Bio-medical Ontologies Maintenance and Change Management

Towards Bioinformatics Resourceomes 17
particular database that could provide important data for him/her research.
Similar enthusiasm could come from the discovery of an on-line program suitable
to perform a key in-silico experiment on that data. A bioinformatician
would be more interested in building such database or program. For both of
them it could be important to find articles describing related resources. In
research it is vital to understand as soon as possible if someone else already
had the same promising idea that you have had. A usual recommendation
is “not to reinvent the wheel” to avoid waste of time and money. Computer
scientists or engineers may be definitely interested in articles describing the
technical details of computational artifacts.
Where to Search for?
The most obvious starting point are search engines. But, how many minutes
- maybe hours? - does a scientist spend every day making Google [11] and
bibliographic searches? Finding the “right” resource is a difficult and timeconsuming
activity. The WWW is not semantically organized and the nature
of resources (which type of resource?) and their semantics (what are they
for?) are not clearly identifiable. The problem is analogous with academic
publications. The papers can be searched using keywords indexing but also
in this case it is still missing a semantic annotation of publications and of
the resources therein presented. Of course journals are the primary source
of knowledge and information exchange in the scientific communities. Due to
the “publish or perish” syndrome [59], unfortunately also the “bibliome” [34]
is growing out of any control. All the articles are available on-line, more
often freely accessible thanks to an “Open Access” policy. In a few years,
for bioinformatics only, the number of journals has raised from a handful
to some tenths, including all the “omics” and post-”omics” subjects which
have bioinformatics at their base. It is then clear why it is becoming essential
the support of “intelligent” software agents equipped with text-mining and
formal reasoning capabilities [68].
Databases are essential resources in bioinformatics. Since 1996 Nucleic
Acid Research (NAR) reserves a special issue to articles presenting biomolecular
databases. Figure 1 provides a summary of the number of articles published
in these database special issues. The trend is clearly increasing passing
from the about 50 articles published in 1996 to the more than 174 published
ten years afterward. In the table it is indicated also the number of
databases, listed since 1999 in the associated “Molecular Biology Database
Collection” [31]. The online collection lists today almost thousand databases
organized into the following categories: Nucleotide Sequence Databases, RNA
sequence databases, Protein sequence databases, Structure Databases, Genomics
Databases (non-vertebrate), Metabolic and Signaling Pathways, Human
and other Vertebrate Genomes, Human Genes and Diseases, Microarray