Read "Going to Extremes: Meeting the Emerging Demand for Durable Polymer Matrix Composites" at NAP.edu (2024)

example, that experimentalists should not measure short-beam shear strength simply because they have always done so and there happens to be a test standard for it. A database should include properties because they support promising models or because they can be used to validate (or repudiate) promising models. Making use exclusively (or nearly exclusively) of existing ASTM or industry standards without considering their relevance is a recipe for disaster.

Data as defined today are expensive to gather, difficult to harmonize, and, many times, irrelevant to a specific model. Furthermore, data tend to become outdated and must be refreshed and improved. This calls for an overhaul of the way we collect, use, tally, and communicate data. A word has been recently coined that encompasses these concepts: informatics.

INFORMATICS AS A DISCIPLINE

Informatics is a relatively new field that is fast impacting the other fields it touches. A working definition of the discipline is the research, development, or application of computational tools and approaches for expanding the use of data, including those required to acquire, store, organize, archive, analyze, or visualize the data. It is important to note, however, that the field did not appear in academia fully formed but took many years to overcome academic inertia and gain the acceptance of researchers in the disciplines involved.

Biomedical Informatics

Biomedical informatics applies computer science, decision science, cognitive science, and organizational theory to the management of biological and medical information. The biological community did not universally agree on the importance of developing information resources and tools, even those that are today some of the most visible—GenBank, model organism databases, and the Human Genome Project. In retrospect, however, each of these efforts has revolutionized the accessibility and applicability of data and analysis tools to biologists, and many say these resources have created new perspectives for how biological research is done and interpreted. Extending these centralized data and analysis resource concepts to PMCs would enable researchers to make connections and draw conclusions about PMC mechanism-property relations that cannot be made with the current decentralized state of data, analysis, and algorithms in the field.

Physicians, clinical researchers, and biologists have long needed to organize and sift through large quantities of data. Since the 1970s, biomedical professionals have joined with computer and information scientists to find new ways of dealing with their data, and the field of biomedical informatics, particularly the subfield of bioinformatics, has exploded in the last 10 years. Biomedical informatics research has been able to capture significant amounts of funding, primarily from the National Institutes of Health, and there are now biomedical informatics laboratories at every institution doing major biological research. According to gradschools.com, 62 schools in the United States and another 29 outside of the United States currently have medical informatics or bioinformatics M.S. or Ph.D. programs.

The emergence of this academic discipline has opened up new areas of research, drawing in scientists who wish to make new discoveries by mining existing data. Biomedical informaticists have made basic research discoveries by creating and then applying computational tools to find subtle patterns in vast amounts of data that were previously inaccessible to biologists. In one example, computational biologists were able to analyze the genome of an intriguing and poorly understood microorganism to find a DNA sequence—unrelated to that of any other known organism—that was critical for understanding how the microorganism, an enzyme, replicated its DNA. This enzyme has been exploited in the development of the polymerase chain reaction and resulted in a Nobel prize for its achiever.

As part of their research, bioinformaticists are constantly developing new databases and computational tools and publishing them on the Internet, providing a tremendous service for biological scientists. In general, informatics researchers generate algorithms to extract valuable information from massive quantities of raw data. When the informaticists provide these tools on the Internet, the larger community of biological scientists can use them for applications specific to their research, such as comparing gene sequences of various organisms to determine their evolutionary relationships.