From a six-month period in 2016-2018, \(n=36\) authors contacted and \(n=24\) responded.
Question | Early career | Senior |
---|---|---|
Any prior experience with posting/sharing data? | 40% | 30% |
Does your institution provide resources for preparation/posting of data? | 80% | 80% |
What, if any, of the below concerns do you have about data sharing if CD were to require data from published studies be made available to other researchers? | Early career | Senior |
---|---|---|
IRB | 50% | 89% |
Jeopardizing trust of participants/communities/violating consent | 90% | 77% |
Risk of scooping planned research | 50% | 56% |
Taking time away from my research | 50% | 56% |
Concerns rated lower in importance: financial cost, fairness/equal partnership, trust in collaboration beyond data sharing.
“The advancement of detailed and diverse knowledge about the development of the world’s children is essential for improving the health and well-being of humanity…”
“We regard scientific integrity, transparency, and openness as essential for the conduct of research and its application to practice and policy…”
https://www.srcd.org/about-us/policy-scientific-integrity-transparency-and-openness
“By scientific integrity, we mean the ‘active adherence to the ethical practices and professional standards essential for the responsible practice of research.’”
“Scientific integrity includes the core values of openness, objectivity, fairness, honesty, accountability and stewardship at every step in the scientific enterprise.”
“By transparency, we mean the clear, accurate, and complete reporting of all components of scientific research.”
“Transparency includes, but is not limited to, reporting the following: participant characteristics, how participants were identified, recruited, and screened, and by what criteria they were included or excluded; how and when participants were tested, measured, or observed…”
“…what apparatus, equipment, or instruments were employed; what transformations the measures or observations underwent; what material and financial resources supported the research.”
“By openness, we refer to the sharing of scientific resources, such as methods, measures, and data, in order to further scientific advances.”
“Scientific openness ranges from provision of materials to other scientists, at no cost or specific obligation, to the depositing of scientific data in data sharing repositories”
Issue | Response |
---|---|
Can confidentiality of shared data be protected? | Yes! |
e.g., Databrary successfully stores identifiable video + other data | |
Identifiable data sharing requires participant permission | |
Repositories ‘safer’ than individual websites, institutional archives | |
Store in repository with restricted access | |
e.g., ICSPR largest and oldest data repository in social sciences |
Issue | Response |
---|---|
Unforseeable risks of ‘indefinite’ storage? | Seek permission to share using standard templates |
Data reuse maximizes benefits of participation |
Issue | Response |
---|---|
Can data be truly ‘de-identified’? | Consider restricted data sharing even for ‘de-identified’ data |
Issue | Response |
---|---|
Do participants understand sharing risks? | Perhaps not fully, but we can minimize risks |
Risks must be balanced with benefits (Brakewood & Poldrack, 2013) | |
Many fields have long & successful histories of sharing data | |
Virtues of standard templates for seeking permission |
Issue | Response |
---|---|
How do I talk to participants about sharing? | Databrary has sample scripts and video examples |
Issue | Response |
---|---|
Preparing data & materials to share takes time | Prepare to share from the beginning of a study |
Inconsistent institutional infrastructure & support | Researchers & SRCD can advocate for more support, provide infrastructure & training |
Issue | Response |
---|---|
Unfair burden on researchers with limited resources | SRCD policy recommends sharing, but does not require |
SRCD training & technical assistance | |
Use and support ‘free’ data repositories (Databrary, ICSPR, OSF) |
Issue | Response |
---|---|
Who bears cost of curation? | Repositories can help |
Need stronger support from funders | |
Reproducible workflows and tools (RMarkdown; Jupyter notebooks) make curation easier | |
NICHD grants for curation |
Issue | Response |
---|---|
Must minors be reconsented when they reach adulthood? | Open question; NICHD says not if overly burdensome + low risk; But different in EU |
Can future secondary uses be adequately described? | Better practice is to specify future uses in generic terms |
Issue | Response |
---|---|
Differences among developed/developing world, U.S. vs. Europe, etc. | SRCD should work with others toward common standards; Databrary consent one starting point |
Issue | Response |
---|---|
Other researchers will ‘scoop’ me | Share when ready (publication goes to press or end of grant period) |
Doesn’t seem to happen often in other fields that share data more often. | |
Require citation of data & materials |
Issue | Response |
---|---|
Errors will become more readily known and possibly subject to criticism | Criticing the work vs. criticizing the worker |
Early adopters will face the brunt | SRCD recommends, but does not require materials, data, code sharing |
“SRCD espouses practices that minimize potential harm to contributing participants, researchers, and the public. The value of minimizing harm takes priority over the values of increased scientific transparency and openness.”
“SRCD further acknowledges the need to protect researchers from professional harm that can occur when requests for scientific transparency and openness veer into attacks on the integrity of researchers themselves or result in significant, new, or unfunded burdens that limit progress in scholarship.”
Issue | Response |
---|---|
Must shared analysis code be reviewed alongside manuscript? | Review of materials, data, code optional |
Must publishers provide infrastructure for sharing? | Possible partnerships with data repositories |
Issue | Response |
---|---|
Mandating preregistration may limit exploratory analyses | Sharing, preregistration, replication recommended and publicized but not required |
Do multiple uses of the same data increase the risk of false positive findings | Different analysts may approach same question from different perspectives |
Preregistration can help |
Issue | Response |
---|---|
Does emphasizing openness devalue diverse modes of scholarship? | SRCD embraces diversity in scholarship |
One size does not fit all |
“SRCD values diverse forms of research, including those carried out on primary data collected by researchers themselves and on secondary data from data repositories, public or non-public sources (e.g., non-author collaborators), and private or proprietary data.”
“Authors should appropriately cite all data sources, program code, materials, and methods used in research.”
“Sharing materials used in research in child development, including questionnaires, stimuli, coding systems, and so forth, is vital to maximize the reproducibility of findings, improve scientific rigor, and develop new knowledge.”
“…sharing the materials used in research is central to promoting the extension and replication of research results.”
“Sharing can also help to promote greater equity by making materials available to researchers who have fewer resources. Thus, SRCD strongly encourages the sharing of research materials with other researchers to the fullest extent possible.”
“1. Information about whether or not authors agree to make research materials available is not considered as part of the review process but will be collected post-acceptance, prior to publication.”
“2. If an author agrees to make research materials available, the author should specify where that material will be made available and for what time period. Ideally materials that are not copyrighted should be placed in free, open repositories (e.g., Databrary, Dataverse, Dryad, ICSPR, OpenNeuro, OSF) and given persistent identifiers (e.g., DOI’s) to facilitate their citation and use indefinitely. For materials that are copyrighted, a link to the specific measure should be provided.”
“3. Authors agreeing to share research materials should, in the acknowledgments or the first footnote of the published paper, indicate that they will make their research materials available to other researchers and provide information about where the materials may be accessed.”
“4. SRCD would like to learn more about the barriers to transparency. Therefore, if research materials are not shared, authors will be asked to provide information during the process of preparing an accepted manuscript for publication about the reasons why research materials are not being shared. That information will be used to evaluate and improve SRCD’s policies, practices, and services, and will not be included as part of the final publication.”
“Transparency in the design and analysis of studies is vital even though changes in the context and timing of studies can complicate issues of reproducibility in child development research.”
“Authors should fully document participant characteristics, how participants were identified, recruited, and screened; by what criteria they were included or excluded; how and when participants were tested, measured, or observed;…”
…what apparatus, equipment, or instruments were employed; how human coders or observers (if any) were trained; and how reliability was estimated; among other facets of research."
“In addition to traditional text- and image-based procedural documentation, video recordings of empirical procedures may improve the transparency of some forms of child development research.”
“Widespread sharing of data associated with research in child development accelerates the pace of discovery and improves scientific rigor.”
“In some cases, shared data are essential to verify or confirm the specific findings reported in a publication (to demonstrate reproducibility) and can be built upon by other researchers who aggregate findings across the scientific literature (to validate a finding through replication).”
“SRCD strongly encourages members and authors in the society’s journals to share data openly with other researchers, without restrictions or conditions, whenever doing so poses minimal risks to participants and does not violate contractual obligations (e.g., copyright).”
“…it is important to specify how raw data were prepared for statistical analyses; what transformations measures or observations underwent (including scale construction, aggregation levels, outliers); and the steps involved in data analysis…”
“…The use of scripts or analysis code makes documenting these sorts of data analytic processes more transparent and reproducible. SRCD strongly encourages their use.”
“SRCD recognizes that achieving open sharing of diverse types of data will require flexibility based on a variety of considerations including the forms of shared data, participant consent, investigator resources, skill development, institutional barriers or facilitators, and so forth.”
“1. Information about whether or not authors agree to make data available and/or make their analytic methods available is not considered as part of the review process but will be collected post-acceptance, prior to publication.”
“2. If an author agrees to make data and/or analytic methods available, the author should specify where that material will be available. The use of free web-based data and materials repository services (e.g., Databrary, Dataverse, Dryad, ICSPR, OpenNeuro, OSF) is strongly encouraged. Analytic methods may be shared in a data repository in a code repository like GitHub, BitBucket, or SourceForge.”
“3. If data and/or analytic methods are not shared, authors will be asked to provide information during the process of preparing an accepted manuscript for publication about the reasons why data and/or analytic methods are not being shared. That information will be used for internal SRCD purposes, and will not be included in the final publication.”
“4. Authors agreeing to share data and/or analytic methods (code) should, in the acknowledgments or the first footnote of the published paper, indicate that they will make these materials available to other researchers and provide information about where the materials may be accessed.”
“The preregistration of analysis plans or entire studies can be a powerful way to improve the rigor of certain forms of child development research, especially hypothesis-driven experimental studies.”
“SRCD encourages researchers to preregister analysis plans wherever they are appropriate for their specific questions.”
“However, support for preregistration should not be viewed as diminishing the value or importance of thoroughly documented exploratory investigations or descriptive research.”
“Preregistration of studies involves registering the study design, variables, and treatment conditions. Including an analysis plan involves specification of sequence of analyses or the statistical model that will be reported. Authors choosing to preregister should indicate which independent, institutional registry was used (e.g., http://clinicaltrials.gov/, http://socialscienceregistry.org/, http://openscienceframework.org/, http://egap.org/design-registration/, http://ridie.3ieimpact.org/).”
“1. Authors should, in acknowledgments or the first footnote, indicate if they did or did not preregister the research with or without an analysis plan in an independent, institutional registry.”
“2. Information about whether an analysis plan was or was not preregistered will be included in the process of review.”
“3. If an author did preregister the research with an analysis plan, the author must: a. confirm in the text that the study was registered prior to conducting the research with links to the time-stamped preregistration(s) at the institutional registry, and that the preregistration adheres to the disclosure requirements of the institutional registry or those required for the preregistered badge with analysis plans maintained by the Center for Open Science.”
“b. report all preregistered analyses in the text, or, if there were changes in the analysis plan following preregistration, those changes must be disclosed with explanation for the changes. c. clearly distinguish in text analyses that were preregistered from those that were not, such as having separate sections in the results for confirmatory and exploratory analyses.”
“SRCD recognizes the value of conceptually grounded, well-motivated replications of important findings from empirical studies, particularly of research published in Child Development. Accordingly, the society encourages their submission.”
“Changes in the context and timing of studies (e.g. changes in sample characteristics, time of data-collection, etc.) or differences among study populations can complicate questions about the reproducibility and replicability of some forms of child development research…”
“Nevertheless, replication is a standard by which the robustness and validity of certain forms of child development research, especially empirical studies, can be evaluated.”
https://www.srcd.org/about-us/policy-scientific-integrity-transparency-and-openness
http://srcd.org/author-guidelines-Scientific-Integrity-Openness-ChildDevelopment
Also new Conflict of Interest (COI) and text recycling/plagiarims policies for CD.
Brakewood, B., & Poldrack, R.A. (2013). The ethics of secondary data analysis: Considering the application of Belmont principles to the sharing of neuroimaging data. NeuroImage, 82, 671–676. Retrieved from http://dx.doi.org/10.1016/j.neuroimage.2013.02.040
Gilmore, R. O. (2016). From big data to deep insight in developmental science. Wiley Interdisciplinary Reviews: Cognitive Science, 7(2), 112–126. Retrieved September 28, 2016, from http://onlinelibrary.wiley.com/doi/10.1002/wcs.1379/full
Gilmore, R.O., Kennedy, J.L., & Adolph, K.E. (2018). Practical solutions for sharing data and materials from psychological research. Advances in Methods and Practices in Psychological Science, 1(1), 121–130. SAGE Publications Inc. Retrieved from https://doi.org/10.1177/2515245917746500
Gilmore, R.O., & Adolph, K.E. (2017). Video can make behavioural science more reproducible. Nature Human Behavior, 1. Retrieved from https://www.nature.com/articles/s41562-017-0128
Goodman, S. N., Fanelli, D., & Ioannidis, J. P. A. (2016). What does research reproducibility mean? Science Translational Medicine, 8(341), 341ps12–341ps12. Retrieved October 9, 2016, from http://stm.sciencemag.org/content/8/341/341ps12
Mischel, W. (2011). Becoming a cumulative science. APS Observer, 22(1). Retrieved from https://www.psychologicalscience.org/observer/becoming-a-cumulative-science
Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Sert, N. P. du, Simonsohn, U., et al. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1, 0021. Retrieved January 10, 2017, from http://www.nature.com/articles/s41562-016-0021
Peng, R. (2016). A simple explanation for the replication crisis in science · Simply Statistics. Retrieved March 12, 2019, from https://simplystatistics.org/2016/08/24/replication-crisis/
This talk was produced on 2019-03-22 in RStudio version 1.1.453 using R Markdown and the reveal.JS framework. The code and materials used to generate the slides may be found at https://github.com/gilmore-lab/2019-03-22-SRCD-conversation/. Information about the R Session that produced the code is as follows:
sessionInfo()
## R version 3.5.2 (2018-12-20)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.3
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## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
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## [1] stats graphics grDevices utils datasets methods base
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## [1] Rcpp_1.0.0 revealjs_0.9 digest_0.6.18
## [4] R.methodsS3_1.7.1 magrittr_1.5 evaluate_0.13
## [7] stringi_1.3.1 R.oo_1.22.0 R.utils_2.8.0
## [10] rmarkdown_1.11 tools_3.5.2 stringr_1.4.0
## [13] xfun_0.4 yaml_2.2.0 compiler_3.5.2
## [16] htmltools_0.3.6 knitr_1.21