Many methods, many microbes: methodological diversity and standardization in the deep subseafloor biosphere

Standardization is widely assumed to be important to advance science. This assumption is typically embedded in initiatives to devise infrastructure and policies to support scientific work. This paper examines a movement comprising scientists advocating methods standardization in an emerging scientific domain, the deep subseafloor biosphere. This movement is not primarily motivated by the usual rationales for standardization, but instead by the aim of intervening in the politics of an infrastructure upon which the domain depends, scientific ocean drilling cruises. This infrastructure is shared and contested with other domains, and this movement regards standardization as a critical step in reconfiguring the infrastructure to secure a greater share of resources for the deep subseafloor biosphere. This movement encounters two tensions. One tension is between the perceived benefits of standardization vs. methodological diversity. Another tension is between perceived benefits for the domain vs. a lack of incentives for individuals to perform necessary standardization work

Dealing with privacy – Personal privacy from a research data management perspective

Sharing research data is increasingly required by key stakeholders, such as funding agencies and journals. However, sharing human subjects data poses multiple issues around protecting these subjects' privacy. This poster examines these issues through a Delphi study, comprising interviews and questionnaires, of stakeholders (n=24) involved in data curation and sharing in Norway. Two particular contexts are considered: 1) privacy in international research collaborations and 2) maintaining research subjects' trust in the re-searcher. The findings presented in this poster show tensions between maintaining subjects' privacy, maintaining trust, and advancing research. These tensions are complicated further by conflicting perspectives on privacy held by different stakeholders. Researchers and other stakeholders must balance these aspects throughout the data lifecycle, from data collection to decisions about sharing. All stakeholders involved in data sharing should pay attention to research subjects through dialog and negotiation

When Scientists Become Social Scientists: How Citizen Science Projects Learn About Volunteers

Online citizen science projects involve recruitment of volunteers to assist researchers with the creation, curation, and analysis of large datasets. Enhancing the quality of these data products is a fundamental concern for teams running citizen science projects. Decisions about a project’s design and operations have a critical effect both on whether the project recruits and retains enough volunteers, and on the quality of volunteers’ work. The processes by which the team running a project learn about their volunteers play a critical role in these decisions. Improving these processes will enhance decision-making, resulting in better quality datasets, and more successful outcomes for citizen science projects. This paper presents a qualitative case study, involving interviews and long-term observation, of how the team running Galaxy Zoo, a major citizen science project in astronomy, came to know their volunteers and how this knowledge shaped their decision-making processes. This paper presents three instances that played significant roles in shaping Galaxy Zoo team members’ understandings of volunteers. Team members integrated heterogeneous sources of information to derive new insights into the volunteers. Project metrics and formal studies of volunteers combined with tacit understandings gained through on- and offline interactions with volunteers. This paper presents a number of recommendations for practice. These recommendations include strategies for improving how citizen science project team members learn about volunteers, and how teams can more effectively circulate among themselves what they learn.Ope

When scientists meet the public: an investigation into citizen cyberscience

Citizen Cyberscience Projects (CCPs) are projects mediated through the Internet, in which teams of scientists recruit members of the public (volunteers) to assist in scientific research, typically through the processing of large quantities of data. This thesis presents qualitative ethnographic case studies of the communities that have formed around two such projects, climateprediction.net and Galaxy Zoo. By considering these social actors in the broader contexts in which they are situated (historical, institutional, social, scientific), I discuss the co-shaping of the interests of these actors, the nature of the relationships amongst these actors, and the infrastructure of the projects and the purposes and nature of the scientific work performed. The thesis focusses on two relationships in particular. The first is that between scientists and volunteers, finding that, although scientists in both projects are concerned with treating volunteers with respect, there are nevertheless considerable differences between the projects. These are related to a number of interconnecting factors, including the particular contexts in which each project is embedded, the nature of the scientific work that volunteers are asked to undertake, the possibilities and challenges for the future development of the projects as perceived by the scientists, and the tools at the disposal of the respective teams of scientists for mediating relationships with volunteers. The second is amongst the volunteers themselves. This thesis argues that volunteers are heterogeneous, from disparate backgrounds, and that they sustain their involvement in CCPs for very different purposes. In particular, they seek to pursue these through the way they negotiate and construct their relationships with other volunteers, drawing on particular features of the project to do so. This thesis contributes to two fields. The first is to Citizen Cyberscience itself, with a view to improving the running of such projects. Some social studies have already been conducted of CCPs to this end, and this thesis both extends the analysis of some of these pre-existing studies and also problematizes aspects of CCPs that these studies had not considered. I discuss the significance of my findings for those involved in setting up and running a CCP, and present some recommendations for practice. The second field is Science and Technology Studies, in particular studies of public engagement with scientific and technological decision- and knowledge-making processes. The modes of engagement found in CCPs differ in key ways from those that have already been documented in the existing literature (in particular, different power relationships) and thus offer new ways of understanding how the public might be engaged successfully in such processes.Ope

Ethical perspectives on data and software sharing in the sciences: A research agenda

Data and software are critical components of scientific work. Increased data and software sharing promises many benefits for science. Many stakeholders are building infrastructure and implementing policies to promote sharing. However, sharing remains rare in practice. Attention must be paid to researchers' ethical perspectives on sharing to fully realize the promise of sharing and promote greater circulation of data and software and better uptake of infrastructure for data and software curation. This research presents an agenda for researching these perspectives, including characterizing and accounting for researchers' perspectives; examining how these perspectives shape decisions related to data and software sharing; and understanding how and why differences in perspectives arise and are contested, negotiated, and resolved in multidisciplinary scientific collaboration. This agenda will enable stakeholders to identify and resolve differences in ethical perspectives, and develop policies, infrastructures, and education that support existing ethical perspectives, and cultivate better ethical practices.Ope

Uncertainty About the Long-Term: Digital Libraries, Astronomy Data, and Open Source Software

Digital library developers make critical design and implementation decisions in the face of uncertainties about the future. We present a qualitative case study of the Large Synoptic Survey Telescope (LSST), a major astronomy project that will collect and make available large-scale datasets. LSST developers make decisions now, while facing uncertainties about its period of operations (2022-2032). Uncertainties we identify include topics researchers will seek to address, tools and expertise, and availability of other infrastructures to exploit LSST observations. LSST is using an open source approach to developing and releasing its data management software. We evaluate benefits and burdens of this approach as a strategy for addressing uncertainty. Benefits include: enabling software to adapt to researchers’ changing needs; embedding LSST standards and tools in community practices; and promoting interoperability with other infrastructures. Burdens include: open source community management; documentation requirements; and trade-offs between software speed and accessibility.Alfred P. Sloan Foundation (#20113194, #201514001)Ope

Beyond Big or Little Science: Understanding Data Lifecycles in Astronomy and the Deep Subseafloor Biosphere

For decades, the big science and little science dichotomy has served as a starting point for many analyses of scientific research and data practices, including studies used to inform the construction of scientific knowledge infrastructures. We challenge this dichotomy by presenting findings from longitudinal, qualitative case studies of data lifecycles in two scientific domains, each centered around a large, distributed scientific collaboration. One is astronomy and the Sloan Digital Sky Survey (SDSS). The other is the deep subseafloor biosphere and the Center for Dark Energy Biosphere Investigations (C-DEBI). We show that some critical stages of the data lifecycle in each domain unfold in big science contexts while other critical stages occur in little science contexts. Furthermore, these big and little science contexts shape each other dynamically. This challenging of the big and little science dichotomy has implications for the building of scientific knowledge infrastructures, including those supporting data management.ye

Our knowledge of knowledge infrastructures: Lessons learned and future directions

The Knowledge Infrastructures Workshop conducted at UCLA in February 2020, and funded by the Alfred P. Sloan Foundation, revisited the goals and findings of the 2012 workshop held at the University of Michigan. Thirty scholars, from a diverse array of disciplines and backgrounds, charted a course for the next decade of KI research. Such infrastructures are increasingly fragile, and often brittle, in the face of open data and open source, the demise of gatekeepers, and shifting public and private boundaries that redistribute power. Participants identified new methods and new opportunities for studying KI. Among the many scholarly products they proposed are publications, grant proposals, conference sessions, and workshops on the role of libraries in data services, the death and afterlives of KI, misinformation and disinformation in KI, KI in the Anthropocene, “N simplish rules” to grow and sustain KI, university capacities for KI, designing sustainable KI, and inclusion of underrepresented groups in the design of KI. The report, position papers, and other materials will be maintained at the KI workshop site, http://knowledgeinfrastructures.org