TY - GEN
T1 - Supporting open collaboration in science through explicit and linked semantic description of processes
AU - Gil, Yolanda
AU - Michel, Felix
AU - Ratnakar, Varun
AU - Read, Jordan
AU - Hauder, Matheus
AU - Duffy, Christopher
AU - Hanson, Paul
AU - Dugan, Hilary
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - The Web was originally developed to support collaboration in science. Although scientists benefit from many forms of collaboration on the Web (e.g., blogs, wikis, forums, code sharing, etc.), most collaborative projects are coordinated over email, phone calls, and in-person meetings. Our goal is to develop a collaborative infrastructure for scientists to work on complex science questions that require multi-disciplinary contributions to gather and analyze data, that cannot occur without significant coordination to synthesize findings, and that grow organically to accommodate new contributors as needed as the work evolves over time. Our approach is to develop an organic data science framework based on a task-centered organization of the collaboration, includes principles from social sciences for successful on-line communities, and exposes an open science process. Our approach is implemented as an extension of a semantic wiki platform, and captures formal representations of task decomposition structures, relations between tasks and users, and other properties of tasks, data, and other relevant science objects. All these entities are captured through the semantic wiki user interface, represented as semantic web objects, and exported as linked data.
AB - The Web was originally developed to support collaboration in science. Although scientists benefit from many forms of collaboration on the Web (e.g., blogs, wikis, forums, code sharing, etc.), most collaborative projects are coordinated over email, phone calls, and in-person meetings. Our goal is to develop a collaborative infrastructure for scientists to work on complex science questions that require multi-disciplinary contributions to gather and analyze data, that cannot occur without significant coordination to synthesize findings, and that grow organically to accommodate new contributors as needed as the work evolves over time. Our approach is to develop an organic data science framework based on a task-centered organization of the collaboration, includes principles from social sciences for successful on-line communities, and exposes an open science process. Our approach is implemented as an extension of a semantic wiki platform, and captures formal representations of task decomposition structures, relations between tasks and users, and other properties of tasks, data, and other relevant science objects. All these entities are captured through the semantic wiki user interface, represented as semantic web objects, and exported as linked data.
UR - http://www.scopus.com/inward/record.url?scp=84937459605&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84937459605&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-18818-8_36
DO - 10.1007/978-3-319-18818-8_36
M3 - Conference contribution
AN - SCOPUS:84937459605
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 591
EP - 605
BT - The Semantic Web
A2 - Gandon, Fabien
A2 - Sack, Harald
A2 - Zimmermann, Antoine
A2 - Sabou, Marta
A2 - d’Amato, Claudia
A2 - Cudré-Mauroux, Philippe
PB - Springer Verlag
T2 - 12th European Semantic Web Conference, ESWC 2015
Y2 - 31 May 2015 through 4 June 2015
ER -