TY - GEN
T1 - Collaborative analytics and brokering in digital humanitarian response
AU - Hellmann, Daniel
AU - Maitland, Carleen
AU - Tapia, Andrea
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/2/27
Y1 - 2016/2/27
N2 - During large scale humanitarian crises, relief practitioners identify data used for decision making and coordination, as critical to their operations. Implicit in this need is the required capabilities for analyzing data. Given the rapidly evolving systems of collaborative data management and analysis in digital humanitarian efforts, information scientists and practitioners alike are keen to understand the role of data analytics in response operations. Through a case study of a digital humanitarian collaborative effort, we examine the processes for big and small data analytics, specifically focusing on data development, sharing, and collaborative analytics. Informed by theories of articulation work and collaborative analytics, we analyze data from indepth interviews with digital humanitarians. Our findings identify key practices and processes for collaborative analytics in resource constrained environments, particularly the role of brokering, and in turn generate design recommendation for collaborative analytic platforms.
AB - During large scale humanitarian crises, relief practitioners identify data used for decision making and coordination, as critical to their operations. Implicit in this need is the required capabilities for analyzing data. Given the rapidly evolving systems of collaborative data management and analysis in digital humanitarian efforts, information scientists and practitioners alike are keen to understand the role of data analytics in response operations. Through a case study of a digital humanitarian collaborative effort, we examine the processes for big and small data analytics, specifically focusing on data development, sharing, and collaborative analytics. Informed by theories of articulation work and collaborative analytics, we analyze data from indepth interviews with digital humanitarians. Our findings identify key practices and processes for collaborative analytics in resource constrained environments, particularly the role of brokering, and in turn generate design recommendation for collaborative analytic platforms.
UR - http://www.scopus.com/inward/record.url?scp=84963593274&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963593274&partnerID=8YFLogxK
U2 - 10.1145/2818048.2820067
DO - 10.1145/2818048.2820067
M3 - Conference contribution
AN - SCOPUS:84963593274
T3 - Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
SP - 1284
EP - 1294
BT - Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
PB - Association for Computing Machinery
T2 - 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
Y2 - 27 February 2016 through 2 March 2016
ER -