International Aging Research Portfolio
International Aging Research Portfolio
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International Aging Research Portfolio

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International Aging Research Portfolio

International Aging Research Portfolio (IARP) is a non-profit, open-access knowledge management system incorporating grants, publications, conferences in natural and social & behavioral sciences. In addition to the advanced search and visual trend analysis tools the system includes a directory of research projects classified into categories related to aging research. The system uses automatic classification algorithms with elements of machine learning to assign research projects to the relevant categories. The directory is curated by many expert category editors and science advisory board members. The chair of the science advisory board is Dr. Charles Cantor.

Aging research is a multidisciplinary field spanning many areas of natural and social and behavioral sciences and the research data is widely dispersed. Popular resources like PubMed and Google Scholar provide access to historic as well as most recent scientific abstracts and full text publications. However, few resources exist that incorporate international databases of the scientific publications, scientific grant abstracts and clinical trials databases.

Grant abstracts are usually published by the funding organizations and precede publications in peer-reviewed literature. Some of the experiments described in grant abstracts fail or do not result in peer-reviewed publications. To prevent redundancy and promote scientific cooperation it is important to browse through all available grant information worldwide to see if there are similar projects being funded.

The IARP database integrates information on research grants, peer-reviewed publications, and issued patent applications from multiple sources. Additionally, the database uses flexible project classification mechanisms and tools for analyzing project associations and trends. This system enables scientists to search the centralized project database, to classify and categorize aging projects, and to analyze the funding aspects across multiple research disciplines. The IARP is designed to provide improved allocation and prioritization of scarce research funding, to reduce project overlap and improve scientific collaboration thereby accelerating scientific and medical progress in a rapidly growing area of research.

The IARP system aggregates grant data from many sources including the US National Institutes of Health (NIH), European Commission (EC), Canadian Institutes of Health Research, US National Science Foundation, Australian National Health and Medical Health Council and publication abstract data through a license of MEDLINE database. The database is searchable and the results can be presented as charts and graphs for trends analysis. One of the main features of the IARP system is automatic and manual classification of the research projects into a structured directory. The IARP science advisory board and volunteer expert category editors classify the projects from the database into relevant categories. These manually classified projects become training sets for the automatic classification algorithms with elements of machine learning. The IARP system is highly modular and portable and may be used as a platform for developing other knowledge management systems for aging research.

The International Aging Research Portfolio (IARP) includes historic grant data from the National Institutes of Health(NIH), European Commission(EC), NSF, Canadian and Australian research councils and many other sources. It also contains MEDLINE article abstracts under a license from the National Library of Medicine. The IARP volunteer development team works directly with the publication offices and regularly updates the database either automatically or by parsing the data mailed on physical medium.

Simple searches on IARP can be carried out by entering key aspects of a subject into search window.

IARP translates this initial search formulation and automatically adds field names, Boolean operators, and enhancing the search formulation significantly, in particular by routinely combining (using the OR operator) text words.

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