1. IG Physical Samples and Collections in the Research Data Ecosystem
Rationale: Need for FAIR Samples
Reproducible sample data
Re-usable samples and data
Recognition of sample collection and curation as scholarly contribution (citation & credit).
Topics:
Persistent unique IDs
Metadata & terminology
Registries, catalogues, harvesters
Sample sharing & preservation policies & practices
Physical infrastructure for sample preservation & access
BoFs at P4 & P6
Workshop in May 2017 (Canberra, Australia)
IG endorsed Nov 2017
P11 collocated event
P11 session
Co-chairs:
Kerstin Lehnert
Simon Cox
Jens Klump
Lesley Wyborn

2. IG “Physical Samples & Collections in the Research Data Ecosystem” Objectives
Identify and characterize existing systems and solutions relevant to linking physical samples with digital research data and publications, identify gaps and challenges;
Identify commonalities and diversities across the stakeholders with aim to converge;
Facilitate international cooperation to develop harmonized approaches and best practices for physical object identification and digital curation.

3. P11 Collocated Event: Results
20 participants
International (US, Europe, Australia, Canada)
Multi-disciplinary
Organizations holding large sample collections (BGS, CSIRO, GA)
PID systems (IGSN, DataCite, EZID)
Cyberinfrastructure (DiSSCO, CyVerse, DeVL, IEDA, etc.)
Topics:
The Need for Trans-disciplinary Coordination of Physical Sample PIDs
PID Infrastructure and Governance Models
Ontologies, Metadata, and Web Representation

4. Workshop Messages
Solve the ID for samples problem, rather than the IDs for Geo or IDs for Bio problem!
PID system needs 3 pillars: Infrastructure, governance, business model (+ community)
Basic technical requirements are straightforward to solve.
Basic infrastructure should be the same and the kernel metadata should be domain/discipline/etc. agnostic.
Challenge is the governance & business model.
Make sure an identifier system survives and persists.
Infrastructure cannot be built on short term grants!
The community needs to come along.

5. PID for Samples Approach:
PID of a sample should be linked to PIDs of many different disciplinary specific and functionality specific metadata records that can be added/updated at any time.

6. The ‘Shell Model’ (credit: Lesley Wyborn)

7. Workshop Consensus
Establish a WG to develop a proposal for addressing governance, business models, policy, and best practices.
Sloan proposal submitted in April 2018
Establish a WG to compile relevant existing data models/vocabularies/ontologies and recommend a common core metadata schema for samples and an ontology for sample types.

8. RDA P11 Session Outcome: First Strike Groups
FS1: Define WG deliverables for what makes (a) sample(s) FAIR
FS2: Define WG deliverables for governance/business model/policy
FS3: Clarify Defining principles
Definitions by P12!