Departmental Member

Supervisory CommitteeDr. Margaret-Anne Storey, (Department of Computer Science)SupervisorDr. Daniela Damian, (Department of Computer Science)Departmental MemberDr. Eric Manning, (Department of Computer Science)Departmental MemberDr. Gholamali Shoja, (Department of Computer Science)Departmental MemberDr. Rosaline Canessa, (Department of Geography)Outside Member This dissertation seeks to answer the research questions that arise when digitaltechnologies are used to support distributed, artifact-centric, scientific collaboration.Scientific research is fundamentally collaborative in nature, with researchers oftenforming collaborations that involve colleagues from other institutions and often othercountries. Modern research tools, such as high-resolution scientific instruments andsophisticated computational simulations, are providing scientists with digital data at anunprecedented rate. Thus, digital artifacts are the focus of many of today’s scientificcollaborations. The understanding of scientific data is difficult because of the complexityof the scientific phenomena that the data represents. Such data is often complex instructure, dynamic in nature (e.g. changes over time), and poorly understood (little a-priori knowledge about the phenomena). These issues are exacerbated when suchcollaborations take place between scientists who are working together at a distance.This dissertation studies the impact of distance on artifact-centric scientificcollaboration. It utilizes a multi-dimensional research approach, considering scientificcollaboration at multiple points along the methodological (qualitative/quantitativeresearch methods), cognitive (encoding/decoding), community (many/single researchgroups), group locality (collocated/distributed), and technological (prototype/production)dimensions. This research results in three primary contributions: 1) a new framework(CoGScience) for the study of distributed, artifact-centric collaboration; 2) new empiricalevidence about the human communication channels scientists use to collaborate (utilizingboth longitudinal/naturalistic and laboratory studies); and 3) a set of guidelines for thedesign and creation of more effective distributed, scientific collaboration tools.