Supporting the engagement of disciplinary research communities with the European Open Science Cloud
RDA4EOSC was funded through an EOSC Secretariat Co-creation grant and brought together the Research Data Alliance, the Digital Repository of Ireland and the Digital Curation Centre in an initiative aiming to support the internationalisation and implementation of EOSC by leveraging the strengths and network of the Research Data Alliance.
The first of six pillars of activities was focused on supporting the engagement of disciplinary research communities with the EOSC and subscribed to carry out a mapping of the state of awareness and readiness of various disciplinary communities with the goal of identifying under-represented disciplines and providing recommendations to reduce gaps and increase engagement with the EOSC. What follows is a report on the mapping activity, findings and recommendations.
This assessment exercise builds upon the work of the EOSC Executive Board Landscape Working Group and that of the Landscaping Task Force (the later also consisting of representatives of EOSC Regional Projects including EOSCPillar, EOSC-Nordic, NI4OS-Europe, EOSC Synergy, ExPaNDS, FAIRsFAIR). The TF created an initial list of indicators by exploiting the requirements of the Landscape Working Group in collaboration with EOSCsecretariat.eu and EOSChub.
In addition it builds upon the recommendations for research communities highlighted in the SRIA aimed to help them progress towards an open science ecosystem that is based on, incentivises and facilitates open science principles and practices in performing and sharing science. Research communities should:
- Normalise their open science scientific processes (standards);
- Regulate them (policies);
- Facilitate their implementation (guidelines and frameworks, e.g.information models that describe flows and elements);
- Make sure their thematic services embed open science aspects by design (roadmaps).
(p. 12, European Commission. Directorate General for Research and Innovation. & EOSC Executive Board., 2021)
From this point of view, this mapping exercise can be seen as a higher level overview that has aimed to look into standards, policies, frameworks, roadmaps, registries and catalogues as well as other elements present and adopted within a community that enable interoperability and federation and the progress towards Open Science. Training and skills and networks, professional associations and initiatives supporting community building were also included as indicators illustrating the social bridges vital for sustainable implementation.
Aims
It is difficult to represent the state of awareness and readiness of domains and disciplines or more precisely of a domain or disciplinary community in a straightforward quantifiable manner. The landscape is fast evolving, making accuracy and completeness of any such effort challenging.
This report aims to provide an approach that can be further expanded to address any issues of accuracy and completeness, but should be seen as a snapshot in time of a series of indicators of awareness and readiness for the engagement with EOSC of various disciplinary research communities.
Target audiences
It has three specific target audiences as it aims to outline needed work that can be taken forward in the future:
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RDA and RDA disciplinary communities - this lays the foundations for the RDA activities within the framework of the EU funded EOSC Future project (INFRAEOSC-03)
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Representatives of disciplinary communities (individually or collectively)
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EOSC support structures, initiatives and projects aimed at improving disciplinary engagement
“The goal of the EOSC is to make research data and software in Europe open and accessible to all researchers - Findable, Accessible, Interoperable, and Re-usable (FAIR). EOSC will be implemented by joint efforts between the European Commission (EC), the EU MS and AC, research communities, and other stakeholders. EOSC is a federated structure with a central core of standards and services that interlinks with national and institutional resources and research infrastructures providing data and services. “ (p. 5, European Commission. Directorate General for Research and Innovation., 2020)
When providing a definition of “Research communities” the Landscape of EOSC-Related Infrastructures and Initiatives report (p. 7, European Commission. Directorate General for Research and Innovation., 2020) highlights the key challenges and some of the limitations that are discussed later in this report: the research communities compose a very broad, complex and fragmented stakeholder grouping due to specialisation, technological and social factors, types of outputs and research goals.
The communities are seen as both consumers of cloud services and data as well as producers, particularly of the latter. “This is a broad class of consumers and identifying key contact points and the right organisation scheme to engage community members is a complex task. “ (p. 8, European Commission. Directorate General for Research and Innovation., 2020)
Engagement of the research communities has always been a priority and adoption and buy-in has been encouraged through a series of demonstrators, use cases focusing on generic or thematic services and infrastructure, specialised and generic training, policy and strategy development. Although progress has been significant, the landscape remains fragmented.
Balancing horizontal, cross-cutting solutions and disciplinary specificities remains a challenge: “The [Competitiveness] Council highlighted the need to respect established practices and existing principles developed by research communities, the European Strategy Forum on Research Infrastructures (ESFRI), the RIs, the e-infrastructures, and the national infrastructures when implementing the EOSC”. (p. 8, European Commission. Directorate General for Research and Innovation., 2020)
The EOSC SRIA highlights the importance of building a user and research centered commons, that is community-driven first and foremost. Its nature will allow connections with diverse stakeholders and contributors such as existing pan-European and international initiatives, infrastructures and bodies like the ESFRI, e-IRG, GO FAIR, CODATA, WDS, OECD etc strengthening participation and validation of practices, tools and services and research outputs.
Phases
This report aims to map awareness and readiness levels based on a set of indicators that reflect on the activities and developments in terms of infrastructures and services, policies and practices of domain communities relevant for their engagement with the European Open Science Cloud.
The assessment was run in the following phases:
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A set of 15 domain / disciplinary communities were identified and a matrix based on 6 key generic indicators was set up to for data collection
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An initial data collection and assessment was performed, based on that the list of target domain / disciplinary communities was reduced to 5 deemed as underrepresented
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The reduced list was the focus of a second round of data collection. This included feedback from representative organisations / researchers belonging to these communities and is an ongoing process.
The indicators
As detailed in the Background section of this report, this effort leverages the work of Landscaping TF on a proposed set of indicators in five macro key areas: Architecture, Organisation & Governance, Policies, Infrastructure, Training and Skills.
As this is a smaller scale study, focusing on a broader and higher level assessment, a more concise set of indicators was defined to meet its objectives:
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Technical enablers (Technical indicators) |
Community/domain infrastructures /repositories/services facilitating interoperability, PIDs, quality control, citation and sharing |
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Community / domain dataset catalogue(s) / registries / federation mechanisms in place/planned |
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Community/domain metadata standards and vocabularies other best practices and / or technical resources |
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Social enablers (Social indicators) |
Community / domain initiatives and consolidated communities; |
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Community / domain specific roadmaps and domain OS/RDM/FAIR policies (possibly referencing EOSC) |
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Community / domain curricula, training & skills development programmes (possibly referencing EOSC) |
Additional information was collected in connection to the RDA as enabler
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Leveraging the RDA |
Related RDA groups / CoP |
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RDA Community / Organisations / People |
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RDA resources |
We are aware that the way the indicators were defined / summarised, the data sources selected and consulted, data collected and discussed, as well as the judgements on what constitutes enough detail to be meaningful may not be shared and might have resulted in the exclusion of aspects that might be particularly relevant to some communities, actors or stakeholders.
To help that and to facilitate further improvements and developments to the assessment as well as an aid to transparency the assessment matrix is available and can be accessed via an open spreadsheet at RDA4EOSC_Assessment Matrix Disciplinary Engagement
Details on the indicators and data sources
Historically the Research Infrastructure (RI) have been a contact point with the disciplinary communities they serve - the thematic infrastructures have been pillars that have helped consolidate communities around services and best practices, training and knowledge sharing, and opportunities for collaboration. The study has particularly looked into the ESFRI landmarks and projects.
The EOSC portal is an important reference and data source for this study and the motivation relates to how it is at the moment reflected in the EOSC related literature: “The current offer of services and resources is managed by the EOSC Portal via the EOSC Catalogue and Marketplace. The EOSC Portal serves as an entry point to EOSC services and resources from various domains by enabling users to access and request e-infrastructure services supplied at institutional, national and regional levels, enabling them to process and analyse data in a distributed computing environment.” (p. 13, European Commission. Directorate General for Research and Innovation., 2020) There is however a need for more clarity around the role the EOSC portal will play in the EOSC ecosystem, will it be one of the multiple entry points or it will serve a more pivotal role?
Why look at disciplinary standards and vocabularies ?
The use of disciplinary standards and vocabularies enables the production, use and re-use of data produced by compliant tools and services by that specific community. This ensures quality and enables interoperability. Rich metadata standards particularly enable wider usability of data and ensure reuse. Vocabularies support semantic interoperability.
Why look at policies?
Defined domain specific policies for data management address protocols and best practices as well as specific IPRs or ethical issues and constitute a solid base that allows and facilitates the subsequent harmonisation across domains. They regulate the practices and can support automated data management.
Why look at training and skills priorities and offer?
A key area where disciplinary specificities are particularly manifest is that of the skills and training - beyond the essential need of having skilled people to support the developments of EOSC and leverage its full potential - skills and training are one of the most efficient vehicles for community engagement.
In informing this report we leveraged a series of disciplinary classifications including the OECD Frascati and the ESFRI one in order to outline the target list of domain communities (discipline / sub-discipline) that would constitute the subject of this analysis:
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1 |
Agricultural and veterinary |
Agriculture, forestry and fisheries |
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2 |
Engineering and technology |
Engineering/ Wind energy |
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3 |
Engineering and technology |
Engineering / Materials Sciences |
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4 |
Humanities and the art |
Language and literature/Linguistics |
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5 |
Humanities and the art |
Arts / Cultural heritage |
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6 |
Medical and health sciences |
Health Sciences |
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7 |
Medical and health sciences |
Bioinformatics |
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8 |
Natural sciences |
Space sciences / Astronomy |
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9 |
Natural sciences |
Computer and information sciences / Librarianship, archival science and information Science |
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10 |
Natural sciences |
Chemical sciences |
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11 |
Natural Sciences |
Biological sciences/ Biodiversity |
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12 |
Natural Sciences |
Earth and related environmental sciences |
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13 |
Social Sciences |
Social sciences / Social survey / Health ageing retirement |
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14 |
Social Sciences |
Media and communications/ Scholarly communications |
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15 |
Social sciences |
Public sector information / Open government data / SDGs |
Data collection
Underlying data and data sources
The set of indicators were deemed as suitable and the target communities / domains identified were used to build an assessment matrix . A set of visualisations were developed based on the matrix allowing a more straightforward comparison between the domains targeted by this assessment.
The information was collated in the assessment matrix and included links to the main data sources:
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Data sources |
Reference topic/ indicator |
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[1] |
EOSC Portal and Marketplace |
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[2] |
ESFRI |
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[3] |
Re3Data |
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[4] |
RDA Metadata standards catalogue |
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[5] |
FAIRsharing.org |
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[6] |
CatRIs |
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[7] |
EOSC Projects / Communities / ESFRI Clusters / Thematic clouds |
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[8] |
Domain Data Commons |
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[9] |
RDA for Disciplines |
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[10] |
FAIR Initiatives: FAIRsFAIR, GOFAIR |
Supporting data sources for the specific community information such as ESFRI landmark websites, reports and resources were also included.
Other data sources drawn upon include the EOSC Executive board reports https://eoscsecretariat.eu/eosc-governance/eosc-executive-board-outputs
There is currently no authoritative source listing all repositories, infrastructures, policies etc We have tried to build a more detailed picture by collecting data from diverse sources.
The data collected can only be described as indicative. More detailed data and a more extended analysis is needed to address progress against higher level indicators set for the EOSC and the more granular aspects that highlight the disciplinary specificities.
A more granular benchmarking exercise against the development of other more advanced disciplinary communities is also highly recommended to highlight common aspects as well as differences.
The choice of discipline (e.g. natural sciences) and sub-discipline (e.g. Biological sciences/ Biodiversity) was meant to provide a clear example and a focus for the mapping of indicators. There is much diversity of approaches and levels of specialisation within disciplinary fields making an overarching assessment too broad and generic and less actionable.
The values of the indicators are discipline specific, these do not reflect the usage of generic infrastructures or services, domain agnostic standards, tools or resources.
The set of indicators selected provide a snapshot of a current assessment of the various research communities as well as suggesting a flexible method to track and update this assessment going forward.
Although there is flexibility to this we can say that the social indicators selected reflect aspects of awareness while the more technical indicators speak of issues related to the readiness. To further visualise this we are also using the traffic light system of the three levels of interaction with EOSC:
Green: Aware, ready and prepare
Orange: Aware but not ready or Ready but not aware
Red: Unaware and unprepared
Based on the findings in the assessment, we have expanded on the “Orange” indicator to also cover the case where the community is ready, has made considerable progress regarding disciplinary infrastructure and services, interoperability and federation but is unaware of the EOSC or there are no clear connection or engagement present.
While it has proved challenging to obtain definitive quantitative and qualitative data relevant across domains or domain specific, it can be noted that clear activities are ongoing within all domains with different “maturity” levels. In some cases the different degree of specialisation can become a barrier to interoperability and developing and adopting integrated solutions.
Understandably the domains where ESFRI landmarks have been active, are much more advanced with respect to the domains that are only at the early stages of such implementations. The landmark projects have supported the development of a comprehensive infrastructure and have consistently invested effort in addressing the social aspects as well such as building the community and understanding incentives and practices.
There are five such cases where the work is being taken forward considering an EOSC specific context. These have been commonly referred to as EOSC ESFRI clusters projects EOSC-Life, ENVRI-FAIR, ESCAPE, SSHOC and PaNOSC. The focus and strengths of these differ from strong federation e.g. ESCAPE to the diversity of services e.g. ENVRI-FAIR or training and skills e.g. SSHOC - their approaches aim to closely consider the disciplinary perspectives and requirements: “The overall expectation of these projects is that EOSC will enable the accessibility and re-use of research data, increase scientific value of research data, and deliver an interoperable environment of data infrastructures. The projects expect EOSC to bring the added values of the infrastructure for sustainable use of research data and a virtual research environment enabling real-time collaboration between researchers using FAIR data.” (p. 3, Gotz et al., 2020). Considering the aims and structures, these are also considered discipline specific research commons under the wider umbrella of the EOSC - a regional research commons itself and are in the green position of the signalling system: both ready and aware of the EOSC.
Natural sciences, especially Earth & Environmental Sciences and Biological Sciences - most data catalogues on EOSC Portal Marketplace; also highest number of services for data management, processing and analysis. These disciplines have an approach that due to their data-intensive nature has prioritised the technical aspects and tended to build the social bridges and focus engagement and training around that.
Most disciplines explicitly prioritise development of common standards especially metadata standards and share those through cross-disciplinary catalogues such the RDA Metadata Standards catalogue, FAIRsharing, both key RDA flagship Recommendations, maintained or community driven.
Discipline specificities determine tailored approaches e.g. working with sensitive or personal data requires communities like the health and medicine and social sciences to prioritise AAI developments while supporting cross disciplinary approaches that bring value add.
There are few disciplinary roadmaps or domain overarching OS/RDM policies – the more consolidated ones come from the cluster projects but there are a few exceptions such like the Joint Programme on Wind Energy of the European Energy Research Alliance (EERA JPWind) underpin by a variety of projects and is a successful example of disciplinary roadmap and approach to consolidating disciplinary governance.
The Joint Programme on Wind Energy of the European Energy Research Alliance (EERA JPWind) is also an example of how to potentially navigate or address the gap between industry interests and the academic agenda as it has seen support and alignment from both the private as well as the public funded research.
Most of the communities assessed find themselves in the orange position of the signalling system as they are either aware but not (fully) ready or ready but not aware of the EOSC and the benefits of engaging with the EOSC community and joining the effort. The Research Data Alliance through its structures and fora is a vehicle for addressing both challenges, and build the social and the technical bridges required, especially through the set up of the disciplinary communities of practice designed to create a coherent overarching approach to disciplinary challenges.
Following the initial phase of the mapping a series of disciplines have been selected for further data collection and analysis as deemed underrepresented within the ESOC. These are:
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Engineering and technology / Engineering/ Wind energy
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Engineering and technology / Engineering / Materials Sciences
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Natural sciences / Chemical sciences
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Natural Sciences / Biological sciences/ Biodiversity
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Social sciences / Public sector information / Open government data / SDGs
The fear of data misuse and the loss of economic advantage has delayed for many years the developments related to data sharing in the domain of Wind Energy. The wider adoption of the FAIR principles and the goal of “as open as possible as closed as necessary” has helped unlock some of the barriers as the wind energy community is embracing the potential of wider data sharing in a trustworthy and standardised way. This, coupled with the release of the Joint Programme on Wind Energy of the European Energy Research Alliance (EERA JPWind) and related funding, has fuelled many of the recent developments in the discipline including community driven tools and service development, taxonomies and community standards, infrastructure.
The work around the EERA JPWind is underpin among other by initiatives like ESFRI WindScanner project and the supporting research infrastructures or the ShareWind project laying the foundations of a data management system for the EERA JP Wind, a key building block that leverages cross disciplinary solutions to help support wider collaboration. By bringing together research and industry, the goal is to support data exchange using domain specific metadata with specific taxonomies, via web-based data registries, increasing citation via DOIs, and findability via catalogues. A federated data model is foreseen, built on top of existing data infrastructures. The EERA JP Wind looks at linking distributed data from different data sources and thus aligning with the European Open Science Cloud.
At the moment the connection appears limited, no tools, services or training resources dedicated to the wind energy domain are available in the EOSC Marketplace. Although there is significant work in bringing together the community around the objectives of the EERA JP Wind, including European Wind Energy Association, the European Wind Industrial Initiative or the European Academy of Wind Energy, considerable work will have to be done around increasing awareness of EOSC and ensuring that the building blocks being put into place with in fact ensure interoperability with EOSC and a federation under the EOSC umbrella.
The challenges in the field are data intensive and require a coordinated approach that supports testing, modelling, resource assessment and spatial planning.
Often referred to as Materials Sciences and Engineering or (MSE) this is a broad domain one that is closely connected to other data intensive disciplines like physics or chemistry. Within the new paradigm of data-driven science, the development of new materials and the improved study and understanding of the existing materials has increasingly been seen as dependent on the developments in terms of the discovery, access, and interoperability of experimental and simulation data in the field and cross-disciplinary. A series of programmes and initiatives have been set up to drive these efforts leveraging the opportunities open science is yielding. Many of these have focused on the development of building blocks for research data management.
Developments are fragmented due to the funding mostly national or regional and traditional or discipline specific gap between industrial and academic interests and agendas. The EOSC offer the opportunity of addressing these issues while leveraging structures and work like the FAIR-DI in Germany, the European Commission Joint Research Center materials database (MatDB) and connecting that to international initiatives like the Materials Genome Initiative (MGI) and MaterialsCommons.org, and the Materials Research Data Alliance.
Currently three resources related to materials sciences are listed on the EOSC Portal, two of which are repositories that serve the community and a complete infrastructure for automated workflows for advanced simulations.
Within the RDA, two groups focus particularly on materials sciences data. One is the joint RDA/CODATA Materials Data, Infrastructure & Interoperability IG focusing on the standardisation and interoperability efforts for materials data. The Interest Group has lead the set up of a more focused working group on International Materials Resource Registries aimed at piloting an international federation of data resource registries to enable data discovery.“A resource registry is a system that harvests and makes searchable high level metadata descriptions of resources held by data repositories, archives, organisations, websites, and services to aid scientists in industry, universities, and government labs in the discovery of data relevant to their research and work interests.”
Key recent progress in the field of research in chemical sciences has revolved around standardising formats for storing and sharing chemical data as well as how to make that data interoperable with other research data and enhance it semantically to ensure reuse.
The interoperability and sharing of chemistry research data is of considerable value as it has fundamental impact on the fields of health, pharmaceuticals, materials, energy and many other applied sciences
Although there has been disciplinary progress in the development of solutions, especially technical ones, few of these have proved to be sustainable and interoperable. “There is a demonstrable need for coordinated development of updated and scaled infrastructures, hard and soft, for enabling chemical data exchange and connecting data providers with data users across sources and applications.” The EOSC aims to provide a framework for such a coordinated approach and support disciplines in strengthening their value propositions across the research landscape, as it builds on cross community interoperability and federation efforts.
At the moment there are two resources listed on the EOSC portal of relevance for the domain of Chemistry although not specifically designed for Chemical sciences data (a computational notebook solution and a computational material sciences certified data repository). This highlights both needed work to increase the awareness levels within the community as well as readiness issues.
The disciplinary practices in chemical sciences, in their traditional approach have also been an area of intense reevaluation and cultural change “Long traditions of small laboratory culture and strong proprietary and commercial value impact the overall adoption and incorporation of open data exchange and high performance computing directly in research chemistry outside of a few sub-disciplines (e.g. drug discovery).“ There is considerable fragmentation as organisations or groups have developed solutions in a silo, without a systematic approach that would allow access and reuse, or long term sustainability.
As highlighted by disciplinary practice survey work (Herres‐Pawlis et al., 2020) , there are remaining gaps in the digital processing and management of chemistry data but researchers are increasingly aware of the benefits of standardized RDM workflows, long-term archiving and metadata annotations for their data. The workplan of the NFDI4Chem is an example of coordinated disciplinary efforts focused on strengthening the technical side through virtual environments supporting federated repositories and the use of digital tools at all stages, strengthening an international community development process for metadata standards for data and machine readable metadata, as well as supporting FAIR and RDM training and skills development. (Herres‐Pawlis et al., 2020)
The EOSC portal currently lists 14 different resources for Biodiversity of which 13 relate to Processing & Analysis and 1 for Training & support. Most of these are part of the BlueBRIDGE Biodiversity services, a group of services that is domain specific and covers standardised data access, species modeling, support for data publication and other intermediate steps in the data management lifecycle. Related applications from D4Science are provided for the management of spatially referenced resources.
There is significant work done at international level to enable biodiversity data management and sharing especially through organisations and initiatives like the TDWG Biodiversity Standards, the Global Biodiversity Information Facility (GBIF), The Society for the Preservation of Natural History Collections (SPNHC),The Barcode of Life, Catalogue of Life, the Biodiversity Heritage Library (BHL) and the IUCN Red List
Connections with the EOSC don’t seem to be very strong. Although there is considerable disciplinary progress in terms of standardisation (community standards development procedures like TDWG) and common data exchange formats (Darwin Core), descriptions and semantically enhances publishing an area that is still lacking is that of the interoperability and cross-disciplinarity . In the future this can constitute a key driver for engagement in EOSC and a clear value add and proposition for the biodiversity data community especially considering the close relationship of the Biodiversity discipline with other domains that are well represented within the EOSC such as Agriculture, Biomedical Life Sciences, Environmental Sciences and Earth Sciences.
Within the RDA, the newly restructured and purposed group on Biodiversity Data Integration Interest Group (BDI IG) has focused on linking the biodiversity community with the research data community in order to build the much needed cross-disciplinary bridges and improve interoperability. The group has been promoting the use of RDA Recommendations and Outputs in the development of tools, services, workflows and policies for an interoperable and FAIR by design approach and aims to provide guidelines for application in biodiversity data. The group, without specifically referencing the EOSC, works both on issues related to readiness and awareness, for FAIR principles implementation, the BDI IG aims to connect with the BiodiFAIRse Implementation Network in order to collectively build communities of practice. The group can find in EOSC the perfect framework to work on a key aim”crossbreed biodiversity standards and solutions with other domains in order to achieve cross-domain interoperability”.
Interoperability and federation in the domain can unlock immense research, social and economic value: “Scientists will be able to engage in multi-disciplinary initiatives to address the key global challenges of the twenty-first century such as climate change, health, food and biodiversity or building energy-efficient vehicles and smarter cities. More generally, all efforts dedicated to achieving the 17 Sustainable Development Goals of the United Nations [UN_SDG] would benefit from access to a wide set of information coming from very different origins.” (p. 19, European Commission. Directorate General for Research and Innovation. & EOSC Executive Board., 2021)
There are many national initiatives focused on building public sector or open government data portals and data sharing practices and policies. This is a result of the Directive 2003/98/EC on the re-use of public sector information, known as the PSI Directive, now called Open Data Directive,an EU directive that encourages EU member states to make as much public sector information available for re-use as possible. The directive focuses on both the economic aspect of the re-use of information as well as on facilitating access by citizens and other categories of stakeholders, including research. Considerable development work has been undertaken in connection to the directive and the EU Open Data portal.
Very few resources on the EOSC portal have been developed for or target the area of public sector information / Open government data / SDGs. An exception is the OpenAIRE Community Gateway for the Greek United Nations (UN) Sustainable Development Solutions Network (SDSN). More generic resources targeting the broad domain of social sciences are available.
Disciplinary input is crucial and needs to be considered at all levels from how data should be formatted and described to issues of incentives for sharing and reuse and data governance and long term preservation.
Social indicators or aspects are harder to assess and more challenging than the technical aspects as these bring together individual and organisational aspects and formal and informal structures that are difficult to evaluate.
As discipline drive developments that ensure their specificities are considered, the overall EOSC community needs to focus on building an open environment that guarantees cross-fertilisation.
There are key issues of inclusiveness to be assessed and addressed from a social sciences point of view of view including. Beyond the technical inclusion (e.g. technical base used, its availability and adoption, level of skill necessary) and language inclusion (Use of language, terms etc), these can include social inclusion (e.g. common goals and shared problems, low resources settings involvement), demographic inclusion (e.g. geographical provenance, education, organisational affiliation), professional inclusion (e.g. professional roles/positions, domain and area of expertise), career stage inclusion (e.g. support/inclusion for early careers, and other), newcomers inclusion (e.g. support for newcomers, induction/onboarding) (p. 9, Pickering et al., 2021).
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