PsyCuraDat: Designing a User-Oriented Curation Standard for Behavioral Psychological Research Data.
TL;DR: In this paper, the authors propose a standard for behavioral psychological research data, which is oriented towards the requirements of the psychological research process, thus considering the needs of researchers in their role as data providers and data users.
Abstract: Starting from the observation that data sharing in general and sharing of reusable behavioral data in particular is still scarce in psychology, we set out to develop a curation standard for behavioral psychological research data rendering data reuse more effective and efficient. Specifically, we propose a standard that is oriented towards the requirements of the psychological research process, thus considering the needs of researchers in their role as data providers and data users. To this end, we suggest that researchers should describe their data on three documentation levels reflecting researchers’ central decisions during the research process. In particular, these levels describe researchers’ decisions on the concrete research design that is most suitable to address the corresponding research question, its operationalization as well as a precise description of the subsequent data collection and analysis process. Accordingly, the first documentation level represents, for instance, researchers’ decision on the concrete hypotheses, inclusion/exclusion criteria and the number of measurement points as well as a conceptual presentation of all substantial variables included in the design. On the second level these substantial variables are presented within an extended codebook allowing for the linkage between the conceptual research design and the actually operationalized variables as presented within the data. Finally, the third level includes all materials, data preparation and analyses scripts as well as a detailed procedure graphic that allows the data user to link the information from all three documentation levels at a single glance. After a comprehensive presentation of the standard, we will offer some arguments for its integration into the psychological research process.
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14 Mar 2022
TL;DR: ACM Reference Format: Toine Bogers, Maria Gäde, Mark Hall, Marijn Koolen, Vivien Petras, and Paul Thomas.
Abstract: ACM Reference Format: Toine Bogers, Maria Gäde, Mark Hall, Marijn Koolen, Vivien Petras, and Paul Thomas. 2022. ThirdWorkshop on Building towards Information Interaction and Retrieval Resources Re-use (BIIRRR 2022). In Proceedings of the 2022 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR ’22), March 14–18, 2022, Regensburg, Germany. ACM, New York, NY, USA, 3 pages. https://doi.org/10.1145/3498366.3505838
1 citations
DOI•
01 Jan 2021
TL;DR: This research was funded by the Federal Ministry of Education and Research (BMBF), funding code: 16QK08.
Abstract: This research was funded by the Federal Ministry of Education and Research (BMBF), funding code: 16QK08.
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Stanford University1, Cognition and Brain Sciences Unit2, The Mind Research Network3, Nathan Kline Institute for Psychiatric Research4, Montreal Neurological Institute and Hospital5, University of Oxford6, Wellcome Trust Centre for Neuroimaging7, Dartmouth College8, National Institutes of Health9, Otto-von-Guericke University Magdeburg10, University of California, Irvine11, Shandong University12, University of Warwick13, MIND Institute14, Lawrence Berkeley National Laboratory15, Helen Wills Neuroscience Institute16, University of Washington17, Georgia State University18, California Institute of Technology19
TL;DR: The Brain Imaging Data Structure (BIDS) is developed, a standard for organizing and describing MRI datasets that uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.
Abstract: The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.
1,037 citations
TL;DR: This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information, focusing on the categories of terms that define the standard, differences between simple and relational DarwinCore, how the standard has been implemented and the community processes that are essential for maintenance and growth of the standard.
Abstract: Biodiversity data derive from myriad sources stored in various formats on many distinct hardware and software platforms. An essential step towards understanding global patterns of biodiversity is to provide a standardized view of these heterogeneous data sources to improve interoperability. Fundamental to this advance are definitions of common terms. This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information. We focus on the categories of terms that define the standard, differences between simple and relational Darwin Core, how the standard has been implemented, and the community processes that are essential for maintenance and growth of the standard. We present case-study extensions of the Darwin Core into new research communities, including metagenomics and genetic resources. We close by showing how Darwin Core records are integrated to create new knowledge products documenting species distributions and changes due to environmental perturbations.
767 citations
TL;DR: The resulting recommendations contain standards for all journal articles, and more specific standards for reports of studies with experimental manipulations or evaluations of interventions using research designs involving random or nonrandom assignment.
Abstract: In anticipation of the impending revision of the Publication Manual of the American Psychological Association, APA's Publications and Communications Board formed the Working Group on Journal Article Reporting Standards (JARS) and charged it to provide the board with background and recommendations on information that should be included in manuscripts submitted to APA journals that report (a) new data collections and (b) meta-analyses. The JARS Group reviewed efforts in related fields to develop standards and sought input from other knowledgeable groups. The resulting recommendations contain (a) standards for all journal articles, (b) more specific standards for reports of studies with experimental manipulations or evaluations of interventions using research designs involving random or nonrandom assignment, and (c) standards for articles reporting meta-analyses. The JARS Group anticipated that standards for reporting other research designs (e.g., observational studies, longitudinal studies) would emerge over time. This report also (a) examines societal developments that have encouraged researchers to provide more details when reporting their studies, (b) notes important differences between requirements, standards, and recommendations for reporting, and (c) examines benefits and obstacles to the development and implementation of reporting standards.
471 citations
TL;DR: It is found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data.
Abstract: Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.
349 citations
TL;DR: Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors, while an examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines.
Abstract: The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines. We distributed surveys to a multinational sample of scientific researchers at two different time periods (October 2009 to July 2010 and October 2013 to March 2014) to observe current states of data sharing and to see what, if any, changes have occurred in the past 3–4 years. We also looked at differences across age, geographic, and discipline-based groups as they currently exist in the 2013/2014 survey. Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors. However, there is also increased perceived risk associated with data sharing, and specific barriers to data sharing persist. There are also differences across age groups, with younger respondents feeling more favorably toward data sharing and reuse, yet making less of their data available than older respondents. Geographic differences exist as well, which can in part be understood in terms of collectivist and individualist cultural differences. An examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines. Implications of these findings include the continued need to build infrastructure that promotes data sharing while recognizing the needs of different research communities. Moving into the future, organizations such as DataONE will continue to assess, monitor, educate, and provide the infrastructure necessary to support such complex grand science challenges.
328 citations