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Minimum Viable Skills for Early Career Researcher

Introduction: Open Science mission for this role

Early career researchers for the purposes of this Minimum Viable Skillset (MVS) include PhD students, postdoctoral researchers, and other researchers within 5 to 8 years of completion of their doctorate degree. The MVS addresses the competencies and skills needed by researchers in the early stages of their research career as is related to Open OS.   

A key principle of Open Science (OS) is that research is conducted openly and transparently leading to better science. Subsequently, researchers at every career stage have a key role in the promotion of Open Science and its practice. Researchers have a key role in the promotion of Open Science (OS) and its practice. Not only do early career researchers contribute to the wider uptake of skills, building their own individual skills and organizational capacities, openness is at the core of the researchers role.  They are an integral part  of all production and dissemination of knowledge.

OS can be facilitated via data sharing, exploring and reusing data and, data publication, and making codes available, promoting open research through peer review, and reproducible research. By adopting  OS  approaches, researchers work to ensure that the  benefits which openness brings, such as the accessibility,  reproducibility and transparency of research, are available to  students, colleagues, and to society as a whole.

Early Career Researcher

Associated function titles:

  • PhD students

  • Post-doctoral researchers

  • Other researchers (working outside of academia and research councils)

Essential skills and competences

  • Good understanding of OS and its practices, in a discipline-specific context, particularly knowledgeable of policies, opportunities and practices of OS (e.g., open access, data storage and archival).

  • Sound knowledge of the data life cycle and adequate capacity to implement discipline-specific FAIR principles.

  • Ability to assess FAIRness of existing resources and make OS-compliant choices to capture, process, analyse, and preserve data

  • Upgradable digital skills: experience in using tools for conducting research, managing  and sharing research output. Commitment to undertaking training on digital-oriented research practices

  • Research management skills: Ability to design an open research strategy, implement an open research vision, and coordinate research activities that embed open science principles

  • Entrepreneurial skills: Ability to identify and apply for OS funding opportunities; ability to acquire funding that furthers open science goals, writing grants and funding applications

  • Good understanding of the relevant legal aspects related to research and their field of expertise, and relevant Open Science practices, including, but not limited to: Intellectual Property Rights (eg copyright, patents, and trade secrets) and other Non-Personal Data (eg use of IoT data and research data), Personal Data Protection and Governance (eg processing Personal Data under the current legal framework, and following existing policies on Data Protection), Privacy, and (Open) Licensing rules and frameworks.

  • Good understanding of ethical principles (e.g., transparency, diversity, and accountability) and best practices (e.g., avoiding bias in data processing when using data-driven technologies) applicable to their field of expertise, including, but not limited to the general ethical principles, frameworks and codes of conduct applicable to research (e.g., the RRI Framework; the European Code of Conduct for Research Integrity).

  • Ability to balance (personal and non-personal) data protection requirements with Open Science/FAIR principles.

Soft/transversal skills

  • Cooperation and collaboration skills.

  • Ethical orientation towards open science principles and their broader social goals.

  • Adaptable: ability to build openness into the research process, staying up to date with research processes, software, data management systems, etc.

  • Time management skills: incorporate Open Science/FAIR practices in a timely way during the research cycle.

  • Communication and interpersonal skills: engage with a variety of stakeholders.

  • Project management

  • Presentation skills

  • Critical thinking

Background assumptions

Main activities

  • Promotes and supports Open Science (OS), which includes joining and supporting its initiatives.

  • Produces research data for management, analysis, use, reuse, and dissemination.

  • Collaborates with informal and formal research groups, including training students and other early career researchers on OS.

  • Interacts with the general public to enhance the impact of science and research.

  • Communicates research for scholarly and societal impact.

  • Publishes research openly, providing metadata, data, code publicly available.

Open Science activities are apparent in all aspects of the early career researchers work flow. In conducting research, the early career researcher participates in additional activities essential to Open Science, including the following:

  • Open access publishing, which can be applied to peer-reviewed journal articles, theses, book chapters, monographs, and conference papers.

  • Opens data, which involves making all data that are necessary to reproduce reported results publicly accessible and digitally shareable.

  • Opens materials, which includes having all components of the research methodology.

Contributes to which Open Science outcomes?

By adopting the Open Science (OS) approach in their work, the early career researcher ensures that their research is carried out with a high degree of transparency, collegiality, and research integrity.  Mainly, by adopting OS approaches and practices, the early careers researcher contributes to:

  • Sharing research input and outputs

  • The adoption and practice of OS and FAIR principles and methods

  • More efficient use of scientific information

  • Improvement of the dissemination of knowledge

  • Improvement of the reproducibility of scientific findings

Further information -- Open Science skills terms

OS skills terms match the essential skills in this MVS to competence definitions from relevant taxonomies. Terms are selected to add further information and to aid discovery of this MVS (an extended list is added at the foot of this document). Sources: European Skills, Competences and Occupations ontology (ESCO), ResearchComp, terms4FAIRskills, Center Scientific Collaboration and Community Engagement.

ESCO Research Skills: Manage open publications; Operate open source software; Demonstrate disciplinary expertise; Manage findable accessible interoperable and reusable data; Manage research data; Apply blended learning; Draft scientific or academic papers and technical documentation; Perform scientific research; Apply for research funding; Manage intellectual property rights; Apply research ethics and scientific integrity principles in research activities; Perform project management;Communicate with a non-scientific audience.

ESCO Transversal Skills:  Think critically; Demonstrate willingness to learn; Manage financial and material resources; Show entrepreneurial spirit; Comply with regulation; Respect confidentiality obligations; Build networks; Use communication and collaboration software; Demonstrate intercultural competence; Work in teams; Demonstrate trustworthiness; Show determination; Cope with stress; Adapt to change; Accept criticism and guidance; Demonstrate curiosity; Think innovately; Keep an open mind; Maintain psychological well-being; Work efficiently; Maintain concentration for long periods; Manage time; Participate actively in civic life; Address an audience; Plan; Lead others; Meet commitments; Organise information, objects and resources; Build team spirit; Show initiative.

ResearchComp: Disciplinary expertise; Analytical thinking; Manage personal professional development; Strategic thinking; Systemic thinking; Write research documents; Develop networks; Interact professionally;  Communicate to the broad public; Disseminate results to the research community.

Terms4FAIRskills: Data policy; Data costs management; data sharing and publication; Assessment on FAIR data criteria; Domain knowledge to contextualise data handling; Research integrity process design; Data processing;Data curation; Data costs management; crediting research contributors; data processing; open peer review; persistent identifiers management;Data access risk assessment and mitigation; Ethical application of patents, licenses; Research governance.

CSCCE: Strategy development; Content planning; Operational planning and implementation; Engagement; Project/programme design; Collaboration; Consultation and listening; Speaking and presenting.

Contributors

Dominique Green, Saba Sharma, Irakleitos Souyioultzoglou, Gabriela Torres-Ramos, Claire Sowinski, Karolina Dostatnia, Luca Schirru, Angus Whyte, Eva Méndez

Link to any other MVS that this MVS is based on (from those in Skills4EOSC D2.1)

Reference sources

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  6. Laurence Gatto. An early career researcher’s view on modern and open scholarship. 2017. URL: https://doi.org/10.5281/zenodo.995702. ↩

  7. Michal JanÍčko, Zdeňka Šimová, and Denise McGrath. Skills of phd graduates for open science and open innovation. Lifelong Learning - celoživotní vzdělávání, 12(2):119–146, 2022. doi:https://doi.org/10.11118/lifele20221202139. ↩

  8. LERU. Open science and its role in universities: a roadmap for cultural change. 2018. URL: https://www.leru.org/files/LERU-AP24-Open-Science-full-paper.pdf. ↩

  9. Universities Norway. Nor-cam–a toolbox for recognition and rewards in academic careers. 1er juin, 2021. ↩

  10. Y. Demchenko. Edison data science framework: part 4. data science professional profiles (dspp), release 2. 2017. URL: https://edison-project.eu/sites/edison-project.eu/files/attached_files/node-486/edison-dspp-release2-v04.pdf. ↩

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