The State of Open Data 2019 - What Are the Key Issues in Open Data for Researchers?
In this post, Mark Hahnel presents findings from the largest continuous survey of academic attitudes to open data and suggests that as well promoting data sharing, it may also have inadvertently fed into the publish or perish culture of research.
Open Science, Open Data and Open Scholarship: European Policies to Make Science Fit for the 21st Century
Open science will make science more efficient, reliable and responsive to societal challenges. The European Commission has sought to advance Open Science policy from its inception in a holistic and integrated way, covering all aspects of the research cycle from scientific discovery and review to sharing knowledge, publishing and outreach.
How to Build a Community of Data Champions: Six Steps to Success.
Inspired by the University of Cambridge Data Champion programme, we have built a community of Data Champions to advocate for good research data management (RDM) practice within all university faculties at TU Delft. Currently, we have 47 active members and the number is increasing.
Ten Key Prerequisites to Securely Fund Open Infrastructure Today and Tomorrow - SPARC Europe
Everything we have gained by opening content and data will be under threat if we allow the enclosure of scholarly infrastructures. We propose a set of principles by which Open Infrastructures to support the research community could be run and sustained.
The State of Open Data 2019 report is the fourth in the series and includes survey results and a collection of articles from global industry experts.It is now the longest running longitudinal study on the subject, which was created in 2016 to examine attitudes and experiences of researchers working with open data - sharing it, reusing it, and redistributing it. This year's survey received a record number of survey participants with around 8,500 responses from the research community. While most trends are encouraging around the adoption and acceptance of open data, the research community is now demanding more enforcement of the mandates that have been adopted by many governments, funders, publishers and institutions around the world.The majority of researchers want funding withheld and penalties for a lack of data sharing.
Iain Hrynaszkiewicz, Publisher, Open Research, PLOS Note: the following perspective was published as part of Digital Science's annual survey and report, The State of Open Data 2019 , to coincide with global celebrations around Open Access Week. The biggest barrier to research data sharing and reuse seems to be a matter of trust, and in particular trust in what others may do with researchers' data if it is made openly available. The 2019 State of Open Data survey revealed that more than 2,000 respondents had concerns about misuse of their research data. Concerns about data misuse represent a multitude of issues; fears that errors could be found in their work, or that the data could be misinterpreted or research participant privacy be compromised. Researchers might also be concerned that their data will be reused for purposes they did not intend, such as commercial exploitation, or for misleading or inappropriate secondary analyses.1 The 2019 survey provides insights from one of the
The State of Open Data 2019 - Global Attitudes Towards Open Data
Figshare has launched its annual report The State of Open Data 2019. While most trends are encouraging around the adoption and acceptance of open data, the research community is now demanding more enforcement of the mandates that have been adopted by many governments, funders, publishers and institutions around the world.
Evaluating FAIR Maturity Through a Scalable, Automated, Community-governed Framework
Transparent evaluations of FAIRness are increasingly required by a wide range of stakeholders, from scientists to publishers, funding agencies and policy makers. We propose a scalable, automatable framework to evaluate digital resources that encompasses measurable indicators, open source tools, and participation guidelines, which come together to accommodate domain relevant community-defined FAIR assessments. The components of the framework are: (1) Maturity Indicators - community-authored specifications that delimit a specific automatically-measurable FAIR behavior; (2) Compliance Tests - small Web apps that test digital resources against individual Maturity Indicators; and (3) the Evaluator, a Web application that registers, assembles, and applies community-relevant sets of Compliance Tests against a digital resource, and provides a detailed report about what a machine "sees" when it visits that resource. We discuss the technical and social considerations of FAIR assessments, and how this translates to our community-driven infrastructure. We then illustrate how the output of the Evaluator tool can serve as a roadmap to assist data stewards to incrementally and realistically improve the FAIRness of their resources.
Implementing a Data Policy: a How-to Guide for Publishers - OASPA
OASPA is pleased to publish this guest post on the subject of open data and data sharing, providing helpful practical advice drawn from a wealth of resources, to enable publishers and editors to play a key role in the important movement to make data accessible.
The Citation Advantage of Linking Publications to Research Data
Efforts to make research results open and reproducible are increasingly reflected by journal policies encouraging authors to provide data availability statements. As a consequence of this, there has been a strong recent uptake of data availability statements, but it is still unclear what proportion of these statements actually contain well-formed links to data, and if there is an added value in providing them.
The goal of the Open Science Graphs Interest Group (OSG IG) is to build on the outcomes and broaden the challenges of the Data Description Registry Interoperability (DDRI) and Scholarly Link Exchange (Scholix) RDA Working Groups to investigate the open issues and identify solutions towards achieving interoperability between services and information models of Open Science Graph initiatives.
Do Swiss researchers share their data with other researchers and with the public? And if not, why? Which data repositories and other channels do they use for data sharing? A large-scale survey by the SNSF and swissuniversities offers some answers.