they do is interesting. They allow for searching documents by concepts using semantic annotation. Documents are annotated with concepts, these annotation links are weighted. This process has to be done manually. The search is carried out using a vector space model. For (graphically) analyzing the relations between documents and concepts they introduce the the notion of a Conceptual Spectrum. A conceptual spectrum visualizes the relations to concepts of one document according to the weight of the annotation link.

Daniel Kirstenpfad over at schrankmonster discovered a nice tool by Microsoft, the Windows Live Writer. It allows offline editing of posts for various blogging software. I will be testing it in the next time, actually this post is written using it.

STNGW is online.

This is the private research blog of Peter Scheir, dealing with topics related to Ontologies, the Semantic Web and Web 2.0 in the context of information retrieval and technology enhanced learning. While I am lucky enough to deal with some of the topics presented here during my work at the Know-Center, this blog is not associated with the Center or my work there.