Chemistry case study

Chemical substances touch on all areas of laboratory science and chemistry underlies many critical worldwide issues, including climate, health, food availability and sustainable development. Increased reporting of machine-readable chemical data will support active research in chemistry and related sciences worldwide, and will be essential to the development of the interdisciplinary science critical to address the UN Sustainable Development Goals and UNESCO’s priorities around Open Science. IUPAC is the world authority on chemical nomenclature, terminology, and standardized methods of measurement, and is engaging in a concerted effort through collaboration with the broader chemistry and data science communities to translate a range of assets and activities into the digital domain. Aligning standards development and implementation with the FAIR data principles will facilitate development of guidelines, tools and validation services that support scientists to share and store data in a FAIR manner and support the ability to compile and interpret data across scientific disciplines.

Case Study Lead(s): Leah Rae McEwen, Cornell University; Fatima Mustafa

Nanomaterials case study

This case study will enable the further adoption of the FAIR principles by the international nanomaterial community and encourage greater alignment with neighbouring disciplines and communities.

It builds on the partners’ successful collaboration in NanoCommons (a research infrastructure for nanoinformatics and FAIR nanomaterials data) and their leadership of the IUPAC InChI Trust efforts to develop a standard extension of the InChI for nanomaterials.

It will test the pilot operationalisation of the FAIR principles; run conference sessions and workshops with stakeholders (including the InChI-for-nano domain experts, and international ‘nano’ database managers and their users) to apply, refine, implement, improve the metrics for FAIR nanosafety datasets; and develop an inventory of FAIR nanoinformatics models and their domains of applicability, underpinning datasets and APIs to support interoperability, including guidelines to further improve the interoperability of nanoinformatics models.

The results will include complete human- and machine-readable nanomaterials data provenance trails that can be implemented in a straightforward way using the distributed FAIRification approach.

Case Study Lead(s): Iseult Lynch, University of Birmingham

Geochemistry case study

Through OneGeochemistry, an informal international network of national geochemical data infrastructure organisations, the geochemistry community seeks to define the minimum common variables for a set of geochemical data types and build them into FAIR Implementation Profiles, that can also be used by laboratories/ repositories/publishers for QA/QC validation of data.

Together with AuScope (Australia), GEOROC (Germany), EPOS Multi-scale Laboratories (Europe), EarthChem (US) and AstroMaterials (US), the OneGeochemistry network represents data on multiple geochemical elemental and isotope systems and instruments. All are investing in building comprehensive databases at a national scale to store, curate and make geochemical data and related digital objects (physical samples, instruments, images, tools, etc) FAIR.

Geochemistry has applications in many disciplines including environment, resources (groundwater, minerals, energy), geohealth, ocean, and agriculture: it is a component of many UN SDGs. Fundamental to our approach is ensuring that in networking common components across these disciplines, we still enable a capacity for deeper disciplinary specialisation.

Case Study Lead(s): Tim Rawling & Alexander Prent, AuScope

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Social Surveys case study

Comparative studies in social science are relatively well-established, with strong traditions of sharing data across countries to establish multi-national comparative data sets for studying cultural, social and political variations in attitudes and institutions. The EU-funded European Social Survey has regularly conducted cross-national surveys of social attitudes of the European population since 2002.

More recently, the ESS has been partnering with a number of researchers outside the EU to establish satellite studies of the ESS in Australia, Japan and South Africa. The extension of practices to these countries provide a new opportunity to compare and harmonise practices and technologies, focusing on Interoperability and Reusability.

This case study will undertake a comparative study of the data management, harmonization and integration practices of one of the satellite countries – Australia, through the AUSSI-ESS – and the core ESS, an ERIC social science infrastructure. It will then leverage the DDI metadata standards to understand how such multi-national collections could be made increasingly interoperable and reusable through shared procedural and technical development, and establish a set of guidelines and tools for the development of cross-national collections into the future.

Case Study Lead(s): Steven McEachern, Australian Data Archive, Australian National University

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Population health case study

The Implementation Network for Sharing Population Information from Research Entities (INSPIRE) project is assembling technologies and standards in support of a data hub that facilitates federated and/or shared research capable of interoperating across often-neglected low-resource settings: it aims to provide a platform-as-a-service, which can make data of disparate types available to many different styles of analysis, among which AI systems are increasingly prominent.

INSPIRE uses OMOP, a common data model that is becoming the gold standard for systematically integrating health data from disparate sources and conducting observational research at scale using routine clinical care data. However, OMOP is not completely FAIR29 and further work is needed to improve the ability to integrate diverse sources of data. This case study team will improve the interoperation of OMOP with other standards to enable machine-actionable descriptions of data structure and provenance (e.g., DDI-CDI, PROV-O, SDTL); the composition of measurements focused on the objects of research (e.g., I-ADOPT); record linkage modeling for creating and evaluating bridges that connect domains, vocabularies (e.g., SKOS); and data discovery (e.g., Schema.org, DCAT). This suite of standards forms the basis of an ‘AI-Ready’ description of data suitable for use across domain and institutional boundaries.

Case Study Lead(s): Jim Todd, London School of Hygiene and Tropical Medicine

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Urban health case study

Cities are considered the primary contributors to global environmental change and human development, being at the centre of leading mitigation and adaptation strategies that could promote human health along with environmental sustainability. Given the transdisciplinary approach of Urban Health, challenges faced within this field are also common to other areas and consequently, solutions proposed from the Urban Health perspective could also promote advancement beyond its discipline.

The SALURBAL project (Urban Health for Latin American cities) is a five-year project based at the Urban Health Collaborative, Drexel University, and with partners throughout Latin America and in the United States that studies how urban environments and urban policies impact the health of residents from almost 370 cities in 11 Latin American countries.

To pursue this goal, the SALURBAL project 1) has systematized a process for city definition and operationalization that integrates multiple ways in which a city can be delimited; 2) has created a data structure that allowed the incorporation of data from different sources, making it shareable across several cores and disciplines; and 3) has developed procedures and standards that systematically documented issues related to data access, quality, and completeness during the process of data harmonization.

The case study will explore and further refine this approach to provide recommendations for urban health data that reflect the FAIR and CARE principles and contribute to promote best practices in data sharing and use within and beyond the Urban Health field.

Case Study Lead(s): Ana Ortigoza, Drexel University

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Biodiversity case study

As a leader in open and reusable data before the FAIR principles were developed, GBIF has an influential role in generating FAIR data throughout biodiversity sciences.

All data mobilized through the GBIF network is completely free and open access with all metadata easily available. Nevertheless, the biodiversity community has determined that it is time to revisit GBIF’s core data model so that it can better implement FAIR data integration, especially in connection to the growing Digital Extended Specimen initiative. It is also becoming critically important to meet the growing need to enable the integration of new data types, especially DNA-derived data, and to better connect the growing long-term biodiversity monitoring data that isn’t currently well connected to the global data network.

Through FAIR recommendations and assessments, and a new FAIR interoperability framework at the heart of the GBIF data model, our goal is to improve our processes and thereby help the global biodiversity community to implement FAIR data standards.

Case Study Lead(s): Joe Miller, Global Biodiversity Information Facility

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Agriculture case study

Plant-pollinator interactions are recognized for their key role in ecosystem functioning and sustainable agriculture. However, plant-pollinator data are currently stored in silos across multiple networks and country-specific initiatives. The capacity to integrate those data at regional and global levels is crucial to enable pattern analysis and understanding at biologically-relevant scales. In this context, adoption of community data standards on pollination and good practices is urgently needed.

This case study will ensure broad participation and alignment with other agricultural data initiatives in Europe and at the global level to facilitate the implementation of the FAIR data principles. A survey of existing initiatives handling plant-pollinator interaction data will be conducted and an overview of the current status of best practices for plant-pollinator data management will be provided and discussed within the community for improvement. FAIR data assessment rubrics will be adapted for the plant-pollinator domain, to be accompanied by guidelines for their use. At least five agriculture-specific plant-pollination initiatives will serve as pilots for data and digital objects standards adoption.

RDA IGAD (Interest Group on Agricultural Data) is leading this effort together with partners in the Biodiversity Information Standards group already involved with developing standards for plant-pollination data in order to advance adoption.

Cae Study Lead(s): Debora Pignatari Drucker, Brazilian Agricultural Research Corporation (Embrapa)

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Oceanography case study

With the onset of the UN Decade of Ocean Science for Sustainable Development, a surge of activity focusing on ocean observation, operations, commerce, socio-economics, and culture will generate data with greater complexity, depth, and volume than ever before. However, the diverse ocean communities building new digital resources have widely variable capacities and visions in implementing the FAIR principles. As a result, entirely valid, but local/regional, FAIR implementations will still lack global interoperability. There is a considerable need to align the policies and practices across independent technologies and systems.

To this end, this case study will leverage the progress made by the Ocean InfoHub and Ocean Data and Information System (OIH, ODIS; https://oceaninfohub.org/), launched by International Oceanographic Data and Information Exchange (IODE) of the Intergovernmental Oceanographic Commission (IOC) of UNESCO. The AWI/Helmholtz partner (whose personnel chaired the technical implementation of ODIS) will examine how the ODIS Interoperability Architecture (ODIS-Arch) being piloted with regional partners can be coordinated with other case studies and central guidelines of CODATA and RDA to support digital policy alignment. The key objective will be to ensure policies support regional and local specificity, but allow the concrete implementation of global FAIRness around key (meta)data types. Through these actions, this case study aims to sustainably interface the ODIS digital ecosystem with many others.

Case Study Lead(s): Pier Luigi Buttigieg, Alfred Wegener Institute for Polar and Marine Research

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Disaster Risk Reduction case study

Harnessing data and hazard definitions and classifications is vital for disaster risk reduction, climate change adaptation and resilience, sustainable development, global health security and urban resilience. It is recognised as a crucial step in support of the Sendai Framework and the other UN landmark agreements of 2015-16.

The UNDRR/ISC Sendai Hazard Definition and Classification Review Technical Report supports these agreements by providing a common set of hazard definitions for monitoring and reviewing implementation which calls for ‘a data revolution, rigorous accountability mechanisms and renewed global partnerships’. An important step will be to make this vocabulary FAIR following the guidelines in the Ten Simple Rules.

Advances in technology have enabled a dramatic increase in the availability of satellite imagery and the power of geospatial services for DRR, yet significant challenges remain for the effective operationalization of these data for practical purposes, including societal use, policy making, rapid response etc. The FAIR principles are critical to facilitating the use of advanced technologies to extract pertinent information for DRR and climate adaptation and resilience. Developing countries face particular challenges in access and usability of data.

The application of the FAIR principles for EO data, including domain-specific FAIR vocabularies for disaster, climate change and global health for the Pacific and Africa, will facilitate the easier, and lower cost, reuse of data and the extraction of key information.

Case Study Lead(s): Bapon Fakhruddin & Jill Bolland, Tonkin+Taylor

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Cultural heritage case study

Cultural Heritage data emerges primarily from the cultural sector (not the research sector), but provides the input into research for a range of humanities disciplines, making this case study itself multidisciplinary and multisectoral.

The sharing of visual sources in particular has challenges around copyright, but also increasingly around formats, with the emergence of 3D data. More generalised issues around metadata standards, vocabularies, digital preservation and persistent identifiers also exist, and humanities disciplines have comparatively less-developed data sharing cultures. Several global image-sharing communities/platforms exist online. These communities provide massive (but not very FAIR) datasets and crucial networks for coordination.

The Digital Repository of Ireland, a CTS-certified TDR for AHSS data that plays a leading role in FAIR globally, will work with these communities to understand what practices exist, and how they could collectively be made more FAIR. Community partners include Wikimedia, Europeana, and IIIF, and may be expanded during the project. Establishing FAIR practices in these communities and networks would have a very significant effect on the sharing of cultural heritage data, and on the research data management practices across the global arts, humanities and social sciences disciplines.

Case Study Lead(s): Natalie Harrower & Beth Knazook, Digital Repository of Ireland

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