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Comparison of research networking tools and research profiling systems
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Comparison of research networking tools and research profiling systems : ウィキペディア英語版
Comparison of research networking tools and research profiling systems
Research Networking (RN) is about using web-based tools to discover and use research and scholarly information about people and resources. Research Networking tools (RN tools) serve as knowledge management systems for the research enterprise. RN tools connect institution-level/enterprise systems, national research networks, publicly available research data (e.g., grants and publications), and restricted/proprietary data by harvesting information from disparate sources into compiled expertise profiles for faculty, investigators, scholars, clinicians, community partners, and facilities. RN tools facilitate the development of new collaborations and team science to address new or existing research challenges through the rapid discovery and recommendation of researchers, expertise, and resources.〔Carey J (2011). "(Faculty of 1000 and VIVO: Invisible colleges and team science )". ''Issues in Science and Technology Librarianship'' Spring 2011.〕〔Fazel-Zarandi M, Devlin HJ, Huang Y and Contractor N (2011). "Expert recommendation based on social drivers, social network analysis, and semantic data representation". ''2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems''. pp. 41-48. (ACM, Chicago, IL)〕

RN tools differ from search engines such as Google in that they access information in databases and other data not limited to web pages. They also differ from social networking systems such as LinkedIn or Facebook in that they represent a compendium of data ingested from authoritative and verifiable sources rather than predominantly individually asserted information, making RN tools more reliable. Yet, RN tools have sufficient flexibility to allow for profile editing. RN tools also provide resources to bolster human connector systems: they can make non-intuitive matches, they do not depend on serendipity, and they do not have a propensity to return only to previously identified collaborations/collaborators. RN tools also generally have associated analytical capabilities that enable evaluation of collaboration and cross-disciplinary research/scholarly activity, especially over time.

Importantly, data harvested into robust RN tools is accessible for broad repurposing, especially if available as Linked Open Data (RDF triples). Thus RN tools enhance research support activities by providing data for customized, up-to-date web pages, CV/biosketch generation, and data tables for grant proposals.
The following tables compare research networking (RN) software.
== General ==

This table provides general information for each tool: name, developing institution, external links to information, whether the code is Open Source and known adopters of the software.

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