Governance of Scholarly Resources SciDataCon Denver, Colorado September 12, 2016 By Sarika Sharma Introduction and hellos

New ways to organize information resources for scientific collaborative work Science Organizations Data Repositories Government Citizen Science Open Journals Collaborative ethos in science and new ways to organization information resources Centralizing + Stewarding digital and non-digital resources for reuse in collaborative work

Information Infrastructure Aggregating data for collaborative knowledge work DATA 1 DATA 2 DATA 3 DATA 5 DATA 4 Aggregating data and collaborative qork requires information infrastructure.. Imagine for a minute that you are an oncology researcher and you are interested in conducting a study that looks at efficacy of different treatments for non-Hodgkins Lymphoma. You find a clinical study in Sweden a research university, a publication with data from Canada, and a group of scholars in California that are attempting to do the same. You are interested in aggregating this data because you believe it will provide a comparison of treatments. So you email the Canadian scholars and they haven’t written back; the Swedish are very interested in collaborating while researchers in California are hesitant in terms of the sharing data of an ongoing study. You are a researcher are left to work with what you have. This where an organization that hosts an information infrastructure comes into play. Organizations that steward scientific data build relationships with organizations, individuals, and groups to develop the norms, procedures, that enable the release of data for collaborative work Information Infrastructure “Access to information in a network world (Borgman, 2007).”

Information Infrastructure Architecture of information categories and classifications Open, flexible, standardized, (Ribes and Lee, 2010), locative Categorizes data, centralizes data, makes the data locative If we don’t know what type of data and where data is, there can’t much cooperative work Information Infrastructure description they are a lot like grocery stores

Why Organizations? Infrastructures sociotechnical entities Require technical expertise Administrative heft, funding, cooperation Develop norms of stewardship and use Understand how these organizations are implicitly developing an institution on data stewardship for scientific work Describe data organizations: grassroots, top-down, some form out of universities, different varieties

Research Questions How are information infrastructures governed by organizations for reuse and collaborative work? How does the organization of those resources become infrastructural to the practice of science?

Substrate to the Substance Scientific Practice Data Infrastructure (Star and Ruhleder, 1996)

Comparative Case Study of Data Infrastructure Policies Research Design Comparative Case Study of Data Infrastructure Policies A&B&C: Three Library Institutions D&G Two Science Organizations E&F: Two Government Organizations A B G C F D E Add here that there are two ways to understand infrastructure: Governance of infrastructure and the ways it is used in practice fundamentally these are two different ways of thinking about the the research question. The first research question will be explored using a theoretical framework of infrastructure that describes the ways in which goveranance highlights certain characteristics of organizations \\ Participant Observation at All-Hands Meeting Website and Document Analysis

Governance: Normative Rules as decision points for organizations Stewardship decisions (Khatri and Brown, 2010) Cultural foundations of organizations Decisions around the institutional ecology of science: norms around publications, funding, attribution, tenure and career, collaborative work, and type of scientific work (Star and Griesemer, 1989) Participant Observations Interviews Document Analysis (to understand the implicit rules of conduct)

A Research Design Ethnography Science Collaborative Team using data from an organization

Two Cases Library Organization=LOC Data Discovery platform Science Organization= SOG Collaborative Science around sensor data

Data Infrastructure, Different Goals Organization Who governs? Model of Organization Model of Infrastructure What is governed? Library Organization LOC: Data Discovery Network of Library and Information Professionals; former scientists Non-profit Business: Science product Hub and Node metadata sharing Data, metadata and resources for data management Science Organization SOG: Sensor Data Network of Senior Scientists with junior scholars Non-profit Science Enterprise: Collaborative Space Assemblage of people and repositories Science Collaboration Groups

Data Handling Norms Organization Deposition Storage Preservation Management LOC: Data Discovery Direct to nodes and internal repository;tools Mostly nodes and tools: Archivematica,Archon, Drambora, etc DMP Tools; Robust research in this area SOG: Sensor Data Reuse Depends on the data Stored at partner organizations: EPA and CUAHSI EPA and CUAHSI

Rules of Engagement: Scientific Practice Community Reuse Technologies Ariculate Scientific Work Publishing Funding Projects LOC: Data Discovery: No community membership Library of scripts and tools for reuse Provide user types Direct you to other organizations and in house policy No funding for proposals SOG: Sensor Data: Community membership Open Source: R Scripts; Modeling Technologies A scholarly community around reuse studies Provide guidelines based on National Science Academy Provide some funding to support proposals

Governance LOC: Rules of use are developed around the institution of library and information Data Sharing: Breaking social and technical barriers to share to an organization Data Management: Best practices and tools Data Reuse: Motivations and incentives; integration studies SOG: Rules of use are developed around the institution of science Data Sharing: Breaking social barriers to sharing and reuse amongst scientists Organizing ways to do novel science: Breakthrough efforts to understand climate change Two different types of cultural norms around governance. Although they both are very much invested in developing information infrastructures one is closer to a community of practice while anther is closer to the library and information institution. While on organization has a very good idea of how to develop the tools and technologies that are necessary for usable infrastructure the communities of practice are largely unknown. On the other hand, SOG has been focused on infrastructure development but through the ethos that collaborative efforts require activities in trust. Already certain gaps that we observe from a distance when looking at infrastructure through the Star and Ruhleder framework. In terms of productivity, there could be greater cooperative work.

Organizing Visions for Science: Polycentric Governance Efforts? Disciplines have traditional divisions of labor Shared approaches to intellectual work will require enhanced means of communication for collective work (Constantinides and Barrett 2014; Feldman, 2014)

Practical Policy Theory Implications Practical: learning more about what these organizations are doing and coming across some patterns or not Policy wise: are there some aspects of governance that policy folks need to be aware of in order to be data handlers? Theoretically: There are implications to be theory, Is there a relationship between the institution that is forming the rules and norms and the types of infrastructures that support scientific work? I find that line of inquiry to be quiet fascinating because it shows how deeply entrenched some institutions are to scientiifc practice and why newer infrastructures take longer to become a part of scientiific practice.

Thank You Sarika Sharma IMLS eScience Fellow skshar01@syr.edu Funded by the National Science Foundation Grant # 1527410