An educational institution is conducting a six-month diagnostic project on Open Research Information (ORI). The project explores how open infrastructures, including OpenAlex and OpenAIRE, could complement the institution's institutional Current Research Information System (CRIS), PURE, for research management, evaluation, and strategic decision-making.
This is a learning and decision-support project, not an implementation project. Its objective is to provide university management with an evidence-based understanding of what open research information infrastructures can and cannot currently offer. The as-is analysis has been completed. We are looking for a Data Analyst to support the to-be analysis: a structured readiness assessment of OpenAlex and OpenAIRE, as well as a comparative assessment of proprietary databases for two academic departments.
What you will do. You will work with an existing readiness assessment framework developed within the project. Your role will be to assess and document open databases (OpenAlex and OpenAIRE) and proprietary databases (Dimensions, Scopus and Web of Science) against key criteria for two academic departments, including:
- data coverage
- data quality
- available metrics
- information types
- user experience
- required skills
- required support
- governance considerations
Each criterion will be assessed against the research intelligence use cases identified during the as-is phase, such as:
- tracking research outputs
- monitoring research impact and performance
- analysing collaboration patterns
- monitoring open science practices
Your main activities will include:
- Conducting structured comparisons between open and proprietary databases, and the institutional current information system, building on existing preliminary coverage analyses
- Identifying metadata gaps, coverage differences, affiliation and DOI mismatches, and potential workflow implications
- Populating and substantiating the readiness assessment framework with evidence-based findings
- Summarising findings in a format that directly supports the project’s management advice phase
- Reporting weekly to project leads, while working closely with faculty contacts
What they ask
- A completed master’s degree in a relevant field (e.g., data science, information science, research management, social sciences, or a related discipline)
- Strong quantitative data handling and analytical skills, with experience working with datasets, sampling, and comparative analysis
- Experience with data cleaning, matching
- Affinity with bibliometrics, research information, or open science is an advantage but not required
- A precise and structured working style, suitable for a short, output-driven project
How to apply
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