Matthew Turk: Tools, Communities, Data and the Research Ecosystem

Tools, Communities, Data and the Research Ecosystem: To a large extent, conducting scholarly inquiry requires mediation between the researcher and data, often taking the form of computational tools and techniques. In this talk, I will present on both specific tools, the communities that surround them, and how researchers in those communities address, process, and understand their data. Stepping back from this, I will describe how these specific communities can be used as models or laboratories for understanding the means by which researchers interact and build shared understanding of data, where computational tools can mediate or shape that interaction, and how the development of socio-technical systems can impede or accelerate the process of inquiry. Finally, I will close by describing mechanisms by which increasing connectivity between technical systems, datasets, and researchers themselves can lead to new synergies as well as several failure modes for this mode of collaboration.

Bio: Matthew Turk earned his PhD from Stanford University in 2009, and spent time as a postdoc at the University of California at San Diego and as an NSF postdoctoral fellow at Columbia University in the CyberInfrastructure for Transformative Computational Science program. At the National Center for Supercomputing Applications at Illinois, he is the principal investigator of the Data Exploration Lab (dxl.ncsa.illinois.edu) where he focuses on engaging with researchers to understand how they engage with data, how semantic representations can facilitate inquiry, and how to build effective interdisciplinary collaborations. In 2014, he was awarded a Data Driven Discovery Investigator award from the Gordon and Betty Moore Foundation and he serves as PI and co-PI on several NSF grants in the areas of data and software. He's been involved in sustainable scientific software working groups (such as WSSSPE), the scientific python community, and serves as a board member for NumFOCUS.