Abstract
All research depends on data in one form or another. From physical field specimens that are themselves raw data but also objects that are measured, classified, sorted, and recorded as both data and meta-data, to born digital data that occur as a result of people’s activities on the Internet and interacting with technological systems, data feed the research enterprise.
For the last decade, Dr. Meyer and his colleagues have been investigating collaborative data intensive research. In this talk, he will draw on this body of knowledge to discuss both collaboration at the institutional, national and international level as well as the challenges of long-lived data.
Case studies from science, medicine, the social sciences, and the arts and humanities will be used to illustrate his overall argument that data-intensive research collaborations should be viewed as socio-technical interaction networks (STINs) comprised of people, machines, and objects both physical and digital. Only by understanding how these parts of the network interact can collaborations succeed (while hopefully avoiding the pitfalls of previous collaborations). Examples of notable successes (and a few notable failures) will be used to illustrate how projects deal with the fact that time and again, human and social factors remain the most bedeviling part of collaboration even once the technical details seem to have been sorted out.
These issues are particularly important when data have a long-life span, sometimes much longer than the lives of the people creating and managing it. Examples from marine biology, genomics, and publishing will show how some fields are dealing with these issues, and the lessons it suggests for organizations such as TDWG.
