Data Sharing in the Social Sciences

In social science research there is a push towards open research and open data. Open Data implies that researchers make their data available to other researchers so that the data can be re-used. This Guide describes the requirements and provides researchers with guidance on how and where to share social science research data with focus on the Swiss research environment

Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences

There is a growing perception that science can progress more quickly, more innovatively, and more rigorously when researchers share data with each other. However many scientists are not engaging in data sharing and remain skeptical of its relevance to their work. As organizations and initiatives designed to promote STEM data sharing multiply – within, across, and outside academic institutions – there is a pressing need to decide strategically on the best ways to move forward. In this paper, we propose a new mechanism for conceptualizing and supporting STEM research data sharing.. Successful data sharing happens within data communities, formal or informal groups of scholars who share a certain type of data with each other, regardless of disciplinary boundaries. Drawing on the findings of four large-scale qualitative studies of research practices conducted by Ithaka S+R, as well as the scholarly literature, we identify what constitutes a data community and outline its most important features by studying three success stories, investigating the circumstances under which intensive data sharing is already happening. We contend that stakeholders who wish to promote data sharing – librarians, information technologists, scholarly communications professionals, and research funders, to name a few – should work to identify and empower emergent data communities. These are groups of scholars for whom a relatively straightforward technological intervention, usually the establishment of a data repository, could kickstart the growth of a more active data sharing culture. We conclude by offering recommendations for ways forward. [This paper is a conference pre-print presented at IDCC 2020 after lightweight peer review.

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

Resilience in the proteomics data ecosystem: how the field cares for its data

The public dissemination of data is an integral part of the life sciences. In the field of proteomics too, data sharing has taken off over the last few years, with the first downstream uses of these data quickly gaining prominence. At the same time, the recent unfortunate demise of two repositories, NCBI Peptidome and ProteomeCommons Tranche, has shown the frailty of such data gathering efforts. Heroic efforts by the PRIDE and Peptidome teams to rescue the Peptidome data have now ensured their continued availability to the field, and alternatives have already been put in place for Tranche. But with public data increasingly at the hub of the life sciences, it is a good time to look at the proteomics data ecosystem in some more detail

Building a Disciplinary, World-Wide Data Infrastructure

Sharing scientific data, with the objective of making it fully discoverable, accessible, assessable, intelligible, usable, and interoperable, requires work at the disciplinary level to define in particular how the data should be formatted and described. Each discipline has its own organization and history as a starting point, and this paper explores the way a range of disciplines, namely materials science, crystallography, astronomy, earth sciences, humanities and linguistics get organized at the international level to tackle this question. In each case, the disciplinary culture with respect to data sharing, science drivers, organization and lessons learnt are briefly described, as well as the elements of the specific data infrastructure which are or could be shared with others. Commonalities and differences are assessed. Common key elements for success are identified: data sharing should be science driven; defining the disciplinary part of the interdisciplinary standards is mandatory but challenging; sharing of applications should accompany data sharing. Incentives such as journal and funding agency requirements are also similar. For all, it also appears that social aspects are more challenging than technological ones. Governance is more diverse, and linked to the discipline organization. CODATA, the RDA and the WDS can facilitate the establishment of disciplinary interoperability frameworks. Being problem-driven is also a key factor of success for building bridges to enable interdisciplinary research.Comment: Proceedings of the session "Building a disciplinary, world-wide data infrastructure" of SciDataCon 2016, held in Denver, CO, USA, 12-14 September 2016, to be published in ICSU CODATA Data Science Journal in 201

Publishing and sharing multi-dimensional image data with OMERO

Imaging data are used in the life and biomedical sciences to measure the molecular and structural composition and dynamics of cells, tissues, and organisms. Datasets range in size from megabytes to terabytes and usually contain a combination of binary pixel data and metadata that describe the acquisition process and any derived results. The OMERO image data management platform allows users to securely share image datasets according to specific permissions levels: data can be held privately, shared with a set of colleagues, or made available via a public URL. Users control access by assigning data to specific Groups with defined membership and access rights. OMERO’s Permission system supports simple data sharing in a lab, collaborative data analysis, and even teaching environments. OMERO software is open source and released by the OME Consortium at www.openmicroscopy.org

Qualitative Measures of Equity in Small Groups

We investigate the utility of two qualitative measures of equity. Our data are videos of groups of first-generation and Deaf or hard-of-hearing students in a pre-matriculation university program designed to help them persist in STEM fields by developing their metacognitive practices. We analyze video data of students in small groups trying to accomplish various tasks. We analyze how groups engage with proposed ideas (inchargeness) and create a space of open sharing (civility). By capturing different aspects of each group, these measures combine to help our understanding of what an equitable group could look like.Comment: Accepted to International Conference of the Learning Sciences (ICLS) 201

Open Content in Open Context

This article presents the challenges and rewards of sharing research content through a discussion of Open Context, a new open access data publication system for field sciences and museum collections. Open Context is the first data repository of its kind, allowing self-publication of research data, community commentary through tagging, and clear citation and stable hyperlinks, and Creative Commons licenses that make reusing content legal and easy.The Nov-Dec 2007 issue of Educational Technology magazine is an entire special issue dedicated to "Opening Educational Resources." A series of articles in this issue highlight open educational models, including OpenCourseWare, Connexions and this piece on Open Context, co-authored by Sarah Whitcher Kansa and Eric Kansa