Abstract
Making sense of research community patterns can be a challenging task since they are often complex, dynamic, and inseparable from the 'messiness' of the real world. This paper introduces a data-centric community mapping tool that extracts and visualizes research communities in Computer Science, based on the DBLP publication database [1]. Initial experiences with the community mapping tool suggest a possibility to facilitate the process of initiating cross-boundary research collaboration using multiple network structures.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 9th International Conference on Creating, Connecting and Collaborating through Computing, C5 2011 |
| Pages | 11-16 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - Jul 29 2011 |
| Externally published | Yes |
| Event | 9th International Conference on Creating, Connecting and Collaborating through Computing, C5 2011 - Kyoto, Japan Duration: Jan 18 2011 → Jan 20 2011 |
Other
| Other | 9th International Conference on Creating, Connecting and Collaborating through Computing, C5 2011 |
|---|---|
| Country | Japan |
| City | Kyoto |
| Period | 1/18/11 → 1/20/11 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
Cite this
Community mapping for cross-boundary research collaboration. / Konomi, Shinichi.
Proceedings - 9th International Conference on Creating, Connecting and Collaborating through Computing, C5 2011. 2011. p. 11-16 5936685.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Community mapping for cross-boundary research collaboration
AU - Konomi, Shinichi
PY - 2011/7/29
Y1 - 2011/7/29
N2 - Making sense of research community patterns can be a challenging task since they are often complex, dynamic, and inseparable from the 'messiness' of the real world. This paper introduces a data-centric community mapping tool that extracts and visualizes research communities in Computer Science, based on the DBLP publication database [1]. Initial experiences with the community mapping tool suggest a possibility to facilitate the process of initiating cross-boundary research collaboration using multiple network structures.
AB - Making sense of research community patterns can be a challenging task since they are often complex, dynamic, and inseparable from the 'messiness' of the real world. This paper introduces a data-centric community mapping tool that extracts and visualizes research communities in Computer Science, based on the DBLP publication database [1]. Initial experiences with the community mapping tool suggest a possibility to facilitate the process of initiating cross-boundary research collaboration using multiple network structures.
UR - http://www.scopus.com/inward/record.url?scp=79960733296&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960733296&partnerID=8YFLogxK
U2 - 10.1109/C5.2011.10
DO - 10.1109/C5.2011.10
M3 - Conference contribution
AN - SCOPUS:79960733296
SN - 9780769543635
SP - 11
EP - 16
BT - Proceedings - 9th International Conference on Creating, Connecting and Collaborating through Computing, C5 2011
ER -