Bio-medical Ontologies Maintenance and Change Management

Towards Bioinformatics Resourceomes 23
present an example showing how a reader currently approaches the papers
of an issue of a typical bioinformatics journal (e.g. Journal Of Biomedical
Informatics 21 , volume 39, year 2006, issue 4). Figure 2 part a), presentsthe
Web page hosting the index of the journal issue with a “flat” list of the
articles. The only information that can help the reader to decide if a paper
can be interesting for his/her research, are its title and authors. Not any
classification is provided for the articles and in any case it is rather difficult
to summarize the content in the title. Furthermore, the reader could have not
any idea of how this knowledge domain is organized and where the papers
could be located in an ideal map of the domain. So we can state that this list
of papers weakly assists in their retrieval, because of the lack of a semantical
approach to the classification of papers.
In Figure 2 part b), we tried to organize the same set of papers in a
hierarchy that can intuitively describe the topics treated by the papers. In this
way the user is able to recognize the resources (in this example only papers)
of interest at first glance, without opening other documents for reading their
abstracts in order to understand their content.
This vision is the beginning of a bigger one, that sees the topics the resources
concern organized through an ontology. In this way it is possible to
give a more understandable description of the domains the papers describe.
Another feature of this intuitive vision is the possibility of extending the field
of bioinformatics resources also to other kind of entities. In this manner also
e.g. programs, databases, scientists, universities, books, and other resources
can be clearly described and retrieved. Like the domains, also the different
kinds of bioinformatics resources can be described through the hierarchical
formalism of ontologies. Besides a perceptible presentation of the reality, this
kind of classification is able to be machine-understandable and consequently
“reasonable” from “in-silico” scientists [68].
3.2 What Is a Resourceome?
In order to help both scientists and software agents in their awareness of the
domain, we raised the exigence of classifying the huge world of bioinformatics
resources (resourceome) [16] building a general machine-understandable
index. This could emerge bottom-up from the creation of - probably overlapping
- Resourceomes (please note here the capital “R”). Organizations,
individual scientist and other Resourceomes creators could share, merge and
integrate their Resourceomes aiming to a general one. But in any case a Resourceome
represents the vision of scientific domain as it is perceived by its
creator. We define a Resourceome as structurally composed of two ontologies.
One ontology is for the description of the kinds of bioinformatics resources
(left side of figure 3) and the other is for the description of the topics that
the resources concern (right side of figure 3).
21 www.sciencedirect.com/science/journal/15320464