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

2. 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

3. 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 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).”

4. 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

5. 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

6. 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?

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

8. 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

9. 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)

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

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

12. 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

13. 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

14. 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

15. 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.

16. 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)

17. 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.

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