Authors : Michele Nuijten, Jeroen Borghuis, Coosje Veldkamp, Linda Alvarez, Marcel van Assen, Jelte Wicherts
In this paper, we present three studies that investigate the relation between data sharing and statistical reporting inconsistencies. Previous research found that reluctance to share data was related to a higher prevalence of statistical errors, often in the direction of statistical significance (Wicherts, Bakker, & Molenaar, 2011).
We therefore hypothesized that journal policies about data sharing and data sharing itself would reduce these inconsistencies. In Study 1, we compared the prevalence of reporting inconsistencies in two similar journals on decision making with different data sharing policies.
In Study 2, we compared reporting inconsistencies in articles published in PLOS (with a data sharing policy) and Frontiers in Psychology (without a data sharing policy). In Study 3, we looked at papers published in the journal Psychological Science to check whether papers with or without an Open Practice Badge differed in the prevalence of reporting errors.
Overall, we found no relationship between data sharing and reporting inconsistencies. We did find that journal policies on data sharing are extremely effective in promoting data sharing.
We argue that open data is essential in improving the quality of psychological science, and we discuss ways to detect and reduce reporting inconsistencies in the literature.
Authors : Devan Ray Donaldson, Shawn Martin, Thomas Proffen
Even though the importance of sharing data is frequently discussed, data sharing appears to be limited to a few fields, and practices within those fields are not well understood. This study examines perspectives on sharing neutron data collected at Oak Ridge National Laboratory’s neutron sources.
Operation at user facilities has traditionally focused on making data accessible to those who create them. The recent emphasis on open data is shifting the focus to ensure that the data produced are reusable by others.
This mixed methods research study included a series of surveys and focus group interviews in which 13 data consumers, data managers, and data producers answered questions about their perspectives on sharing neutron data.
Data consumers reported interest in reusing neutron data for comparison/verification of results against their own measurements and testing new theories using existing data. They also stressed the importance of establishing context for data, including how data are produced, how samples are prepared, units of measurement, and how temperatures are determined.
Data managers expressed reservations about reusing others’ data because they were not always sure if they could trust whether the people responsible for interpreting data did so correctly.
Data producers described concerns about their data being misused, competing with other users, and over-reliance on data producers to understand data. We present the Consumers Managers Producers (CMP) Model for understanding the interplay of each group regarding data sharing.
We conclude with policy and system recommendations and discuss directions for future research.
Open access to research data has been described as a driver of innovation and a potential cure for the reproducibility crisis in many academic fields. Against this backdrop, policy makers are increasingly advocating for making research data and supporting material openly available online.
Despite its potential to further scientific progress, widespread data sharing in small science is still an ideal practised in moderation. In this article, we explore the question of what drives open access to research data using a survey among 1564 mainly German researchers across all disciplines.
We show that, regardless of their disciplinary background, researchers recognize the benefits of open access to research data for both their own research and scientific progress as a whole. Nonetheless, most researchers share their data only selectively.
We show that individual reward considerations conflict with widespread data sharing. Based on our results, we present policy implications that are in line with both individual reward considerations and scientific progress.
This paper reflects on the relation between international debates around data quality assessment and the diversity characterising research practices, goals and environments within the life sciences.
Since the emergence of molecular approaches, many biologists have focused their research, and related methods and instruments for data production, on the study of genes and genomes.
While this trend is now shifting, prominent institutions and companies with stakes in molecular biology continue to set standards for what counts as ‘good science’ worldwide, resulting in the use of specific data production technologies as proxy for assessing data quality.
This is problematic considering (1) the variability in research cultures, goals and the very characteristics of biological systems, which can give rise to countless different approaches to knowledge production; and (2) the existence of research environments that produce high-quality, significant datasets despite not availing themselves of the latest technologies.
Ethnographic research carried out in such environments evidences a widespread fear among researchers that providing extensive information about their experimental set-up will affect the perceived quality of their data, making their findings vulnerable to criticisms by better-resourced peers. T
hese fears can make scientists resistant to sharing data or describing their provenance. To counter this, debates around Open Data need to include critical reflection on how data quality is evaluated, and the extent to which that evaluation requires a localised assessment of the needs, means and goals of each research environment.
The research was aimed at evaluating how research data are being managed in research institutions in Zimbabwe. The study also sought to assess the challenges that are faced in research data management by research institutions in Zimbabwe.
Twenty five institutions of higher learning and other organisations that deal with research were selected using purposive sampling to participate in the study.
An online questionnaire on SurveyMonkey was sent to the selected participants and telephone interviews were done to follow up on participants who failed to respond on time. Data that were collected using interviews were entered manually into SurveyMonkey for easy analysis.
It was found out that proper research data management is not being done. Researchers were managing their own research data. Most of the research data were in textual and spreadsheet format. Graphical, audio, video, database, structured text formats and software applications research data were also available.
Lack of guidelines on good practice, inadequate human resources, technological obsolescence, insecure infrastructure, use of different vocabulary between librarians and researchers, inadequate financial resources, absence of research data management policies and lack of support by institutional authorities and researchers negatively impacted on research data management.
Authors recommend the establishment of research data repositories and use of existing research data repositories that are registered with the Registry of Research Data Repositories to ensure that research data standards are adhered to when doing research.
Authors : Adam Kriesberg, Kerry Huller, Ricardo Punzalan, Cynthia Parr
The 2013 Office of Science and Technology Policy (OSTP) Memo on federally-funded research directed agencies with research and development budgets above $100 million to develop and release plans to increase and broaden access to research results, both published literature and data.
The agency responses have generated discussion and interest but are yet to be analyzed and compared. In this paper, we examine how 19 federal agencies responded to the memo, written by John Holdren, on issues of scientific data and the extent of their compliance to the directives outlined in the memo.
We present a varied picture of the readiness of federal science agencies to comply with the memo through a comparative analysis and close reading of the contents of these responses.
While some agencies, particularly those with a long history of supporting and conducting science, scored well, other responses indicate that some agencies have only taken a few steps towards implementing policies that comply with the memo.
These results are of interest to the data curation community as they reveal how different agencies across the federal government approach their responsibilities for research data management, and how new policies and requirements might continue to affect scientists and research communities.
Data has become more and more ubiquitous in the research context. As a result, a growing number of services are created to analyze, store and share research data. This has induced the Research Data Working Group of the Digital Scientific Library (BSN10) to launch an inventory of French research data management services, funded by the Ministry of Higher Education and Research.
The inventory covers all services that are managed by French institutions and infrastructures and dedicated to public research teams from all fields. Sixty services, provided by forty-five structures, have already been identified and analyzed.
The paper describes the methodology used to carry out the inventory and analyzes these first results by service type, scope and research field. It also emphasizes the heterogeneous and emergent nature of the inventoried services.