(reconstructed from wayback)
Talks over on the Simile list have moved into the realm of bibliographic citations and of the best way of describing people. FRBR has been mentioned as well as IFLAâ€™s FRAR work for authority records in this context. Iâ€™m particularly encoraged by the more recent work of Ian Davis and Richard Newman in this area in grounding FRBR in RDF.
I very much respect the FRBR work and I believe the instantiation of FRBR in RDF is an important step for weaving libraries into the Web and letting folks outside of the library community know that the libraries still know a thing or two regarding the modeling and management of information . Iâ€™d very much like to see this work move forward and Iâ€™m interested in learning more about how to help.
From the perspective of project Simile (where this discussion in part is taking place), however, Iâ€™m slightly less interested in the â€œbestâ€ way of describing things (e.g. People) and more interested in how to start operationalize the contextual linking of these things together. I believe there are some relatively simple steps that might be taken to achieve a very powerful network effect.
Here is an example â€¦
hubmed has wrapped pubmed and provided (among many things) an RDF representation of the corresponding bibliographic data. This is an important step for â€œconnecting thingsâ€ in the biomedical and life sciences community. Here is an example of one of these records ( HTML, RDF/XML)
By itself, the article in RDF form is not really helpful. That said, in RDF it makes it easier to connect this with other data sets. To illustrate this example, Iâ€™ve added this RDF data to the Semantic Bank and used this tool to help connect intersting bits and pieces from several servers.
One of the first things one may notice looking at this record is that youâ€™ll see the authors listed as (anonymous items). This is one of the reasons why Iâ€™m of the opinion that a â€œdefault valueâ€ thats included by the data providers would be useful.
If you get past the debug-view of the interface, another thing you may notice (choose â€˜Show Referersâ€™) is the fact that this article is a â€œsupporting Articleâ€ for an Observation and that there is another article that supports this Observation as well. Further, this Observation is one of several â€œsupporting Evidenceâ€ (again choose â€˜Show Referersâ€™) that is associated with the Amyloid Hypothesis which is related to Alzheimers Disease.
Some of this data comes from pubmed (articles), some comes from scientific communities (in the above case, the Amyloid Hypothesis is from Alzforum). Through the Semantic Web we can begin to see the various potentials of using a common framework to draw connections among various â€œthingsâ€ of interest. In this specific case of the life sciences community, I think this community is very close to not only connecting people to people, people to articles, articles to journals, etc. but articles to hypothesis, hypothesis to disease, genes, proteins, etc. And ultimatly conntecting the dots between diseases to drugs.
There are many paths one may take to make this connection and the path for one may not be the same as one that works for another. Providing the ability f\ or people to create new connections among data and share this with others is key. A community focused on a particular goal, task or interest coupled with a f\ ramework for representing, sharing and integrating data is a powerful combination.
Small but important steps will help facilitate this goal. On the technology side, more tools like Connotea, Simile, etc. are required. From the content side however, common means of referencing â€˜thingsâ€™ that are real (people, places, articles, genes, proteins, etc.) and from there, agreement on a common means for describing these resources (RDF) are still required. Common protocols and interfaces to this data will be needed as well. This is where technologies such as SPARQL will be increasingly critical. Folks over in Nature and Hubmed seem to â€œget itâ€ and are good examples of a growing awareness in the â€œinterconnectedness of thingsâ€.
There continues to be a lot of focus on the â€œbestâ€ way to describing things. I donâ€™t want this to stop. My hope is, however, that people will begin to place an equal if not greater value on the contextualization of these things theyâ€™re hoping to describe. As we weave a web of data, I believe how things connect will prove more valuable.