[Limor Peer]

Please check the virtual Plenary programme for remote access details
New dates and times to accommodate several time zones:

April 1, 9:00 pm UTC – 10:30 pm UTC: Remote access registration: https://aarnet.zoom.us/meeting/register/vJMqfuCorjwsBc6yvYrcektyinY9YX4Mrg
April 2, 1:00 pm UTC – 2:30 pm UTC: Remote access registration: https://aarnet.zoom.us/meeting/register/vpUufuGprz4rS-3TvJ-rxVXUiTCTwXR-nA

Collaborative Notes Link:  https://drive.google.com/open?id=1uaSTSTxnqk1g35Aw0gbhhfMTG-c-O_PUyrJWWQ…

You can join the groups to stay involved with their work if you are an RDA member:
Log in to the RDA Web site with your RDA userid/password, go to the group you wish to join (CURE-FAIR WG and/or Reproducible Health Data Services WG)  and press the “Join group” button on the right (near the top of the page).
If you are not an RDA member, you can join RDA here: https://rd-alliance.org/user/register (it’s free!)

Brief introduction of previous work, and discussion of the draft CURE-FAIR  WG case statement
A group discussion of WG management and next steps within RDA
Group activity on CURE-FAIR practices, gaps, and opportunities for collaboration and integration

1. First group option
CURE-FAIR WG

Additional links to informative material

BoF on Curating for FAIR and reproducible data and code (RDA14) page https://www.rd-alliance.org/curating-fair-and-reproducible-data-and-code
Reproducible Health Data Services WG https://www.rd-alliance.org/reproducible-health-data-services-wg
Reproducibility IG (historical) https://www.rd-alliance.org/groups/reproducibility-ig.html

Avoid conflict with the following group (1)
FAIR Data Maturity Model WG

Brief introduction describing the activities and scope of the group
Scientific reproducibility provides a common purpose and language for data professionals and researchers. For data professionals, reproducibility can be a framework to hone and justify curation actions and decisions, and for researchers it offers a rationale for inserting best practices early into the research lifecycle. Curating for reproducibility (CURE) includes activities that ensure that statistical and analytic claims about given data can be reproduced with that data. Academic libraries and data archives have been stepping up to provide systems and standards for making research materials publicly accessible, but the datasets housed in repositories rarely meet the quality standards required by the scientific community. Even as data sharing becomes normative practice in the research community, there is growing awareness that access to data alone – even well-curated data – is not sufficient to guarantee the reproducibility of published research findings. Computational reproducibility, the ability to recreate computational results from the data and code used by the original researcher, is a key requirement to enable researchers to reap the benefits of data sharing, but one that recent reports suggest is not being met. Data curation workflows that enable data access often fall short when research reproducibility is the ultimate goal. Code review and result verification are required in order to confirm the integrity of the scientific record, to build upon previous work to discover, and to develop innovations. Several initiatives confirm that the scientific community is embracing these ideas. For example, the CURE Consortium has been implementing practices and developing workflows and tools that support curating for reproducibility in the social sciences.
CURE-FAIR stands for Curating for reproducible and FAIR data and code.

Estimate of the required room capacity
100

I declare that I have informed the chairs of all the Working / Interest groups included in this joint meeting application.
Acknowledged

Meeting objectives

Inform attendees of the WG prior work and activities and elicit input on plans within RDA
Identify existing relevant guidelines, policies, practices, and workflows, with a focus on perspectives from a variety of disciplines
Identify potential use cases to enrich the WG output
Continue to build WG engagement and membership

Privacy Policy
1

Target Audience
We invite researchers across the disciplines, data professionals, data archivists, archive and repository managers, technologists, software developers, academic officers, publishers, and participants from related WG/IG.

Discussion