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Disciplinary groups play a pivotal role in the RDA ecosystem. Not only do they provide a mechanism for engaging with the outputs of the RDA community, they are instrumental in providing input to the cross-cutting technical and socio-cultural groups. With its formation and endorsement in 2013, the Biodiversity Data Integration IG has been one of the pioneering groups in RDA, focusing from the outset on linking the wider communities of practice in the biodiversity data domain with experts and other communities within RDA. 


The COVID-19 outbreak was a game changer that will have a permanent effect on digital strategies. It has made it abundantly clear that the domain needs to expand its digital strategies beyond simply adding content online. This includes strengthening relationships with our audiences, supporting the development of people and their digital skills, evaluating joint policies and the ability to evaluate choices in the ever changing technology landscape. The BDI IG aims to be a platform for discussion and development of recommendations and guidance that can help institutions and researchers in the domain in their digital transformation.


This charter has been updated because there are many developments in the field of biodiversity data now that would benefit with alignment of developments in other scientific domains and vice versa. Examples are the global movement to FAIR data, implementing RDA recommendations towards a FAIR DO infrastructure for specimens with Natural Science Identifiers, an extended Catalogue of Life and the establishment of a Global Alliance for Biodiversity Knowledge.


Please find the updated Charter here:

Review period start:
Wednesday, 12 August, 2020 to Saturday, 12 September, 2020
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Reuse of health and clinical research data (including social care, and hereafter referred to as health research  data)  has  major  restrictions  when  compared  to  other  research  data  in  the  biomedical domain.  This  primarily  pertains  to  the  concerns  imposed  by  privacy,  sensitivity  and  ethical  issues raised by making data freely available. Meanwhile, research data management (RDM) practices such as  the  creation  of  data  management  plans  (DMP),  sharing  datasets,  the  deposition  of  data  in repositories,  and  the  application  of  FAIR  data  principles  to  research  outcomes  are  becoming increasingly  common  as  they  are  required by funder mandates. Besides this requirement placed by funders  there  is  also  the  wider  need  for  researchers  to  share,  find  and  access  data  to  progress common goals as the primary value, and promote integrity and reproducibility.

The last few years have seen a rapid rise in uptake of the FAIR principles, which originated in the life sciences domain, but which have now been adopted to varying degrees across all research domains. Concomitant  with  the  rise  of  FAIR  datasets  has  been  an  increase  in  open  research  which  urges researchers to make their data available for reuse, especially those that are publicly funded. However, an  important  caveat  when  thinking  about  FAIR when compared to open research is the phrase “as open as possible, as closed as necessary”.

The recent enforcement of the GDPR in Europe is a prime example of a legal framework that makes strict regulations around the processing and sharing of personal data and places the onus on the data controller  to  make  sure  provisions  are  in  place  to  ensure  this.  Although  the  GDPR  is  the  most  far reaching  data  protection  legislation  currently  in  the  world,  there  are  other  territories  that  have restrictions  on  secondary  use  of  personal  data  and  health  data,  e.g.  USA (HIPAA), Ireland (Health Research  Regulation),  India  (Personal  Data  Protection  Bill)    and  S-Africa  (Protection  of  Personal Information Act). As well as internationally enforced restrictions, there are those at national and local levels, and together they all require evidence that the sharing and reuse of health research data are carried out responsibly and in-line with stated aims. The legislation is not meant to impose barriers but to protect individuals' rights.

FAIR adoption in the health research domain is complicated by numerous factors including concerns regarding:  ethical,  moral,  cultural,  technical,  and  legal  constraints  of  primary  source  data.  We therefore propose this WG to address some of these issues to:

    Analyse and report legal and ethical issues surrounding data privacy of health research data at the national level.

    Identify  commonalities  across  territories  that  can  be  a  foundation  for  harmonisation  of guidelines on FAIR adoption.

    Provide  Health  Research  Performing  Organizations  (HRPOs) with a set of clear and simple guidelines for implementing FAIR Open Data policy in health research.

Therefore,  the  main  purpose  of  this  WG is to provide HRPOs (such as universities, public research institutes, hospitals, medical charities etc.) with a set of clear and simple guidelines, which will define, establish  and  enable  implementation  of  an  aligned FAIR data policy at the institutional level.

Review period start:
Friday, 5 June, 2020 to Monday, 6 July, 2020
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Update November 30, 2020:

Our group has been approved by the TAB and endorsed by the Council. Yay! This makes the charter definitive as well. Thanks to all who have contributed and provided feedback. And thanks to the TAB and Council for their trust in this group. 

Update October 2020:

Based on the revisions requested by the TAB, we have updated the IG charter (changes in yellow) with regard to the following aspects:

  • updated information on the co-chairs nomination/election, including geographical spread.
  • updated information on our contacts with relevant other IG and WG, to speed up collaborations

We thank the TAB for their useful feedback and hope the updated charter will result in the formal recognition of our IG (in formation). Don't hesitate to contact us in case of questions.

Many thanks and best regards,

Mijke Jetten, on behalf of the other co-chairs as well,

Peter Neish, Niklas Zimmer, Mohammad Akhlaghi, Varsha Khodiyar, Michelle Barker, Romain DAVID, Debora Drucker, Christina Drummond, Yan Wang


May 2020:

In attachment, you find the charter proposal for the Professionalising Data Stewardship Interest Group (in formation). Part of the submission process is a round of community review (up to June 18) on the proposed charter. We kindly ask you to read the charter and provide feedback via the 'comments option'. 

Many thanks in advance,

Mijke, Marta & Peter (co-chairs)


Original Charter (May 2020):

Revised Charter (October 2020):

Review period start:
Monday, 18 May, 2020 to Thursday, 18 June, 2020
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Please note that the CURE FAIR WG's Case Statement was revised in October 2020, following the community review and TAB review. This final version is dated October 2020.

The version that underwent community and TAB review was created in May 2020. Both versions are attached to this page.

The goal of the working group is to establish guidelines and standards for curating for reproducible and FAIR data and code (Wilkinson et al., 2016). The ultimate objective is to improve FAIR-ness and long-term usability of “reproducible file bundles” across domains.

When we think of specific research outputs, we might think of data, software, codebooks, etc. These individual outputs may have inherent value. For example, a set of observations that is very costly to produce, or that cannot be repeated, or a script that can be used by others for computation. Traditional curation has considered these outputs as its core objects. But in the context of empirical research, these outputs interact with each other, often to produce specific findings or results. Nowadays, the process by which results are generated is captured in computation. Our approach to curation takes into account this process and focuses on computational reproducibility.


Computational reproducibility is the ability to repeat the analysis and arrive at the same results (National Academies of Sciences, Engineering, and Medicine, 2019; Stodden, 2015). It requires using the data and code used in the original analysis, and additional information about study methods and computational environment. The reason to pursue computational reproducibility is to preserve a complete scientific record , to verify scientific claims, to do science and build upon the findings, and to teach (Elman, Kapieszewski, & Lupia, 2018; Resnik & Shamoo, 2017; Stodden, Bailey, & Borwein, 2013).


In this framework, the object of the curation is a “reproducible file bundle” and its component parts, including the files and their elements (e.g., variables), with the goal of enabling continued access and independent reuse of the bundle for the long term.

The CURE-FAIR WG is focused on the curation practices that support computational reproducibility and FAIR principles.

By curation we refer to the activities designed for “maintaining, preserving and adding value to digital research data throughout its lifecycle” (Digital Curation Center, n.d.).

The WG will deliver,

  1. A snapshot of the current state of CURE-FAIR practices drawing upon community surveys and reviews of practice.
  2. A synthesis of practices relating to curating for computational reproducibility and FAIR principles.
  3. A final document outlining standards and guidelines for CURE-FAIR best practices in publishing and archiving computationally reproducible studies, including the associated computational methods and materials.
Review period start:
Friday, 15 May, 2020 to Monday, 15 June, 2020
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Update on the FAIR4RS WG Case Statement - 31 July 2020

The FAIR4RS Steering Committee would like to thank the community and the RDA TAB for their valuable feedback to the Case Statement. Here we offer a resubmission addressing the minor changes suggested.


Summary of changes:

  • Minor additions in audience, RDA WG/IG engagments, and references.
  • A review of section 4 Work Plan, reorganising the milestones to align work with existing Working Groups and community feedback.
  • A review of engagement activities in section 5 Adoption Plan, making it clear and explicit that the general community will be made aware of the developments, invited to contribute and consulted regularly for feedback.
  • Editing section 6, adding aproximate current member numbers. A clarification that community members can join or leave the steering committee, with ongoing continuous disclosure of membership changes.
  • Update of contributors.

We commit to continue working with the members of the community to achieve the deliverables on time.


With kind regards,

Paula Andrea Martinez,  on behalf of the FAIR4RS Steering Committee.

Updated Case Statement:
Original Case Statement:


Original text of this page


One of the major challenges of data-driven research is to facilitate knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of data and their associated research objects, e.g., algorithms, software, and workflows. To address this, an initial effort to define a "DATA FAIRPORT"1 began in 2014 at the Lorentz workshop and transitioned into developing a set of FAIR data Guiding Principles in 2016. The details of the FAIR data principles2 strongly contribute to addressing this challenge with regard to research data, and the principles, at a high level, are intended to apply to all research objects; both those used in research and that form the outputs of research. Here we focus on the adaptation and adoption of the FAIR principles for the case of research software.


Software has become essential for research. To improve the findability, accessibility, interoperability, and reuse of research software3 , it is desirable to develop and apply a set of  FAIR Guiding Principles for software. Many of the high-level FAIR data principles can be directly applied to research software by treating software and data as similar digital research objects. However, specific characteristics of software — such as its executability, composite nature, and continuous evolution and versioning — make it necessary to revise and extend the original data principles.


Application of the FAIR principles to software will continue to advance the aims of the open science movement. The FAIR For Research Software Working Group (FAIR4RS WG) will be jointly convened as an RDA Working Group, FORCE11 Working Group, and Research Software Alliance (ReSA) Taskforce, in recognition of the importance of this work for the advancement of the research sector. FAIR4RS WG will enable coordination of a range of existing community-led discussions on how to define and effectively apply FAIR principles to research software, to achieve adoption of these principles.


The working group will deliver:

  • A document developed with community support defining FAIR principles for research software
  • A document providing guidelines on how to apply the FAIR principles for research software (based on existing frameworks)
  • A document summarising the definition of the FAIR principles for research software, implementation guidelines and adoption examples.

Please see for the full Case Statement.

1 See also DTL, 2014; and Kok, 2014.

2 See also Wilkinson et al., 2016.

3 For further information refer to Clément-Fontaine et al., 2019.



Review period start:
Monday, 11 May, 2020 to Thursday, 11 June, 2020
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March 30, 2020


The objectives of this Working Group are twofold:

  1. to clearly define detailed guidelines on data sharing under the present COVID-19 circumstances to help stakeholders follow best practices to maximize the efficiency of their work
  2. to develop guidelines for policymakers to maximise timely data sharing and appropriate responses in such health emergencies.

The group will address the development of such detailed guidelines on the deposit of different data sources in any common data hub or platform. The guidelines aim at developing a system for data sharing in public health emergencies that supports scientific research and policy making, including an overarching framework, common tools and processes, and principles which can be embedded in research practice. The guidelines to be developed will address general aspects related to the principles the data should adhere to (FAIR and other principles), as well as specificities related to five areas (below).



The COVID-19 WG will create a draft set of deliverables in a 3- week timeline (by April 24), with ongoing efforts to continue to add and review material:

1.    A set of Guideline documents, highlighting the primary data sharing resources in five areas, each with different data types and cross-cutting themes (e.g. ethics, legal, etc.). Other areas will be added, if required, as the effort proceeds.
a.    Omics
b.    Clinical
c.    Epidemiology
d.    Social Sciences
e.    Community Participation

2.    A set of Resource lists in each of these areas.
3.    A Decision Tree tool to facilitate navigation to specific Resources.

Value Proposition

The COVID-19 WG outputs are intended for the full range of stakeholders working on solutions to the COVID-19 pandemic, including: researchers; research administrators; public health practitioners, funders; data managers; policy makers. The set of tools will provide access to specific data sharing resources based on the focus of the individual.
Engagement with Existing Work in the Area 
Given the nature of the COVID-19 pandemic, there are a number of other groups working on facilitating access to resources in this area. The WG will list these other efforts, and where appropriate integrate their efforts into this output. Some specific efforts include:

1.    OECD use of Open Government Data (OGD) in response to the COVID-19 outbreak
a.    Sheet
2.    Virus Outbreak Data Network (VODAN)
3.    CODATA ‘Making Data Work for Cross-Domain Grand Challenges’ or launch in 2021

Work Plan

Given the tight timeline for the WG, a process has been defined that will facilitate a quick turnaround, while ensuring the quality of the work.

1.    The outputs of the WG will work together to form a single access tool, from General Guidelines→Area Guidelines→Resource Submission Forms→Resource Lists→Decision Tree/Search for Accessing Resources.

2.    The WG members (over 300 as of March 30) will be divided into Area Teams that will add and perform peer review of recommended Resources. Each Area Team which may include a number of sub-groups, will work concurrently to produce the appropriate outputs: 

a.    Writing Group: will draft the Guidelines for that Area

b.    Resource Group: will add appropriate resources, and provide peer-review

3.    The work of the Areas will be coordinated by Area leaders:

a.    Area Teams

i.    Moderator(s): overall coordination of the Teams

ii.    Co-chair observer: A representative from the co-chairs team to ensure appropriate resources are available.

iii.    Support person: To provide support for calls, scheduling, input forms, updating task lists, etc.

b.    Co-chairs

i.    Co-chairs plus additional support resources.

4.    The various roles within each team will provide the input and quality control needed to ensure the WG outputs are of a high quality. The outputs will receive further vetting once drafted by the broader RDA and stakeholder communities.

5.    Each of the Area Teams will have weekly calls via Zoom, and there will be 2-3 Zoom Webinar meetings with the full WG membership to review progress and get feedback. The Co-chairs+ Team will meet weekly on Monday, the Co-chairs+ & Moderators Team weekly on Tuesday, The Co-chairs+ & Editorial Team weekly on Wednesday, and the Area Teams weekly on Thursday. The full WG member webinar meetings will be scheduled at appropriate times. The progress of the groups will be tracked by a WG Project Manager using an appropriate tool.

Adoption Plan

Given the critical nature of the global research effort being marshalled to combat the COVID-19 pandemic, the 300+ members of the WG will be asked to indicate adoption/use of the outputs, and to promote through their networks as much as possible. RDA’s organizational partners will also be asked to do the same. 

This Working Group operates according to the RDA guiding principles of Openness,  Consensus,  Balance,  Harmonization,  Community-driven,  Non-profit and technology-neutral and is OPEN TO ALL

The RDA is collaborating with CODATA, GO FAIR, and WDS under their Data Together statement.

Initial Membership

The Co-chairs of the Working Group and sub-groups are:

  • Juan Bicarregui
  • Anne Cambon-Thomsen
  • Ingrid Dillo
  • Sarah Jones
  • Mark Leggott
  • Priyanka Pillai

The Members of the WG are listed on the WG Members page (320 as of March 30), and a smaller subset indicating where their efforts would best be used are listed in a separate Expertise sheet. The roles for specific Members will also be listed on the WGs Wiki page.


Review period start:
Wednesday, 1 April, 2020 to Friday, 1 May, 2020
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!! DRAFT !!

WG Charter: 

This WG intends to develop two outputs: 

Outcome 1: A recommendation regarding legal and ethical best practice for the use of sUAS and sUAS data for research purposes including capturing, sharing and (re) use of data.

Outcome 2: A technical recommendation regarding the cyberinfrastructure requirements for supporting sUAS data capture in a research environment.

Value Proposition:

Based on 5 years of community engagement a number of relevant issues have been highlighted as potential topics for future work (the primary outcomes and context were published by the sUAS data IG in [1]). These were presented and discussed at P14 and following this community consultation process two outcomes were chosen as the primary goals the group wants to pursue:

  1. legal/ethical recommendation on sUAS research data capture, sharing and use;

  2. technical recommendations focussing on the infrastructure to enable sUAS research data.

These outcomes will specifically seek to address the needs of the following research communities.  

Outcome 1 is intended to guide researchers using and seeking to use sUAS to capture data, publish such data, and reuse the captured data.  Our engagement work thus far has shown this is a subject that has not been well addressed anywhere. Furthermore, as many countries are currently in the process of developing regulations regarding sUAS use, this is an opportunity to contribute to the discussions.

Outcome 2 is also intended to serve a range of users. As a new technology, researchers running and looking to run sUAS based data capture programs, and those who fund and support such researchers (cyberinfrastructure facilities, librarian, funders, and institutions) are currently lacking formal guidance regarding what cyberinfrastructure they might anticipate needing.  While many of these users are very capable of deriving such for themselves this is arguably unnecessary repetition. Our engagement work thus far has shown this is a subject that has also not been comprehensively addressed anywhere.

Engagement with existing work in the area:

As indicated, the above 2 foci are the result of a comprehensive global community engagement effort as published [1].  Throughout this work, the specific goal outcomes named have not been encountered.  Building upon existing research, therefore, the aim is to contribute with our recommendations to the ongoing discussions on the responsible use of sUAS worldwide in line with the shared RDA mission to develop and adopt infrastructure that promotes data-sharing and data-driven research in the field of sUAS.

To grow our network both within and outside the RDA, members are encouraged and supported to actively engage with a wide variety of interest groups and key stakeholders including policymakers. NGO’s interest groups (independent) researchers and (non) commercial drone users to build a strong community and platform that will help us develop recommendations that have the best potential to be endorsed and adopted by the community.

In the case of Outcome 1, 

-    within the RDA, the RDA Legal Interoperability IG, International Indigenous Data Sovereignty IG, and Ethics and Social Aspects of Data IG have been contacted.  

-    External to the RDA are many potential points of input, the scale of our engagement will depend on our ability to scale our efforts. 

Of particular note are the subjects of legal frameworks under which sUAS operate in different countries, and the global and local norms regarding both human privacy and all sUAS observable objects in the world. With respect to regulations the International Civil Aviation Authority, along with specific WG members home aviation authorities are primary sources.  A third key source of information on this subject will be the growing number of institutional policy documents regarding the use of sUAS. Although research on responsible data management, exist providing a foundation for how institutions are addressing and considering local legal frameworks more insights are needed.  Depending on the expertise and interests amongst the WG members we for now propose to limit our focus at this stage to the US, the EU, Africa and Australia.

In the case of Outcome 2 which seeks to make recommendations regarding cyberinfrastructure for sUAS data, within RDA the range of groups that might be consulted is potentially broad given that sUAS can potentially capture data from nearly every domain and that the data pipeline touches on nearly every domain of data expertise.  External to RDA, the OGC UXS WG, ASPRS, as well as any national cyberinfrastructure research programs and all sUAS users all potentially would have value to contribute.  Clearly such a breadth of communities and commentators cannot all be consulted and a strategy of narrowing this breadth is essential. Specifically, the first task of the WG should be to seek out key representatives that are likely to serve as primary sources for the type of information we are seeking.  For instance, our group itself represents a breadth of sUAS users and programs, and the majority of us are connected to our own national equally experienced colleagues.   

Work Plan:

As the 2 outcomes of this work are largely independent of one another the investigative efforts can be run in parallel.  However, where work required involves consulting with common 3rd parties these parallel efforts will benefit each other by providing a multiplier effect in multiplying the number of potential input sources for each other.  In all work, sources, results, and discussions will be publicly recorded and available for comment in a RDA sUAS WG Github repository. Therefore, 4 stages of parallel by synchronised work are planned.

Stage1 Design (4 months):  In parallel and with each led by a co-chair, subtask teams will work to collect a list of  potentially relevant sources of information. Where these sources are people and institutions these will be noted but not yet consulted, where these are documents or otherwise non-human sources they will be reviewed, and summaries publicly recorded. 

Stage2 Information gathering (10 months):

Stage3 Synthesis and Reporting (4 months):

Stage4 Publication and Adoption efforts (2 months):

Adoption Plan:

From the first stage onwards, all WG members and especially co-chairs and core members of both subteams of the WG are expected to actively engage with various community groups involved in the sUAS ecosystem (experts, researchers, practitioners and decisionmakers)  internationally to raise awareness of the WG and create a platform for feedback and adoption of the outcomes. During each Plenary a working session is proposed and/or a face to face meeting to present the ongoing efforts regarding awareness, networking and potential for adoption.

Initial Membership:

 A specific list of initial members of the WG and a description of initial leadership of the WG. 

F van den Boom;


J Wyngaard;

[open position to be filled in during P15]


[insert your name here]

A. Specht (but I know some others even better than me (!). I shall try to rope them in)



A living document to be made available internally and externally with relevant sources of information

[ available after P15 on GITHUB/ Google Drive doc ]



[1] Wyngaard, J.; Barbieri, L.; Thomer, A.; Adams, J.; Sullivan, D.; Crosby, C.; Parr, C.; Klump, J.; Raj Shrestha, S.; Bell, T. Emergent Challenges for Science sUAS Data Management: Fairness through Community Engagement and Best Practices Development. Remote Sens. 2019, 11, 1797.

Hodgson JC & Koh LP (2016) Best practice for minimising unmanned aerial vehicle disturbance to wildlife in biological field research. Current Biology 26:R404-R405;

Vas, E., Lescroel, A., Duriez, O., Boguszewski, G., and Gremillet, D. (2015). Approaching birds with drones: first experiments and ethical guidelines. Biol. Lett. 11, 20140754.;

Ratcliffe N, Guihen D, Robst J, Crofts S, Stanworth A & Enderlein P (2015) A protocol for the aerial survey of penguin colonies using UAVs. Journal of Unmanned Vehicle Systems 3:95-101.

Smith CE, Sykora-Bodie ST, Bloodworth B, Pack SM, Spradlin TR & LeBoeuf NR (2016) Assessment of known impacts of unmanned aerial systems (UAS) on marine mammals: data gaps and recommendations for researchers in the United States1. Journal of Unmanned Vehicle Systems:1-14  This database is comprised of a country directory with summaries of national drone laws.

Website of the International Civil Aviation Authority for the UAS toolkit 

Website of the Federal Aviation Administration on UAS 

See also: FAA's mobile application for recreational flyers to know whether it is safe to fly their drone.

The EU just published EU wide rules on UAS: the Commission Delegated Regulation (EU) 2019/945 & Commission Implementing Regulation (EU) 2019/947,

The EU Aviation Safety Agency (EASA) 


Review period start:
Tuesday, 3 December, 2019 to Wednesday, 1 April, 2020
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Review period start:
Wednesday, 27 November, 2019 to Thursday, 9 January, 2020
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Interest Group Title: RDA for the Sustainable Development Goals


Introduction: Fit with the overall RDA vision and mission


The Sustainable Development Goals (SDGs) are 17 global goals, with 169 associated targets, which came into effect in January 2016 and will continue to guide UN policy and funding until 2030. Progress on the UN's 17 Sustainable Development Goals requires broad collaboration within the global data community, as well as nuanced understanding of the barriers for developing information infrastructures. Interoperability of data remains a barrier to collecting, storing, merging, and analyzing data for monitoring SDG metrics effectively - and improving data interoperability may both enhance monitoring, as well as help to enable and support progress towards achieving the SDGs. Achieving interoperable data to advance the SDGs will require best practices, recommendations, technologies, and support of capacity building - which is in direct alignment with many of RDA’s ongoing and upcoming outputs, recommendations, interest group, and working group activities.




Objectives and scope of the Interest group activities will fall into two categories:

  1. Improved data management/sharing of SDG indicator data, based on implementation and adaptation of RDA outputs within workflows surrounding the SDGs and NGO development space more broadly.
  2. Assessing the impact of data infrastructure, and associated quality and limitations thereof, as a component of sustainable development. Defining the value and importance of data infrastructure within sustainable development overlaps directly with the infrastructure-related SDG indicators. More broadly, defining and justifying the importance of data infrastructure will clarify this need to funders supporting development initiatives, researchers and admins supporting the work of development monitoring, and future policy development.




Group participation is encouraged for any RDA members working in areas of research, policy, advocacy, data management, or infrastructural support surrounding the Sustainable Development Goals. Such roles include, though are in no way limited to, researchers focused on global sustainability and capacity enhancement, legal experts, data and repository managers, research librarians, and national statisticians.


Engagement with existing work in the area


  • Data for Development IG
  • Indigenous Data Sovereignty Group
  • Small Unmanned Aircraft
  • Health Data IG
  • Reproducible Health Data Services Working Group
  • RDA/Codata Data Science Summer Schools


User Scenarios


Achieving successful monitoring of the sustainable development goals requires international data exchange and an array of changes to the culture of science and capacity enhancement activities ongoing in nations wherein data for the SDG indicators are being collected. These capacity enhancement activities fall within four broad categories, all of which overlap with the social and technical challenges to international research data sharing:

  • Organizational collaboration
  • Data sharing and interoperability
  • Data sharing and data governance
  • Capacity building

Broadly, the value-add of this Interest Group’s activities will be to:

  1. Create materials to support the implementation of RDA outputs and recommendations within the social and technical work of the UN surrounding the sustainable development goals. These materials will be aimed to support the work of data managers, statisticians, research policy advisers and advocates, and diverse project managers supporting SDG data infrastructure and data use.
  2. Facilitate organizational collaboration/support with the U.N. and its agencies partnerships in commercial, academic, and NGO space. Facilitating such partnerships will Increase the visibility of the RDA on a global scale, providing precedence for future collaboration with additional IGOs and NGOs. RDA’s OAB, TAB, Council, Secretariat, and group membership could all play a role in facilitating such partnerships.
  3. Build collaborative partnerships across RDA interest groups and working groups working within the field of capacity development in low and middle income countries, furthering progressing RDA’s mission.

Scope of Interest Group:


Activities ongoing within the RDA that could align with the SDG

  1. Conduct a literature review of the United Nations actions for SDGs, the related targets and indicators, and additional efforts ongoing in the space of research data that overlap with the intersection of RDA and the SDGs.
  2. Landscape analysis of RDA Working Group/IG connections to SDG work, as examined in aim 1
    1. Draft tabular matrix WG/IG overlap with indicators and OD2I (value chain of data to decisions)
    2. Build an interactive board/sticker/cards @P14 for WG/IGs to place themselves within the matrix - MILESTONE
    3. Identify working and interest groups of potential high-impact for SDGs
    4. Validate matrix in collaboration with selected working and interest groups
  3. Create an implementation guide advising members of the U.N. working in the areas of Sustainable Development Goals about the applicable RDA outputs and recommendations, strategies for implementation, and available technologies and methods to support implementation.
  4. Identify examples of implementation: Identify pathways and past success-cases wherein RDA working/interest groups were in collaboration with or implemented by SDG or capacity development work.
  5. Conduct test adoptions of implementation guide, developed in aim 3, to garner usability and implementation feedback from members of the U.N.





Interest group members will hold bi-monthly meetings via telecom platforms such as Zoom, GoToMeeting, or etc. for all interest group members. These meetings will have running agenda items, reports of ongoing projects, and additional items added given upcoming events or emerging opportunities aligned with deliverables or collaboration with partnering organizations. Co-chairs may also meet outside of these bi-monthly meetings to manage ongoing deadlines. Meeting notes will be made open to the public via the RDA website. Plenary sessions will provide public updates about IG activities and space for community feedback regarding strategy or scope.


Potential Projects for Interest Group Scope


In preperation of defining the Interest Group’s scope and potential objectives, the following activities are proposed:

  1. Select representatives from the RDA community active in work aligned with the SDGs familiar with strategies for forming organizational partnerships with the RDA.
  2. Assess key needs/gaps for the UN, funder, and SDG-associated organizations addressable by these RDA activities.
  3. Recognizing the work of the UN in identifying tiers of SDG indicators and the future needs for SDGs, identify potential alignment of RDA activities that may support UN tier indicator work
    • Tier 1: Indicator is conceptually clear, has an internationally established methodology and standards are available, and data are regularly produced by countries for at least 50 per cent of countries and of the population in every region where the indicator is relevant.
    • Tier 2: Indicator is conceptually clear, has an internationally established methodology and standards are available, but data are not regularly produced by countries.
    • Tier 3: No internationally established methodology or standards are yet available for the indicator, but methodology/standards are being (or will be) developed or tested
  4. Execute a problem/needs assessment as mapped by the UN and supporting community. Such a needs assessment would likely require conversations, structured surveys, or litereature reviews with UN executives or policies concerning how the U.N. perceives problems/needs, and where RDA may contribute.

In reflecting on the sessions and feedback throughout the p13, some of the major takeaways and potential next steps on SDG work are as follows:


Create adoption/output portfolio (aim 3) for the development sector audience. This output portfolio could also frame the value of RDA outputs for various SDG goals, such as #9 Industry, Innovation and Infrastructure (focusing on the value of research data infrastructure supporting sustainability), and #17 Partnerships for the goals (focusing on the value RDA brings in as a large 8,000-strong member community). Such a portfolio could be a brief summary of RDA-alignment with the SDG work and some educational materials, such as a webinar, describing how RDA outputs could be applicable to social and technical issues surrounding work in the SDGs. We'd also thought featuring testimonials of people working in the SDGs who recognize the RDA's benefit or have used RDA outputs in past within their work would be beneficial. We're in contact with members of the RDA summers schools and education for librarians IG who are well-experienced in crafting similar portfolios for targeted audiences, and will continue to explore how such a portfolio could be impactful.


Assess existing RDA groups and partnerships aligned with the development sector. Given the diverse RDA outputs and recommendations that could support the SDGS, we will assess their alignment with the SDGs and select representatives from these activities who might be amenable to discussing strategies for forming a partnership with the UN. These representatives may also have previous experience with forming organizational partnerships or may themselves represent a RDA organizational partner.

The aim being three-fold:

  1. Define activities ongoing within the RDA that could align with the SDGs
  2. Select representatives active in this work familiar with strategies for forming organizational partnerships with the RDA
  3. Assess key needs/gaps for the UN addressable by these RDA activities and form a case-statement for a working or interest group.

Many of the topics covered in the IN2N publication could be of interest to the UN and represent the sorts of contributions the RDA-community could offer. Ensuring the final publication reaches the attention of the UN could be a worthwhile strategy.

Potential Group Members




Member Type



Contact mail

Ingvill C. Mochmann




Anthony Juehne

Co- Chair



Lindsay Barbieri

Co- Chair



Rob Quick





Jay Pearlman





Francoise Pearlman




jsp@sprintmail.comimdis 2018

Edit Herczog




mrs.edit.herczog@gmail. com

Francoise Genova





Ilya Zaslavsky






Additional links to informative material related to the group

Sustainable Development Goals Interoperability Data Collaborative:


Interoperability: A practitioner’s guide to joining-up data in the development sector:


A Vision for the Humanitarian Use of Emerging Technology for Emerging Needs:"


ICSU, ISSC (2015): Review of the Sustainable Development Goals: The Science Perspective.
Paris: International Council for Science (ICSU)

Please add below additional links to informative material related to the participating groups, i.e. group pages, case statements, working documents etc…\




RDA Data for Development Interest Group:


RDA Health Data Interest Group:


RDA Small Unmanned Aircraft Systems Data Interest Group:


RDA P11 session - Ethics in FAIR Data: Ethical and practical issues of data sharing and usage within and across disciplines


RDA Plenary 13 - Data for Sustainable Development: Opportunities, Challenges and Responsibilities. (2019). YouTube. Retrieved 6 June 2019, from


Joint Session IG Data for Development, IG Health Data, IG Small Unmanned Aircraft Systems’Data - RDA 13th Plenary Meeting. (2019). RDA. Retrieved 6 June 2019, from


RDA Output Adoption Webinar Series: Outputs to Support Reproducible Health Research. (2019). RDA. Retrieved 6 June 2019, from

Review period start:
Thursday, 14 November, 2019 to Saturday, 14 December, 2019
Custom text:


Amrita Sadivaiyal Vyavasayam Kulu, a group comprising of twenty farmers,
belonging to the tribal community of Irulas, initiated organic farming at
Sadivaiyal, a tribal hamlet in the suburbs of Coimbatore, Tamil Nadu.
This paper explores the case of organic agriculture in a tribal village in
Tamil Nadu. Amrita SeRVe is an initiative launched by the Mata
Amritanadamayi Math. One of its main objectives is to motivate farmers
to make the transition to organic agriculture and hand-hold / mentor
them as they make the switch.Amrita SeRVe (Self Reliant Village project)
planned and helped the farmers from tillage, collection of seeds,
preparation of manures and pesticides, introduction of technological
innovations, modern methods in production and processing of raw
materials till the marketing of products. This experiment  tried at Sadivaiyal
united the farmers in a pristine culture of sharing, caring, protecting and
selling paddy together. This empowered them to know and bargain for
their rights. This was clearly demonstrated in their farming practices,
done without any instance of money-lending or of borrowing loans from

Keywords:  Organic Farming, Convergence Method, tribal hamlet, Bhavani rice, Tamil
                     Nadu, Sustainable development, Organic rice production, panchagavya,
                     jivamritham, mulching.


Program Manager, Amrita SeRVe, Amrita Vishwa Vidyapeetham Amritapuri Campus, Kerala, India. Email:

Article Received on: 06-10-2018                            Accepted on: 18-04-2019

Review period start:
Saturday, 9 November, 2019
Custom text: