2022 marked the Research Data Access and Preservation (RDAP) Summit's second fully virtual conference, which focused on the theme of Envisioning an Inclusive Data Future . Presenters shared perspectives on new and emerging services, as well as observations of existing and prior practices, and strategies for re-envisioning these activities. The Summit built upon last year’s theme of Radical Change and Data, which encouraged presenters and attendees to consider the intersections between data and social change. In this special issue’s commentary, Inclusion in Data: Incorporating DEIA Components into Research Data Services Practices , Chelsea H. Barrett reflects on the RDAP 2022 Summit, highlighting the role of data management professionals in incorporating DEIA into research projects and research data services. As the amount of available data continuously expands, the supports necessary to ensure that these data are collected, managed, communicated and disseminated in inclusive, ethical ways require breadth and depth of services and expertise. Several presentations throughout the Summit described the complexities, opportunities and realities of implementing and sustaining increasingly specialized and in-demand data services.

This issue underscores the unique power of research data communities at academic libraries in developing researcher skill and institutional capacity. There's no "I" in Research Data Management by Alisa B. Rod, Biru Zhou, and Marc-Etienne Rousseau presents a case study of a large research institution. The institution is using its library as a centralized host for a series of data management panels and support services that included cross-campus partners such as the Vice-Principal of Research and Innovation (VPRI), IT Services, and Research Ethics units. A collaborative approach between library staff and their counterparts in other campus units has been instrumental to successfully leveraging a shared ticketing system to support researcher queries relatively seamlessly.

The complexity of collaboration is highlighted in Data Management Librarians Role in a Large Interdisciplinary Scientific Grant for PFAS Remediation: Considerations and Recommendations by Jennifer Chaput and Renee Walsh, which describes the practical challenges associated with librarians participating as co-Principal Investigators on large, grant-funded initiatives. The authors describe a Superfund research center project proposal focused on harm reduction and remediations of poly- and perfluoroalkyl-substances (PFAS or PFOA) contamination. The librarians were members of the Data Management and Analysis Core, which focused on ensuring the clarity, utility, and interoperability of research data across all aspects of the project. The authors highlight how the organizational structures of libraries differ from academic departments, and how the different responsibilities and job classifications of librarians, as opposed to faculty colleagues, can potentially lead to misunderstandings and tension.

Collaborative approaches can also be an effective mechanism for developing community, as is explored in Developing a Data Fellowship Program and Peer-to-Peer Support Model by Nicholas Ruhs. The author describes developing a STEM fellowship program at their library that was built around two main components of fellowship work: direct peer-to-peer student consultation for data support and instruction, and professional development and learning opportunities for the student fellows. Scaffolding this new program from existing peer-training models in the library’s instruction program led to a well-integrated launch of this new program, and the author highlights several areas for future growth.

Collaboration underpinned multiple approaches to data education and outreach. Developing a Centralized Hub for Research Data Services Trainings and Resources in Health Sciences Contexts introduced available training, curriculum, and learning resources. Peace Ossom Williamson notes that these trainings are widely available and can be accessed through the National Center for Data Services, which was established within The Network of the National Library of Medicine. These resources, which include a data glossary, data videos, and continuing education courses, promote practices that support data sharing and data ethics while providing tools for data discovery and reuse.

The value of open science, and the role of research data services in advocacy for open science, has been a consistent theme through many RDAP summits. In The Open Science of Deep Learning: Three Case Studies , Chreston Miller, Leah Hamilton, and Jacob Lahne discuss the importance of making data, code, and models openly available in deep learning projects. Deep learning, a subset of machine learning, involves algorithms which are modeled to behave as the human brain does in order to mimic some of the ways in which humans learn. In this paper, Miller et al. discuss the potential of using open access deep learning resources in research projects by presenting three case studies. Each case study showcases workflows or tools that can be applied in other projects which use deep learning algorithms or deep learning models. The authors introduce open access resources throughout their article.

In addition to emphasizing the importance of open science and scholarship as an educational focus, two papers in this issue describe data sharing behaviors of researchers. In Show me the data! Data sharing practices demonstrated in published research at the University of Massachusetts Chan Medical School , Tess Grynoch and Kimberly MacKenzie explore the data sharing practices of researchers at their university, examining both if and how research data are published. In addition, the authors investigate the trends highlighted in their findings with National Institutes of Health policies and guidelines, finding that data from areas in which there are more granular and direct guidelines (such as genomic data) were more commonly shared. Exploration of policies continues in the article Are Institutional Research Data Policies in the US Supporting the FAIR Principles? A Content Analysis by Clara Llebot and Diana J. Castillo. The authors here discuss the relationships between institutional data policies and the FAIR principles, exploring current implementations. The authors also discuss missed opportunities and offer suggestions for further developing policies.

The 2022 RDAP summit illustrated the variety of ways research data professionals are building new service models while deepening and diversifying their offerings to reflect the needs of their communities. Next year’s RDAP theme, Building on Experience: Centering Communities in Data Creation and Access , is a continuation of the ongoing conversation, as presenters are encouraged to consider how we, as research data professionals, can engage with a wider range of individuals and groups, and how we can build community within our own unique environments.