Skills Profile Reuse data from existing sources

What knowledge, skills and attitudes or aptitudes are needed?

Knowledge

Basic Understand key characteristics of a trustworthy repository service, show familiarity with directories of these services and other reputable sources of data, code and other research outputs for the domain concerned. Understand basic metadata terms, descriptive information, constraints on reuse due to licensing or privacy conditions, and and the conversion, cleaning or normalisation techniques typically used with secondary data in the domain.

Intermediate Identify useful sources of data or code, understand how to search them. Identify good examples of data reuse in the domain, and the metadata or descriptive information used to enable this. Understand how to apply conversion, cleaning or normalisation techniques. Understand how others, e.g. Data Stewards and Research Software Engineers, may support reuse.

Expert Demonstrate expert knowledge and creativity to find, access, integrate and reuse data for novel purposes.

Skills

Basic Search for appropriate sources of data or code, find relevant material, describe techniques to reuse it.

Intermediate Demonstrate how to find, access and reuse data/ code in your domain, employing appropriate techniques to make these actionable for the current purpose, e.g. by transferring into a local workspace, cleaning and normalising to a standard, re-compiling or re-configuring code to prepare for reuse, possibly through integration with other objects.

Expert Demonstrate the ability to make reused data or code actionable for excellent research. Produce expert advice on reuse constraints due to licensing or privacy conditions.

Attitude

Basic Show willingness to look for existing data or software sources relevant to the problem, rather than creating new data by default, and seek help in doing so from colleagues and professional support services.

Intermediate Give helpful advice to students and colleagues on suitable sources and techniques for reuse, and seek advice from professional research support services where appropriate to broaden reuse opportunities.

Expert Show creativity in translating secondary data or code from its original context, to address new questions and problems, or to produce new tools to do so.

What counts as success?

Research data, code, and related outputs are found, accessed, and made to interoperate with those locally available. They are made actionable for reuse within licensing or privacy conditions, and enable excellent research, teaching or other applications.

Whose roles apply this skill?

Researcher

First stage researcher (R1) Recognised researcher (R2)* Established researcher (R3) Leading researcher (R4)

Data scientist

Data scientist (R1)* Recognised data scientist (R2)* Established data scientist (R3) Leading data scientist (R4)

Data advisor

Data steward Research manager User support, training and outreach Ethics and data protection advisor Commercialisation advisor

Data service provider

Data librarian Service manager/ project manager Research software engineer Data service architect Archivist

What related competences should the research team have?

  • Appraise and select repositories for FAIR sharing
  • Manage databases
  • Software prototyping
  • Set up and document workflows
  • File naming and organisation
  • Data cleaning, processing and software versioning
  • Creative problem solving, flexibility
  • Data transformation and integration

What capabilities – and services – would amplify this skill?

Apply policies to comply legal requirements, ethical & FAIR principles

Develops local policies and guidelines for publishing research data and related objects, and for selecting repositories that comply with relevant regulatory and policy frameworks.

  • Training and support
Prepare and document for FAIR outputs

Supports research groups to determine and fulfil appropriate criteria to reuse, manage, and share FAIR research outputs, and fulfil these expectations according to domain norms and standards.

  • Sharing and discovery
  • Data management
Data cleaning, processing and software versioning

Provides access to relevant tools, services and infrastructure.

  • Service catalogue
  • Data management
  • Processing and analysis