New software identifies scientific trends
software that is set to provide insights into trends and patterns
in scientific and patent information, which is achievable through
greater value from search results.
The software is set to become a valuable tool in drug research and development. The race to provide effective treatments increasingly depends on the techniques and methods used to extract relevant data. Current practices being developed in the bioinformatic field creates massive amounts of data.
While the great strength of biological data adds to the depth of understanding, the worry is that the bottleneck that is forming will threaten to engulf all the good work that has been so far achieved.
STN AnaVist, was developed in response to the scientific needs for tools to help them analyse search results from scientific literature and patent databases and visualise patterns and trends in the research landscape.
The software was designed to include analysis of information from three scientific resources: CAS' CAplus database of scientific literature and patent information and the USPATFULL and PCTFULL patent databases containing the full text of US and Patent Cooperation Treaty (PCT) patents.
Now, scientists will be able to assimilate and present information more effectively to support competitive intelligence, research & development strategy and management decision-making.
"STN AnaVist creates an interactive workspace to interpret patent and research data in new ways. It allows users to identify relationships between the data. The features enhance views on developments in research and technology," says Sabine Brünger-Weilandt, managing director and CEO of FIZ Karlsruhe.
"Through pictures and landscapes, based on the traditional research results, our users will gain exciting new perspectives and insights - a new vista of scientific knowledge," she added.
The software also features an interactive workspace displaying a range of data visualisations, dynamically integrated, including cluster and contour maps, histograms, and co-occurrence matrices.
Harmonisation and standardisation of data prior to visualisation is achieved using algorithms based on intellectual data analysis. STN AnaVist also features a data grouping aspect that helps to minimise scattering of results by permitting editing and customising data elements across the databases.
More data has been generated between 1999 and 2002 than that generated in all of the pharmaceutical industry's history. Especially within the past 40 years, a fivefold increase in the number of abstracts published in Medline has pushed the number up to 12 million. Most are available online as full text articles.
In addition to this there are patents, internal reports, and other potentially valuable in-house and public sources. Although a small proportion of this information is in a structured form that can be managed using database systems, around 80 per cent is unstructured and written in a natural language.
"The information challenge of the 21st Century is not information access, but information utilisation. STN AnaVist is an important first step from the STN partnership to bring new technologies to bear on this challenge," said CAS President Robert Massie.
"Using results from CAS databases and others on STN, information users will now be able to view the competitive landscape, visualise where research is heading-receive a much greater return on their investment in information," he added.
