Name of Proposed Interest Group: Sensitive Data Interest Group

RDA site: https://www.rd-alliance.org/groups/sensitive-data-interest-group

1. Introduction (A brief articulation of what issues the IG will address, how this IG is aligned with the RDA mission, and how this IG would be a value-added contribution to the RDA community)

Sensitive Data: A working definition of sensitive data is: Information that is regulated by law due to possible risk for plants, animals, individuals and/or communities and for public and private organisations. Sensitive personal data include information related to racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership and data concerning the health or sex life of an individual. These data that could be identifiable and potentially cause harm through their disclosure. For local and government authorities, sensitive data is related to security (political, diplomatic, military data, biohazard concerns, etc.), environmental risks (nuclear or other sensitive installations, for example) or environmental preservation (habitats, protected fauna or flora, in particular). The sensitive data of a private body concerns in particular strategic elements or elements likely to jeopardise its competitiveness.
Adapted from: David et al., 2020, “Templates for FAIRness evaluation criteria - RDA-SHARC IG” https://zenodo.org/record/3922069#.YCJU7ehKg2w

A range of disciplines collect data which are potentially sensitive, presenting serious barriers to reuse and reproducibility. There are a number of barriers which need to be overcome before sensitive data can be utilised safely and to its best advantage. One major challenge is that not all sensitive data is alike, with significant disciplinary variation in how sensitive data is defined, linked, managed, stored, and reused. Additionally, common approaches to working with, sharing and managing data are not always appropriate for sensitive data. For example, sensitive data exposes the different perspectives underlying the FAIR and CARE principles. Further, sensitive data requires careful stewarding such that it can be disseminated in an ethically and culturally appropriate way. Nonetheless, sensitive data has significant potential to be utilised in the conduct of novel and impactful work. Therefore, it is essential that a set of community standards and best practices be developed for sensitive data usage and management.

Issues the IG will address

In addition to issues identified by the RDA community as this IG develops, we envisage this IG will address the following issues:

1. Data carries with it different levels of sensitivity depending on its context (e.g., research discipline, who the data is about, what the data is being used for). However, it is not always clear how we should assess data for sensitivities in different contexts. A resource is needed for those working with data to allow them to make informed decisions about data sensitivity and, consequently, data governance, management, and usage.
2. Sensitive data is often identified. However, re-identification can be possible and can cause serious harm. Resources are needed on mechanisms of reidentification and the different risks for different types of sensitive data.
3. Data that has been labeled sensitive is often not shared beyond the team that collected/created this data. This means that data collection is sometimes duplicated, and is a challenge for reproducible research. More ethically and culturally safe sharing of sensitive data may also enhance the robustness of research design and development. Resources are needed which provide information for those working with sensitive data with information about how that data can be shared and reused in a safe and ethical manner.
4. At times there is a duality between sharing and reusing data in general, and for stewarding data in culturally and ethically appropriate ways. This duality is exacerbated in the context of sensitive data due to lower rates of data sharing, and increased potential for harm. Guidelines are needed for balancing principles of data sharing and reuse (e.g., FAIR) with ethically and culturally appropriate principles (e.g., CARE) specifically in the context of sensitive data.
5. Consent is a major consideration when sharing any data, especially sensitive data. However, informed consent can be challenging to obtain, especially when reusing data. This is sometimes a barrier to sharing sensitive data. Guidelines are needed that explore consent models, especially post-hoc consent, for governing the primary and secondary use of sensitive data. 

How this IG is aligned with the RDA mission

The RDA Vision: This IG aligns with the RDA vision because it will develop mechanisms for the responsible reuse of sensitive data - a data source that is both extremely valuable but which also carries many ethical and cultural considerations. Sensitive data will play an increasingly significant role in addressing the grand challenges of the 21st century, such as issues of social and environmental justice. Indeed, the benefits and potential harms of sensitive data are increasingly being discussed in public forums as corporations and private companies leverage such data for profit. As mechanisms for sensitive data reuse become widely available (such as through the work of this IG), new innovation and invention will be fostered through the reuse of sensitive data. This IG has participants from University and non-University sectors, which strongly positions the IG to engage with all the variety of stakeholders.

The RDA Mission: This IG aligns with the RDA mission as it develops guidelines for the technical components of working with sensitive data, and for addressing the social aspects of working with sensitive data including fostering discussion around the cultural and ethical considerations of data reuse. This IG is well positioned to meet these challenges given the diverse backgrounds of the initial members. The connection between the technical aspects of working with sensitive data (such as secure virtual environments) and the ethical and cultural aspects (such as consent, disciplinary perspectives and norms, and CARE principles) is a key point of interest for this IG.

How this IG would be a value-added contribution to the RDA community

Sensitive Data is ubiquitous. However, its context varies. For this reason, this IG complements the work of a range of existing IGs and WGs, including:

• COVID-19 Data Working Group
• Raising FAIRness in Health Data and Health Research Performing Organisations (HRPOs) Working Group
• Reproducible Health Data Services Working Group

• Biodiversity Data Integration Interest Group
• Education and Training on Handling of Research Data Interest Group
• Ethics and Social Aspects of Data Interest Group
• Health Data Interest Group
• International Indigenous Data Sovereignty Interest Group
• Social Dynamics of Data Interoperability Interest Group
• Social Sciences Interest Group

• Infectious Diseases Community of Practice (forthcoming)

The aims of the Sensitive Data IG is to provide a space to focus explicitly on sensitive data. While the scope is interdisciplinary, this IG focuses on sensitive data types. Our planned activities will compliment the above IGs as we address sensitive data in domain specific terms (e.g., sensitive data in the health domains) as well as in general terms (e.g., systems for sharing sensitive data). The Sensitive Data IG already has members from a number of the above IGs, which will aid us in coordinating our activities with these groups. The Sensitive Data co-chairs are collectively members of over 20 RDA groups.

All members of the Sensitive Data IG are also active members of the RDA community. We will draw on this to ensure that our efforts take account of previous work in the RDA, and to ensure that our group remains up-to-date on RDA activities.

2. User scenario(s) or use case(s) the IG wishes to address
(what triggered the desire for this IG in the first place):

We identified the following key reasons for forming this IG. We envisage that additional use cases will be developed through working with the RDA community following endorsement.

1. There are a lack of guidelines for working with sensitive data both within and between disciplines/research areas. One reason for this is because sensitive data varies between contexts (e.g., between disciplines). To develop a cohesive but also targeted set of guidelines, a group is needed which comprises members of a range of disciplines with a shared interest in sensitive data.
2. There is a need for a framework which considers the ethical and cultural aspects of sensitive data, alongside the technical aspects. Individuals may want to share their sensitive data and may have conducted all the necessary ethical/cultural safe guards. However, they may lack an understanding of how this can be achieved with the technical resources available to them, what repository or sharing mechanism can handle such data, and how best to access persistent IDs which allow them to track the use of their data. Conversely, individuals may have the ideal technological solution for sharing without an understanding of the ethical/cultural considerations. A group is needed to facilitate a dialogue between the ethical/cultural and technical aspects of sensitive data sharing, and to produce tangible outputs which progress this discussion.
3. There is a general consensus that sensitive data is highly valuable but that it is not being utilised to its full potential. While there is a range of anecdotal support for this claim, a body of work is needed which explores and documents the state of sensitive data primary and secondary usage, and which examines the underlying causes of sensitive data reuse practices within and between disciplines.
4. There is a recognition that there are a number of stakeholders with respect to  sensitive data assets, and that each stakeholder has different requirements, needs, expectations, and terminology (e.g., in the case of health data, government, hospitals, researchers, community members). A group is needed which can synthesise the main expectations of different stakeholders to develop resources of individuals and organisations to use when engaging with, sharing, and accessing sensitive data (i.e., a resource for a shared language between stakeholders).
5. There is a need for adequate and specialised resourcing and infrastructure to manage, work with, and share sensitive data. Different data types require different solutions for management, analysis, and sharing. While a range of solutions are available for these different data types, their suitability for sensitive data is not always clear. Work is required to assess solutions for different sensitive data types specifically.
6. Our era is experiencing the most brutal collapse in biodiversity that the earth has known. Yet biodiversity produces many ecosystem services, and resources. However, species and habitat diversity is undermined by many human activities. The preservation of both fragile and overly coveted species and resources makes the publication of their geolocation sensitive. Other data concerning the characteristics of certain pathogens have also proven to be sensitive.
7. The humanities and social science disciplines likewise require clear guidance regarding collection, use and reuse of sensitive data. This may encompass specific ethical considerations pertaining to data collection (e.g., balancing FAIR v CARE principles), research data collection methods when working with vulnerable individuals or communities often on sensitive topics, the joining of disparate datasets, and considerations of how long such data should be retained, and where.

3. Objectives (A specific set of focus areas for discussion, including use cases that pointed to the need for the IG in the first place.  Articulate how this group is different from other current activities inside or outside of RDA.):[

1. Using the definition presented at the top of this document as a starting point, develop a shared understanding and refined definition of sensitive data.
2. Define various levels of “sensitivity” for data.
3. Data should be as open as possible and as closed as necessary. Within this context, develop an understanding of how sensitivity relates to openness.
4. Identify different consent models.
5. Identify types of sensitive data holdings and resources across various domains.
6. Identify existing data definitions and standards for different types of sensitive data.
7. Identify challenges in collecting, using and sharing sensitive data.
8. Engage with key stakeholders working in the area of sensitive data management/analytics .
9. Identify existing solutions for sensitive data collection, analysis, storage and dissemination.
10. Identify differences in how sensitive data is managed between groups and regions.

4. Participation (Address which communities will be involved, what skills or knowledge they should have, and how will you engage these communities. Also address how this group proposes to coordinate its activity with relevant related groups.):

Use these people to help grow the case studies

While the interested participants in this interest group are currently mostly from Australia, we have been working to establish this group as part of a global Community of Practice. We are currently developing a strategy to achieve international engagement.

To further this effort, the group has seen the recent addition of chairs from Europe and the USA to the group. The Social Science Interest Group, which comprises a broad international membership base and chairs from Norway, USA and Australia, also has formal participation in the Sensitive Data interest group.

The next phase of this engagement strategy will be through specific engagement with RDA groups and other stakeholders covering a range of domains and geographic regions. Specific stakeholders to be approached are still to be determined, but will be drawn from the these target groups These include:

• RDA Interest Groups: Social Science IG (established), International Indigenous Data Sovereignty IG (Initial approach made, pending response), Ethics and Social Aspects of Data IG, RDA-COVID19 WG (and the various sub-groups), Reproducible Health Data Services WG, Epidemiology common standard for surveillance data reporting WG, Domain Repositories IG, Health Data Interest Group, RDA/NISO Privacy Implications of Research Data Sets IG, Virtual Research Environment IG, Social Dynamics of Data Interoperability IG
• Communities outside of RDA: Relevant domain and discipline communities, eg. The SSHOC and EOSC work programs around sensitive data, US and Canadian networks of Research Data Centres, International and Regional Statistical Agencies (WHO, UNStat, Eurostat, National Statistical Offices), (HEALTH DATA EXAMPLE COMMUNITIES??)?

5. Outcomes (Discuss what the IG intends to accomplish. Include examples of WG topics or supporting IG-level outputs that might lead to WGs later on.):

1. To identify the key expectations of the community and use these to refine the IG's objectives.
2. List different types of data across disciplines such as health, social sciences, etc and how different levels of sensitivities apply to those types of data.
3. Identify best practices in sensitive data management across multiple regions, domains and disciplines and how to adapt the best practices.
4. Engage with relevant RDA IGs, WGs and CoPs to identify priorities in the area of sensitive data management.
5. Gather common guidelines and recommendations for working with sensitive data in different disciplines and in different regions.
6. Catalogue of ethical, philosophical and cultural principles that underpin the use of sensitive data assets.

6. Mechanism (Describe how often your group will meet and how will you maintain momentum between Plenaries.):

The IG will meet every 3 - 4 weeks via Zoom. Meeting times will be alternated to accommodate as many time zones as possible. Google Docs will be used to develop shared documentation. Email will be used to communicate about meetings and tasks requiring follow-up between meetings. The current chairs/members of the IG are already successfully using this system to meet and maintain momentum.

The IG will also meet regularly at Plenaries as an opportunity to workshop new ideas with the RDA community and foster new engagements. The group will also establish an informal communication channel through Slack, or a similar platform, to allow for ongoing conversation. The group will also organise webinars and information sessions between Plenaries to share ideas and for group members to stay in touch with the activities of the group. The IG will also use our RDA page to share documents and communicate regularly with the RDA community.

7. Timeline (Describe draft milestones and goals for the first 12 months.):

Initial activities: The group met for the first time as a Birds of a Feather session at RDA 16. Following this, a core group of interested members met to begin drafting the group charter. This group also submitted a proposal for an IG session for RDA 17. The group will send the draft charter for initial TAB review and community consultation in the lead up to RDA 17. The draft charter will also be sent for feedback specifically to members who have joined the IG page and who attended the BoF session at RDA 16. The draft charter and TAB/community/group feedback will be discussed at the RDA 17 session. Following this, the revised charter will be submitted for formal endorsement.

First 12 months: Once the IG is formally endorsed, we will undertake the following activities in the first 12 months:

1. Formally launch the IG - update our RDA IG site, call for additional co-chairs, share the approved charter with group members, establish a regular meeting time, establish RDA mailing list for the IG.
2. Engage in group consultation to identify the main themes of interest and develop a strategy for establishing working groups/task forces to address these.
3. Engage with stakeholders for feedback on key sensitive data issues and to develop the IGs networks within and outside of RDA.
4. Invite existing RDA IGs identified in section 4 above to provide feedback on, and participate in, working groups/task forces themes.
5. Presentation of webinar/workshop to workshop working group/task force topics and open the working groups/task forces topics for group comment through interactive platforms like Google Docs. 
6. Formalise the working groups/task forces, share the goals of the working groups/task forces with the group and RDA more broadly to increase participation, prepare for RDA18 as an opportunity to share progress of the IG and working groups/task forces.
7. Prepare reports and outputs from the working groups/task forces, share reports with the community, present a webinar/workshop to share the outputs with the community.
8. Hold an IG meeting to assess the progress from the preceding 12 months and determine the next steps for working groups/task forces.

8. Potential Group Members (Include proposed chairs/initial leadership and all members who have expressed interest.)

• People interested in leadership:

• People who have joined on the Sensitive Data RDA IG so far

• People who attended the BoF expressed interest in participating following the BoF:

RDA Case Statement

GORC International Benchmarking WG

1. Charter

The Global Open Research Commons (GORC) is an ambitious vision of a global set of interoperable resources necessary to enable researchers to address societal grand challenges including climate change, pandemics, and poverty. The realized vision of GORC will provide frictionless access to all research artifacts including, but not limited to: data, publications, software and compute resources; and metadata, vocabulary, and identification services to everyone everywhere, at all times.

The GORC is being built by a set of national, pan-national and domain specific organizations such as the European Open Science Cloud, the African Open Science Platform, and the International Virtual Observatory Alliance (see Appendix A​       for a fuller list). The ​  GORC I​ G ​ is working on a set of deliverables to support coordination amongst these organizations, including a roadmap for global alignment to help set priorities for Commons development and integration. In support of this roadmap, this WG will develop and collect a set of benchmarks for GORC organizations to measure their user engagement and development internally within the organization, gauge their maturity and compare features across commons. 

In the first case, the WG will collect information about how existing commons are measuring success, adoption or use of their services within their organization, such as data downloads, contributed software, and similar KPI and access statistics. 

Secondly, we will also develop, validate, collect and curate a set of benchmarks that will allow Commons developers to compare features across science clouds. In the latter case for example, we would consider benchmarks such as evidence or the existence of : 

1. A well defined decision making process
2. A consistent and openly available data privacy policy
3. Federated Authentication and Authorization infrastructure
4. Community supported and well documented metadata standard(s)
5. A workflow for adding and maintaining PIDs for managed assets
6. A mechanism for utilizing vocabulary services or publishing to the semantic web
7. A process to inventory research artefacts and services
8. An Open Catalogue of these artefacts and services
9. A proven workflow to connect multiple different research artefact types (e.g. ​data and publications​; data and electronic laboratory notebooks; data and related datasets)
10. A mechanism to capture provenance for research artefacts
11. Mechanisms for community engagement and input; an element or scale for inclusion

We anticipate that the first set of metrics will be quantitative measures used within an organization, while the second set of benchmarks will be comparable across organizations.

2. Value Proposition

This WG is motivated by the broader goal of openly sharing data and related services across technologies, disciplines, and countries to address the grand challenges of society. The deliverables of the WG itself will inform roadmaps for development of the infrastructure necessary to meet that goal, while engagements and relationships formed during the work period will help forge strong partnerships across national, regional and domain focused members which are crucial to its success. Identifying observable and measurable benchmarks in pursuit of the global open science commons will help create a tangible path for development and support strategic planning within and across science commons infrastructures. In the future, best practices for commons development will emerge based on the experience of what actions led to successful outcomes. This work will provide a forum for discussion that will allow members to identify the most important features and the minimal elements required to guide their own development and build a commons that is globally interoperable. Finally, it will support developers as they seek resources to build the global commons by helping them respond to funding agencies requirements for measurable deliverables.

The proposed WG was discussed at the ​RDA 16 virtual plenary​.^[1] Participants discussed the initial work packages and agreed during the meeting this was a worthy goal and an appropriate approach. 

3. Engagement with Existing Work

The GORC IG builds on, and incorporates the previous ​National Data Services IG​. The Commons that will be investigated in this WG are likely either to have considered or implemented outputs from other RDA groups, such as the  ​Domain Repositories IG​, the ​Data Fabric IG​, and the ​Virtual Research Environment IG​, just to name a few. These groups and many others outside of RDA will have recommendations that speak to functionality and features of various components of Commons; for example the re3data.org schema for collecting information on research data repositories for registration, the EOSC ​FAIR WG​ and ​Sustainability WG​ that seek to define the EOSC as a Minimum Viable Product (MVP).  We will review these and other related outputs to see if they have identified benchmarks that we feel will support our goals. This review period will ensure that we do not duplicate existing efforts. ​Appendix B​ of this case statement identifies a few of these existing efforts, both within and without RDA; this list will be expanded and reviewed by the WG members.

4. Work Plan

To create these deliverables, members of the group will:

1. Create a target list of Commons (​Appendix A​)
2. Review public facing documentation of each Commons to extract benchmarking information (both KPIs and feature lists). 
3. Review public facing documentation of recommendations and roadmaps from related communities to extract benchmarking information (​Appendix B​). This evaluation phase will include an examination of the outputs from other RDA WGs and position papers available in the wider science infrastructure community, along with experiences gathered by the WG’s members.
4. Because benchmarking information may not be easily found in public documents we will conduct outreach to Commons representatives and related organizations to ask for additional feedback and information about benchmarks used by their community.  This may include benchmarks already in use, as well as benchmarks that organizations feel would be useful but which are not yet implemented.
5. Synthesize and document the benchmarks into 2 deliverables, described below..

We anticipate that the WG will create sub-working groups or task groups. The WG will decide if they would rather define the task group according to the deliverables, creating a Commons Internal Benchmarking TG and a Commons External Benchmarking TG, or if they would rather subdivide according to a typology of the commons, for example with some members looking at pan-national, national, or domain specific commons, or by some other subdivision of labor.

The WG will proceed according to the following schedule:

5. Deliverables

This group will create ​Supporting Outputs​ in furtherance of the goals of the  ​GORC IG​.

Specifically, 2 documents: 

D1: a non-redundant set of KPIs and success metrics currently utilized, planned or desired for existing science commons, and 

D2: a list of observable international benchmarks of features, structures and functionality that can help define a Commons and that will feed into a roadmap of Commons interoperability.

D3: Adoption Plan: described in section 9 below.  

6. Mode and Frequency of Operation

The WG will meet monthly over Zoom, at a time to be determined by the membership. The WG will also communicate asynchronously online using the mailing list functionality provided by RDA and via shared online documents. If and when post-Covid international travel is restored during the 18 month work period of this WG then we will propose and schedule meetings during RDA plenaries and at other conferences where a sufficient number of group members are in attendance.

7. Addressing Consensus and Conflicts

The WG will adhere to the stated ​RDA Code of Conduct​ and will work towards consensus, which will be achieved primarily through mailing list discussions and online meetings, where opposing views will be openly discussed and debated amongst members of the group. If consensus cannot be achieved in this manner, the group co-chairs will make the final decision on how to proceed.

The co-chairs will keep the working group on track by reviewing progress relative to the deliverables. Any new ideas about deliverables or work that the co-chairs deem to be outside the scope of the WG defined here will be referred back to the GORC IG to determine if a new

WG should be formed.  

8. Community Engagement

The working group case statement will be disseminated to RDA mailing lists and communities of practice related to Commons development that are identified by the GORC IG in an effort to cast a wide net and attract a diverse, multi-disciplinary membership. Similarly, when appropriate, draft outputs will also be published to relevant stakeholders and mailing lists to encourage broad community feedback.

9. Adoption Plan

The WG will create an adoption plan for distributing and maintaining the deliverables.  A specific plan will be developed to facilitate adoption or implementation of the WG

Recommendation and other outcomes within the organizations and institutions represented by WG members.  This will include possible strategies  for adoption more broadly within the global community, and in such a way as to facilitate interoperability of global infrastructures.  Pilot adoptions or implementations would ideally start within the 18 month timeframe before the WG is complete. We envision implementation occurring when developers of commons compare themselves with similar organizations. We also envision the adoption plan will speak to howwe include the benchmarks in the larger GORC roadmap being created by the parent IG. 

10. Initial Membership

Co-chairs: 

1. Karen Payne <​ito-director@oceannetworks.ca>​
2. Mark Leggott <​mark.leggott@rdc-drc.ca>​ 
3. Andrew Treloar <​andrew.treloar@ardc.edu.au​> 

 Appendix A: List of Commons

Pan National Commons

1. European Open Science Cloud
2. African Open Science Platform
3. Nordic e-Infrastructure Collaboration
4. the Arab States Research and Education Network, ASREN
5. LIBSENSE  (​​ LIBSENSE is a community of practice, not an infrastructure. The infrastructure will be built by the RENs, NRENs and universities)
6. WACREN  
7. LA Referencia 

National Commons

European Roadmaps -​ ​The European Commission and European Strategy Forum on Research Infrastructures (ESFRI) encourage Member States and Associated Countries to develop national roadmaps for research infrastructures.  

1. German National Research Data Infrastructure​ (NFDI)
2. DANS
3. ATT (Finland​) 
4. GAIA-X​ (non- member state?; ​see also​) (​focused on data sharing in the commercial sectors - without excluding research)
5. UK
   
   1. UK Research and Innovation
   2. JISC
   3. Digital Curation Centre

Non-European 

6. QNL (Qatar​) 
7. China Science and Technology Cloud (CSTCloud); ​​  see also 
8. Australian Research Data Commons
9. Canadian National Data Services Framework​ (in development)
10. National Research Cloud (US; AI focused)​ 
11. NII Research Data Cloud​ (Japan) 
12. KISTI ​(South Korea)

Domain Commons

1. International Virtual Observatory Alliance​ (IVOA)
2. NIH Data Commons;​ Office of Data Science Strategy​           ​ (USA)
3. NIST RDaF (USA)​
4. Earth Sciences 
   
   1. DataOne Federation
   2. Federation of Earth Science Information Partners (ESIP)​    
   3. EarthCube
   4. GEO​ / ​GEOSS
   5. Near-Earth Space Data Infrastructure for e-Science (ESPAS, prototype)​       
   6. Polar
      
      1. The​ Arctic Data Committee landscape map of the Polar Community​  
      2. Polar View - The Canadian Polar Data Ecosystem (includes international​       initiatives, infrastructure and platforms)
      3. Polar Commons​ / Polar International Circle (PIC) [not sure if this is active] iv.            PolarTEP
   7. Infrastructure for the European Network for Earth System Modelling (IS-ENES)​        
5. Global Ocean Observing Systems ​(composed of ​Regional Alliances​)
6. CGIAR Platform for Big Data in Agriculture
7. Social Sciences & Humanities Open Cloud (SSHOC)​
8. Dissco ​https://www.dissco.eu/​ Research infrastructure for natural collections (a commons for specimens and their digital twins)
9. ELIXIR Bridging Force IG​ (in the process of being redefined as “Life Science Data Infrastructures IG”)
10. Global Alliance for Genomics and Health (GA4GH) 
11. Datacommons.org - primarily statistics for humanitarian work​        

Gateway/Virtual Research Environment/Virtual Laboratory communities and other Services

1. International Coalition on Science Gateways
2. Data Curation Network
3. CURE Consortium
4. OpenAire
5. RDA VRE IG

 Appendix B: Draft List of WG/IG, documents, recommendations, frameworks and roadmaps from related and relevant communities

1. RDA Outputs and Recommendations Catalogue
2. RDA D​ata publishing workflows​ (​Zenodo​)
3. RDA FAIR Data Maturity Model
4. RDA ​9 functional requirements for data discovery
5. Repository Platforms for Research Data IG
6. Metadata Standards Catalog WG  
7. Metadata IG
8. Brokering IG
9. Data Fabric IG
10. Repository Platform IG
11. International Materials Resource Registries WG
12. RDA Collection of Use Cases​ ​(​see also​)
13. Existing service catalogues (for example the ​eInfra service description template used in​ the EOSC)
14. the Open Science Framework
15. Matrix of use cases and functional requirements for research data repository platforms​.
16. Activities and recommendations arising from the interdisciplinary ​EOSC Enhance program
17. Scoping the Open Science Infrastructure Landscape in Europe
18. Docs from ​https://investinopen.org/about/who-we-are/  
19. Monitoring Open Science Implementation in Federal Science-based Departments and Agencies: Metrics and Indicators
20. Next-generation metrics:Responsible metrics and evaluation for openscience​. Report of the European Commission Expert Group on Altmetrics (​see also)​
21. Guidance and recommendations arising from EOSC ​FAIR WG and ​​   Sustainability WG
22. Outputs from the ​International FAIR Convergence Symposium​ (Dec 2020) (particularly the session ​Mobilizing the Global Open Science Cloud (GOSC) Initiative: Priority, Progress and Partnership
23. The European Strategy Forum on Research Infrastructures (​ESFRI) Landscape Analysis “provides the current context of the most relevant Research Infrastructures that are available to European scientists and to technology developers”
24. NIH Workshop on Data Metrics​ (Feb 2020)

Introduction (A brief articulation of what issues the IG will address, how this IG is aligned with the RDA mission, and how this IG would be a value-added contribution to the RDA community):

Extensive work has been, and continues to be done on data interoperability at the technical and information domains. However, a large portion of the challenges in building interoperable information infrastructures are the result of the interplay between organisations, institutions, economics, and individuals.  Collectively these form the social dynamics that foster or hinder the progress towards achieving technical and information interoperability.

These are some of the most difficult challenges to address.  Currently there is only a limited body of work on how to address these challenges in a systematic way.  In keeping with the mission of the RDA, the focus of this group is to focus on what is required to build the social bridges that enable open sharing and re-use of data.

The focus of this interest group is to identify opportunities for the development of systematic approaches to address the key social challenges and to build a corpus of knowledge on building and operating interoperable information infrastructures.

User scenario(s) or use case(s) the IG wishes to address (what triggered the desire for this IG in the first place):

Within Australia, the National Collaborative Research Infrastructure Strategy (NCRIS) set forth the need to establish a National Environmental Prediction System (NEPS).  This requires the collaboration, coordination and (most importantly) the interoperability between a range of facilities, organisations and government entities for this system to work effectively.  A number of facilities involved have recently come to the realization that the Social dynamics between the facilities is a key factor in the success (or failure) of this initiative.

Within the United States, initiatives such as the Pacific Research Platform, the National Research Platform, and the Eastern Regional Network are a few examples of cross-institutional initiatives whose success is dependent as much on social dynamics as on overcoming technical challenges.

The problem exists at smaller scales as well.  At the institutional level, the need to drive adoption across IT, IT Security, Research units, and Libraries provides a persistent challenge.

The BoF session held at the 13th Plenary session highlighted that similar challenges exist within other research domains.

There are many solutions that are being applied everyday around the world to address these challenges.  Many of these are conceived and developed through the knowledge and experiences of the individuals involved.  However , at present there is limited systematic knowledge on this topic and therefore they have limited systematic knowledge to draw upon.

For example, the RDA itself is an instrument intended to address some of the challenges that exist in the social dynamics across the global research data landscape.  As such it provides both an interesting case study as well as a representative microcosm of the broader challenges in this space.

Objectives (A specific set of focus areas for discussion, including use cases that pointed to the need for the IG in the first place.   Articulate how this group is different from other current activities inside or outside of RDA.):

Currently there is no other IG within the RDA that has a specific focus on the social dynamics, (ie: the interplay between organisations, institutions, economics, and individuals) relating to interoperable information infrastructure.

The main objective of this IG is to:

• Identify organisational, institutional, economic, and individual aspects that increase the friction to achieving information interoperability.
• Develop a corpus of knowledge, including models, frameworks and patterns that can be applied by practitioners to develop the desired social dynamics that reduce friction and foster information interoperability.
• Identify and develop case studies of solutions that demonstrate the application of the corpus of knowledge on this topic.  It is acknowledged that often the details of specific case studies could be sensitive and documented case studies may need to be synthesised drawing upon actual cases.

The purpose of this IG is to create the body of knowledge and illustrative case studies for practitioners to be able to equip themselves with the best knowledge to understand the social dynamics that exist in their specific context and to be able to draw on this knowledge to influence positive change. 

Participation (Address which communities will be involved, what skills or knowledge should they have, and how will you engage these communities.  Also address how this group proposes to coordinate its activity with relevant related groups.):

The participation in this IG is left open and broad to anyone who has an interest in the social dynamics as it relates to building interoperable data infrastructures.  Specific skills and knowledge that would be useful for this IG include,

• Social psychology
• Organisational behaviour and organisational psychology
• Economics
• Legal frameworks
• Digital anthropology
• Digital ethnography

It is expected that many of the topics of interest for this IG will have some degree of overlap with other IGs and WGs within RDA.  It is intended that this IG will keep these related IGs informed of its activity, and seek to coordinate with them on topics that overlap or have a common interest.  It is feasible that in the future we could hold joint sessions at plenary events around common topics.

Drawing on the description provided in the RDA website, the following IGs have been identified as potentially having overlapping interests with this IG,

1. Big Data IG
2. Biodiversity Data Integration IG
3. Chemistry Research Data IG
4. CODATA/RDA Research Data Science Schools for Low and Middle Income Countries
5. Data Economics IG
6. Data Fabric IG
7. Data Foundations and Terminology IG
8. Data in Context IG
9. Data policy standardisation and implementation IG
10. Digital Practices in History and Ethnography IG
11. Domain Repositories IG
12. Early Career and Engagement IG
13. Education and Training on handling of research data IG
14. ELIXIR Bridging Force IG
15. Engaging Researchers with Data IG
16. Ethics and Social Aspects of Data IG
17. Federated Identity Management
18. Global Water Information IG
19. National Data Services IG
20. Physical Samples and Collections in the Research Data Ecosystem IG
21. PID IG
22. Preservation Tools, Techniques, and Policies
23. RDA/CODATA Legal Interoperability IG
24. RDA/CODATA Materials Data, Infrastructure & Interoperability IG
25. RDA/NISO Privacy Implications of Research Data Sets IG
26. RDA/WDS Certification of Digital Repositories IG
27. Research Data Architectures in Research Institutions IG

Outcomes (Discuss what the IG intends to accomplish.  Include examples of WG topics or supporting IG-level outputs that might lead to WGs later on.):

There are two primary outcomes of this IG:

1. Create a community of interest on the Social dynamics of interoperable information infrastructures;
2. Create a corpus of knowledge on the topic.
3. Identify and develop case studies of solutions that demonstrate the application of the corpus of knowledge on this topic.

Some initial topics that could lead to Working Groups include,

• Problem and solution patterns in Information Infrastructure;
• Governance  & participation models;
• Frameworks for trust;
• Incentives and disincentives for collaboration and participation;
• Specific institutional partnerships known to exist, how they came to be, and their varying degrees of success

Mechanism (Describe how often your group will meet and how will you maintain momentum between Plenaries.):

     The group will aim to have at least 1 virtual meeting between sessions.  It will also establish a mechanism (possibly the mailing-list) for offline discussions.

Timeline (Describe draft milestones and goals for the first 12 months):

Potential Group Members (Include proposed chairs/initial leadership and all members who have expressed interest):