| Literature DB >> 24376309 |
Titus Schleyer1, Brian S Butler1, Mei Song1, Heiko Spallek1.
Abstract
Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers' need for comprehensive information and potential collaborators' desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user's primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems.Entities:
Keywords: Design; Human Factors; Management; Online knowledge communities; Theory; Web 2.0; Web 2.0 applications; Web collaborative software; social networks; social software
Year: 2012 PMID: 24376309 PMCID: PMC3872832 DOI: 10.1145/2147783.2147785
Source DB: PubMed Journal: ACM Trans Comput Hum Interact ISSN: 1073-0516 Impact factor: 2.351