Outputs & Recommendations

"10 Things for Curating Reproducible and FAIR Research," describes the key issues of curating reproducible and FAIR research (CURE-FAIR).

23 Things: Libraries for Research Data provides an overview of practical, free, online resources and tools that you can begin using today to incorporate research data management into your practice of librarianship from the Libraries for Research Data Interest Group of the Research Data Alliance.

The provision of adoption guidelines will help implement the FAIR4RS Principles. The FAIR4RS Working Group formed subgroups to address milestones (as contained in the case statement), including a subgroup on adoption guidelines, FAIR4RS Subgroup 5.

The ICSU-WDS & RDA Publishing Data Services group proposes an approach to sharing information about the links between the literature and research data. A set of hubs will collect literature­data (as well as data­data) links from their natural communities using minor extensions to existing local procedures and, in some cases, inference. The hubs agree on an interoperability framework with a common information model and open exchange methods, optimised for exchanging information among the hubs. The hubs will serve as an enabling global information infrastructure for the development of (third party) services.

The Recommendation is also published at the following DOI: http://dx.doi.org/10.15497/RDA00002

Relevant to this recommendation is also the release of the Scholix framework by ICSU-WDS and RDA, details can be found here: https://rd-alliance.org/rda-and-icsu-wds-announce-scholix-framework-link...

Data is central to empirical linguistic research. Linguistic data comes in many different forms, and is collected and processed with a wide range of methods. Data citation recognizes the centrality of data to research. Furthermore, it facilitates verification of claims and repurposing of data for other studies.

RDA Council Strategy Subcommittee - (27 August 2016)

The CODATA/RDA Summer School in Data Science and Cloud Computing in the Developing World WG provides a framework to run a series of Summer Schools in Data Science and data sharing in low and middle income countries (LMICs) with the goal of addressing the gap in research data science skills that stops researchers from reaping the benefits of the data revolution.

As part of the Education And Training On Handling Of Research Data IG (ETHRD-IG) activities, the Learning Resource Collectors Focus Group studied the evolving landscape of learning resources on RDM topics. As we collected and listed a snapshot of current catalogues or registries of learning resources for review, we realized that a set of core characteristics could describe these types of organisations that would be useful to help people evaluate and understand the resources they offer. In addition, the identification of core characteristics could help the organisations themselves consider some of the factors that might help them build, structure, and sustain their collections and the services they offer in support of researchers and data specialists seeking learning resources on RDM and data skills topics. This document also supports the work of another ETHRD-IG focus group that recommends a set of minimal metadata elements for learning resources.

Often researchers receive a file from colleagues, follow a link, or otherwise encounter data created elsewhere that they would like to make use of in their own work. However, they may not know how to work with it, interpret it or visualise its content, being unfamiliar with the specifics of the structure and/or meaning of the data, ranging from individual observations up to complex data sets. Frequently, researchers need to stop here since it requires too much work to look for explanations, tools, and where tools exist, install them.

Defines and describes 14 features of journal research data policies and arranges these into a set of six standard policy types or tiers, which can be adopted by journals and publishers to promote data sharing in a way that encourages good practice and is appropriate for their audience's perceived needs.

Abstract

Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data.

This document describes a maturity model for FAIR assessment with assessment indicators, priorities and evaluation methods. This is useful for the normalisation of assessment approaches to enable comparison of their results.

In September 2021, the FAIR4RS WG formed subgroups to address milestones for the adoption of the FAIR4RS principles. This document is the output of subgroup 6, focused on adoption support.

The SHARC Interest Group of the Research Data Alliance was established to improve research crediting and rewarding mechanisms for scientists who wish to organise their data (and material resources) for community sharing. This requires that data are findable and accessible on the Web, and comply with shared standards making them interoperable and reusable in alignment with the FAIR principles. It takes considerable time, energy, expertise and motivation. It is imperative to facilitate the processes to encourage scientists to share their data.

This white-paper expresses common requirements of Research Communities seeking to leverage Identity Federation for Authentication and Authorisation.

The Global Open Research Commons is an Interest Group within the Research Data Alliance. The IG is working to reach a shared understanding of what a “Commons” is in the research data space; what functionality, coverage and characteristics does such an initiative require and how this can be coordinated at a global level.

Commons: A global trusted ecosystem that provides seamless access to high quality interoperable research outputs and services.

Strapline: Digital research resources for the common good.

One of the outputs of the IG is a Typology of the essential elements in a Commons.

In developing this typology, the IG identified the need to also provide a set of definitions for each of the typology elements. This diagram supplments the Typology and Definitions document, a formal statement of this typology with the associated definitions - DOI 10.15497/RDA0008

This is the draft version of the final report, post it here for group members' feedback before submit it and go through the RDA process.

Basic funding of data infrastructure may not keep pace with increasing costs. There is a need, therefore, to consider alternative cost recovery options and a diversification of revenue streams. In short: who will pay for public access to research data? The RDA/WDS Interest Group Publishing Data Cost Recovery for Data Centres aims to contribute to strategic thinking on cost recovery by conducting research to understand current and possible cost recovery strategies for data centres.

Computer actionable policies are used to enforce management, automate administrative tasks, validate assessment criteria, and automate scientific analyses. The benefits of using policies include minimization of the amount of labor needed to manage a collection, the ability to publish to the users the rules that are being used, and the ability to automate process management.

This report provides a consolidated view of the answers collected during a survey conducted in October 2020. This survey was conducted amongst members of the RDA FAIR Data Maturity Model Working Group and aimed at investigating the differences of perspectives on benefits and challenges of the FAIR assessments between members representing funders and research communities.

The Metadata Standards Directory Working Group set out to develop a directory that would enable researchers, and those who support them, to discover metadata standards that would be appropriate for documenting their research data, regardless of their academic discipline. It happened that a directory with similar aims had recently been developed independently by the UK Digital Curation Centre (DCC), so the group collaborated with the DCC on developing the directory further to achieve additional goals regarding coverage, ease of maintenance, and sustainability.

1. establish the Provenance Working Group
2. establish and maintain a list of provenance-related resources
   • listing of provenance conferences

Experts from 47 European research infrastructure initiatives and ERICs have agreed on a set of assertions about the nature, the creation and the usage of Persistent Identifiers (PIDs).

The demand for better reproducibility of research results is growing. More and more data is becoming available online. In some cases, the datasets have become so large that downloading the data is no longer feasible. Data can also be offered through web services and accessed on demand.

RDA Council Strategy Subcommittee - 8 November 2016

The DMP Common Standards WG has developed an application profile that allows to express information from traditional DMPs in a machine-actionable way. It allows for automatic exchange, integration, and validation of information provided in DMPs.

This report presents the first analysis of the Models of Data Stewardship survey completed by the Research Data Alliance Professionalising Data Stewardship Interest Group (RDA PDS-IG) in October-November 2021.

This recommendation provides a comprehensive model for actionable collections and a technical interface specification to enable client-server interaction. It also reports on first adoption and implementation efforts across communities and institutions and provides perspectives on the use of data types in connection with collection structures, highlighting pathways for possible future work.

Workflows that enable persistence, quality control and access are all crucial to enhance the possibilities for greater discoverability as well as efficient and reliable reuse of research data. Such workflows for data publishing are at the core of this analysis and working group.

Global middleware infrastructure is insufficient for robust data identification, discovery, and use. While infrastructure is emerging within sub-ecosystems such as the DOI ecosystem of services purposed for data and literature objects (i.e., DataCite, CHORUS, CrossRef), in general the layers of abstraction that have made the Internet so easy to build on, is lacking for data especially for computer (machine) automated services.

As part of the Education And Training On Handling Of Research Data IG activities, the Minimal Metadata for Learning Resources Focus Group recommends a minimal set of metadata for learning resources. By comparing and analyzing existing learning resource-related metadata schemas to find the overlaps, the group provides guidance on metadata elements that should be minimally required for purposes of learning resource discovery to those concerned with supporting or providing training resources.  This set includes a report, a list of minimal metadata elements along with a data dictionary with examples for how to use the elements, and supporting documents.

The Catalogue of Common Procedures was developed by the DSA–WDS Partnership Working Group on Repository Audit and Certification, a Working Group (WG) of the Research Data Alliance (RDA) . The goal of the effort was to create a set of harmonized Common Procedures for certification of repositories at the basic level, drawing from the procedures already put in place by the Data Seal of Approval (DSA) and the ICSU World Data System (ICSU­-WDS). These procedures are intended to support the implementation of the Catalogue of Common Requirements developed by the WG to harmonize the certification criteria previously established by the DSA and ICSU-­WDS.

The goal of the RDA Research Data Repository Interoperability WG (RDRIWG) was to achieve consensus on an adoptable approach to facilitating research data repository interoperability for a defined set of initial use cases. The following document presents final recommendations the members of the RDRIWG have agreed on. It describes a general exchange format based on the well-known BagIt specification complemented with BagIt Profiles, another specification defining how to describe the internal structure of BagIt-based packages. In order to achieve a basic level of interoperability with regard to the content of such exchange packages, the WG members have agreed on recommending to include DataCite metadata in each package. The presented recommendations document describes the exchange format itself together with adoption guidelines and information about related efforts. In addition, early adoptions are publicly available at GitHub and referenced within the document.

The aim of the Dynamic Data Citation Working Group was to devise a simple, scalable mechanism that allows the precise, machine-actionable identification of arbitrary sub selections of data at a given point in time irrespective of any subsequent addition, deletion or modification. The approach recommended by the Working Group relies on dynamic resolution of a data citation via a time-stamped query also known as dynamic data citation. It is based on time-stamped and versioned source data and time-stamped queries utilized for retrieving the desired dataset at the specific time in the appropriate version.

Session notes from RDA P11 (Berlin, Germany). Includes links to session presentation, map index, also attendance sheet and discussion recap. 

This output describes a concept for establishing a comprehensive network of components for the management of digital objects. The concept follows principles of layering and modularity and describes a set of key components required to realize a network for e-infrastructures in practice.

The FAIR For Research Software Working Group (FAIR4RS WG) is leading the research software community in the crucial step of agreeing how to apply the FAIR principles to research software, including defining the principles and adoption guidelines. This group was convened under the Research Software Alliance (ReSA), the Research Data Alliance (RDA), and FORCE11 (the Future of Research Communication and Escholarship).

The Top 10 FAIR Data & Software Things are brief guides (stand alone, self paced training materials), called "Things", that can be used by the research community to understand how they can make their research (data and software) more FAIR (Findable, Accessible, Interoperable and Reusable).

The Council Operations and Coordination Subcommittee (see https://www.rd-alliance.org/about-rda/governance/rda-council/rda-council...) has revised the document on Transparency and Openness in response to the community comment received on the previous version (which is attached to this page).  

Community comments on this new version are very welcome.