Data Depositors Research Articles

RCSB Protein Data Bank: supporting research and education worldwide through explorations of experimentally determined and computationally predicted atomic level 3D biostructures.

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules (e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

NATIONAL ADDICTION AND HIV DATA ARCHIVE PROGRAM: DEVELOPING AN APPROACH FOR REUSE OF SENSITIVE AND CONFIDENTIAL DATA.

Sharing data produced through health research projects has been increasingly recognized as a way to advance science more rapidly by facilitating discovery and increasing rigor and reproducibility. Much of the data collected from human subjects includes sufficient sociodemographic detail and/or covers sensitive topics, and thus requires restricted data management and sharing practices. Over the last two decades, scientific organizations, presidential memoranda, and other sources have all called for increasing opportunities to share data. Recognizing the value of shared data, the National Institutes of Health issued a new Data Management and Sharing Policy, effective January 25, 2023. Prior to this updated policy, in 2009, the National Institute on Drug Abuse recognized the value of sharing data and established an archive, the National Addiction and HIV Data Archive Program. This program focused on sharing data, often highly sensitive, generated from social and behavioral addiction research, including quantitative and qualitative assessments as well as biomarker and imaging data. NAHDAP has developed practices and curation standards to ensure datasets are improved and usable, and provides technical assistance for both data depositors and users. We share three key lessons learned working to disseminate sensitive data over the last 13 years, including (1) protecting the confidentiality of human subjects; (2) ensuring careful consideration of costs for archiving data requiring protection ; and (3) providing support to facilitate the discovery and use of the data.

Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide.

Depositing Data: A Usability Study of the Texas Data Repository

Objective: The purpose of this study is to examine the usability of the Texas Data Repository (TDR) for the data depositors who are unfamiliar with its interface and use the results to improve user experience. Methods: This mixed-method research study collected qualitative and quantitative data through a pre-survey, a task-oriented usability test with a think-aloud protocol, and an exit questionnaire. Analysis of the quantitative (i.e., descriptive statistics) and qualitative data (e.g., content analysis of the thinking-aloud protocols) were employed to examine the TDR’s usability for first-time data depositors at Texas A&M University. Results: While the study revealed that the users were generally satisfied with their experience, the data suggest that a majority of the participants had difficulty understanding the difference between a dataverse collection and dataset, and often found adding or editing metadata overwhelming. The platform’s tiered model for metadata description is core to its function, but many participants did not have an accurate mental model of the platform, which left them scrolling up and down the page or jumping back and forth between different tabs and pages to perform a single task. Based on the results, the authors made some recommendations. Conclusions: While this paper relies heavily on the context of the Harvard Dataverse repository platform, the authors posit that any self-deposit model, regardless of platform, could benefit from these recommendations. We noticed that completing various metadata fields in the TDR required participants to pivot their mindset from a data creator to that of a data curator. Moreover, the methods used to investigate the usability of the repository can be used to develop additional studies in a variety of repository and service model contexts.

RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.

Sharing research data to comply with a journal policy: Experience of a first-time depositor

Background Journals in health sciences increasingly require or recommend that authors deposit the data from their research in open repositories. The rationale for publicly available data is well understood, but many researchers lack the time, knowledge, and skills to do it well, if at all. There are few descriptions of the pragmatic process a researcher author undertakes to complete the open data deposit in the literature. When my manuscript for a mixed methods study was accepted by a journal that required shared data as condition of publication, I proceeded to comply despite uncertainty with the process. Purpose The purpose of this work is to describe the experience of an information science researcher and first-time data depositor to complete an open data deposit. The narrative illustrates the questions encountered and choices made in the process. Process Methods To begin the data deposit process, I found guidance from the accepting journal’s policy and rationale for its shared data requirement. A checklist of pragmatic steps from an open repository provided a framework used to outline and organize the process. Process steps included organizing data files, preparing documentation, determining rights and licensing, and determining sharing and permissions. Choices and decisions included which data versions to share, how much data to share, repository choice, and file naming. Processes and decisions varied between the quantitative and qualitative data prepared. Results Two datasets and documentation for each were deposited in the Figshare open repository, thus meeting the journal policy requirements to deposit sufficient data and documentation to replicate the results reported in the journal article, and also meeting the deadline to include a Data Availability Statement with the published article. Conclusion This experience illustrated some practical data sharing issues faced by a librarian author seeking to comply with a journal data sharing policy requirement for publication of an accepted manuscript. Both novice data depositors and data librarians may find this individual experience useful for their own work and the advice they give to others.

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

An Exploratory Analysis of Social Science Graduate Education in Data Management and Data Sharing

Effective data management and data sharing are crucial components of the research lifecycle, yet evidence suggests that many social science graduate programs are not providing training in these areas. The current exploratory study assesses how U.S. masters and doctoral programs in the social sciences include formal, non-formal, and informal training in data management and sharing. We conducted a survey of 150 graduate programs across six social science disciplines, and used a mix of closed and open-ended questions focused on the extent to which programs provide such training and exposure. Results from our survey suggested a deficit of formal training in both data management and data sharing, limited non-formal training, and cursory informal exposure to these topics. Utilizing the results of our survey, we conducted a syllabus analysis to further explore the formal and non-formal content of graduate programs beyond self-report. Our syllabus analysis drew from an expanded seven social science disciplines for a total of 140 programs. The syllabus analysis supported our prior findings that formal and non-formal inclusion of data management and data sharing training is not common practice. Overall, in both the survey and syllabi study we found a lack of both formal and non-formal training on data management and data sharing. Our findings have implications for data repository staff and data service professionals as they consider their methods for encouraging data sharing and prepare for the needs of data depositors. These results can also inform the development and structuring of graduate education in the social sciences, so that researchers are trained early in data management and sharing skills and are able to benefit from making their data available as early in their careers as possible.

Abstract 2489: Enabling data access, sharing, collaborative and reproducible research: The Frederick National Laboratory for Cancer Research (FNLCR) data coordinating center

Abstract The Frederick National Laboratory for Cancer Research hosts a Data Coordinating Center and Toolset (the Metadata Designer plus Validator) hereafter referred to as the DCC that embodies a scalable, next-generation biological and cancer research data repository that is flexible, intuitive, and adaptive. The DCC provides integrated management of datasets across all deposited projects making its data more accessible and easily reusable by the cancer research community. The DCC stores and manages access to data, enabling researchers or data depositors to grant controlled access only to specific collaborators while maintaining a user-specified embargo on deposited datasets. The DCC enables a data access and sharing capability aimed to facilitate the development of new biological insights. The DCC implements the ISA (Investigation-Study-Assay) paradigm. The ISA framework provides a rich description of experimental metadata that is agnostic and irrespective of sample characteristic, technology or measurement type. It provides clear and simple sample-to-data relationships that enables resulting data and discoveries to be reproducible and reusable. These data are in the standard Investigation-Study-Assay tab-delimited format (ISA-TAB) format, which describes a scientific investigation, its study or studies, and each study's assay(s). The DCC portal is a public repository of experiment-related information describing cancer and biomedical research investigations. The portal can be used to browse, search, and access data from uploaded datasets. Through its stand-alone Toolset (Metadata Designer plus Validator), the DCC offers data depositors and researchers a simple interface to create and validate ISA-Tab compatible metadata associated with data generated in their research. Deriving new insights from aggregates of datasets and the need for reproducible research has never been more apparent. However, a fundamental requirement for these is a comprehensive metadata annotation and documentation of the research processes - an art that is elusive to researchers. Beyond the resultant publication is the data and metadata. These two basic ingredients are building blocks for a successful reproducible research project. In addition, appropriately curated data and metadata are invaluable resources for meta-analyses of seemingly disparate research studies. Further emphasizing the importance of these basic elements, are the principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) - to guide data producers and publishers around obstacles and help maximize added-value gained from published studies. The DCC provides a much-needed resource to the research community for simplifying the sharing of data sets that meet these principles. The DCC portal is located at https://cssi-dcc.nci.nih.gov/cssiportal/ Citation Format: Paul Aiyetan, Paul Donovan, David Mott, Matthew Starr, Rajani Kuchipudi, Mahesh Yelisetti, Debra Hope, Corinne Zeitler, Uma Mudunuri, Andrew Quong. Enabling data access, sharing, collaborative and reproducible research: The Frederick National Laboratory for Cancer Research (FNLCR) data coordinating center [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2489.

RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, rcsb.org), the US data center for the global PDB archive, serves thousands of Data Depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without usage restrictions to more than 1 million rcsb.org Users worldwide and 600 000 pdb101.rcsb.org education-focused Users around the globe. PDB Data Depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy and 3D electron microscopy. PDB Data Consumers include researchers, educators and students studying Fundamental Biology, Biomedicine, Biotechnology and Energy. Recent reorganization of RCSB PDB activities into four integrated, interdependent services is described in detail, together with tools and resources added over the past 2 years to RCSB PDB web portals in support of a ‘Structural View of Biology.’

SAGE: supporting secondary data analysis and expediting knowledge mobilization with linked administrative, service delivery, and research data

IntroductionThe cultural revolution of data sharing is becoming a global movement. It allows for scientific replication and verification of research results, avoiding research duplication, and enabling greater transparency and knowledge mobilization with a relatively low cost. However, privacy protection and data security are critical concerns for human-subject related data sharing.
 Objectives and ApproachIn order to facilitate data sharing and engage various stakeholders to better inform policy and practice while protecting privacy, SAGE (Secondary Analysis to Generate Evidence) was established by PolicyWise for Children and Families. It is a collaborative data repository platform that connects stakeholders through secondary use of data. SAGE was built to link, manage, and share research data, community service data, and administrative data related to health and social well-being. Governance and technical processes are in place to ensure that data depositors are involved in decision-making, and data accessed by collaborators are secured and re-identification risks assessed.
 ResultsSAGE has been in operation for over a year. Through engagement with the research and non-profit communities, SAGE now offers ten data assets. Discovery is facilitated through well-documented metadata through NADA and Dataverse. Six new collaborative projects have been initiated through SAGE. SAGE is working actively with local non-profits to liberate data to generate evidence and collaborate with each other on common goals. SAGE has helped these organizations understand the legal and legislative barriers to data sharing, and build the technical capacity to further this goal. Discussions are underway with Alberta public entities on how SAGE can support the linkage and governance processes in the use of administrative data.
 Conclusion/ImplicationsSAGE is putting the governance processes and security practices in place to fill a need for a facilitated data sharing model for sensitive data. SAGE is supporting the cultural shift towards data sharing and reuse by fostering trust and collaboration among researchers, non-profit and government ministries.

The Limits of sharing: Controlled data collections

We investigated 24 web-based data repositories with “controlled collections” to determine why and how repositories control access to and use of data. We selected our sample of data repositories from across scholarly and scientific disciplines in order to investigate differences between fields. Using content analysis and surveys, we collected data about current repository policies and practices and underlying motivations for controlling data access and use. Looking across all disciplines, we found no overarching reason for restricting access to data, but “avoiding misuse” was listed most frequently. Ensuring attribution was the dominant reason for controlling use of data. Observed between-field findings are tentative given the small number of repositories in some fields that met study criteria; however, our data do suggest some interesting differences. We also found cross-disciplinary patterns regarding methods for controlling access to and use of data. Better understanding of and attention to access and use control interests may allow repositories to attract more data depositors and ultimately increase the amount of data that can be shared.

Digital elevation models for research: UK datasets, copyright and derived products

Abstract The UK is served by a wide range of digital elevation models (DEMs) that have a variety of technical specifications from several different vendors. The abundance of data presents researchers with a complex range of choices dependent upon their application (and therefore ‘fitness-for-purpose’) and desired use of intellectual property rights (IPR). This paper explores current DEM datasets of the UK and presents their use within the context of claimed copyright and IPR. In particular, responsibilities placed upon grant holders for the lodgement of research outputs by UK Research Councils places new emphasis upon data access, derived data and data re-use. The complex interplay of rights between research output stakeholders (data suppliers, data creators, data users) presents a difficult scenario for both data repositories and data depositors.

The Protein Data Bank: A Case Study in Management of Community Data

As the sole repository for three-dimensional structure data of biological macromolecules, the Protein Data Bank (PDB) is an important resource for research in the academic, pharmaceutical, and biotechnology sectors. Over the years, the methods and speed of structure determination have changed as technology has improved. At the same time the methods for data collection, archiving, and distribution of the structural data in the PDB have also evolved. Concurrently, the community of data depositors and users has expanded. As of October 2003, the PDB archive contains approximately 23,000 released structures and the website receives over 160,000 hits per day. The lessons learned from the development of the PDB may be applicable to the ongoing development of new data and knowledge resources in proteomics.