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Sample Identifier and Metadata Practices/Tools to Enable Interdisciplinary Sample Data Discovery, Integration, and Reuse Across Multiple Data Systems.

  • Creator
    Discussion
  • #134075

    Lesley Wyborn
    Participant

    Collaborative session notes: https://docs.google.com/document/d/1RK3bnyt_7bUeYR-znhMcVul_P7fcqx15xzjnPtdowCw/edit?usp=sharing

    Welcome (5 minutes)

    Logistics & overview of session objectives, invitation to fill in attendance and invite participants to enter their samples projects in a crowd-sourced catalogue

    Review of ‘23 things’ Physical Samples (10 minutes)

    An overview of practical, free, online resources and tools (DRAFT)

     Five-minute Lightning presentations on various major systems developing infrastructure for samples (20 minutes) 

    ESIP Samples Cluster: Draft Journal Guidance for Physical Samples and Associated data – Sarah Ramdeen

    New Projects and updates: iSamples/Sampling Nature – Sarah Ramdeen (on behalf of Kerstin Lehnert)

    Metadata Mapping (iSamples) – Steve Richards

    Update on partnership between DataCite and IGSN – Jens Klump

    Deep Dive: Use cases on Linking Related Physical Samples and Interdisciplinary Data. Introduction to the breakout sessions on reviewing identifiers, key metadata elements, and/or coordination efforts required for interdisciplinary sample data discovery, integration, and reuse across multiple data systems  (5 minutes) Joan Damerow

    Three concurrent breakout sessions (30 minutes each), selected by attendees on:

    Interdisciplinary Sample and Data Discovery (Steve Richards)

    Sample Meta(data) Access and Linking across Data Systems (Joan Damerow)

    Reuse of samples and data: what metadata is critical to ensure credit? (Lesley Wyborn)

    Circle back (15 minute) on: Joan Damerow

    Interdisciplinary Discovery

    Access and Linking

    Ensuring Credit in Reuse of Samples

     Synthesis and Next steps (5 minutes) Lesley Wyborn

    Additional links to informative material

    Group Page

    https://www.rd-alliance.org/groups/physical-samples-and-collections-research-data-ecosystem-ig

    Case Statement:

    https://www.rd-alliance.org/group/physical-samples-and-collections-research-data-ecosystem-ig/case-statement/physical-samples

    IGSN 2040 announcement:  https://blogs.ei.columbia.edu/2018/07/20/sloan-foundation-grant-open-science/

    Papers from the Linking Environmental Data and Samples Symposium, Canberra, May 2017

    Beijing Declaration on Research Data: http://www.codata.org/news/361/62/The-Beijing-Declaration-on-Research-Data

    ESIP: Vocabularies for rock type categories https://sched.co/jMO5

    iSamples: High level vocabularies for cross domain physical sample indexing https://doi.org/10.5281/zenodo.5123606

    ESIP Physical Samples Cluster https://wiki.esipfed.org/Physical_Sample_Curation

    Sampling Nature RCN https://www.samplingnature.org  

    Applicable Pathways
    Data Infrastructures – Organisational to Environments

    Avoid conflict with the following group (1)
    ESIP/RDA Earth, Space, and Environmental Sciences IG

    Avoid conflict with the following group (3)
    RDA for the Sustainable Development Goals IG

    Contact for group (email)
    lesley.wyborn@anu.edu.au

    Group chair serving as contact person
    Lesley Wyborn

    Meeting objectives
    There have been a number of systems developed for the unique identification and description of physical (material) samples. Interdisciplinary variations are inevitable and must be supported by the infrastructure since no single facility or approach will suit all. However, sample identifier and metadata practices and tools developed within a single discipline must still enable data discovery, integration and reuse across multiple data systems. There has to be a balance between enabling interdisciplinary aggregations, without impacting on deeper disciplinary descriptions within the local or community-specific variations, that would enable greater and more effective use/reuse of a sample and its related data artefacts (e.g., observations, images, analytical data). 
    What is required is a global ‘Framework’ that will leverage common elements within each ‘System’, but will still allow some inevitable differences to enable each ‘System’ to also meet its stakeholder needs. 
     
    The objectives of this session is to bring together the global samples community to determine the key metadata elements across multiple sample communities that enable:

    Sample and data discovery; 

    Sample (meta)data access and linking across systems; and 

    Ensuring credit in reuse of samples and data.

    Please indicate the breakout slot (s) that would suit your meeting
    Breakout 1, Breakout 2, Breakout 3, Breakout 6, Breakout 10, Breakout 11

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