TY - CHAP
T1 - Crowdsourcing for information visualization
T2 - Promises and pitfalls
AU - Borgo, Rita
AU - Lee, Bongshin
AU - Bach, Benjamin
AU - Fabrikant, Sara
AU - Jianu, Radu
AU - Kerren, Andreas
AU - Kobourov, Stephen
AU - McGee, Fintan
AU - Micallef, Luana
AU - von Landesberger, Tatiana
AU - Ballweg, Katrin
AU - Diehl, Stephan
AU - Simonetto, Paolo
AU - Zhou, Michelle
N1 - Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crowdsourcing in empirical studies for visualization – participants, study design, study procedure, data, tasks, and metrics & measures. We then present four case studies, discussing potential mechanisms to overcome common pitfalls. This chapter will help the visualization community understand how to effectively and efficiently take advantage of the exciting potential crowdsourcing has to offer to support empirical visualization research.
AB - Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crowdsourcing in empirical studies for visualization – participants, study design, study procedure, data, tasks, and metrics & measures. We then present four case studies, discussing potential mechanisms to overcome common pitfalls. This chapter will help the visualization community understand how to effectively and efficiently take advantage of the exciting potential crowdsourcing has to offer to support empirical visualization research.
UR - http://www.scopus.com/inward/record.url?scp=85031501419&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031501419&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-66435-4_5
DO - 10.1007/978-3-319-66435-4_5
M3 - Chapter
AN - SCOPUS:85031501419
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 96
EP - 138
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer-Verlag
ER -