Data Management Consulting
We provide practical consultations for researchers, research groups and institutions on research data management, FAIR data preparation, repository publication, metadata, documentation, licences and data sharing.
This service helps users understand what should be done with their data before, during and after publication, and how to prepare research outputs for reuse, citation and integration with open science services.
Submit a consultation request
What this service supports
Research data strategy
We help research groups define a practical approach to organising, documenting, storing, publishing and preserving their research data.
FAIR data preparation
We advise on how to make datasets more findable, accessible, interoperable and reusable through metadata, documentation, identifiers and licences.
Repository and publication route
We help select an appropriate publication route: DataverseUA, institutional repository, domain repository, project portal or EOSC-related catalogue.
Practical next steps
We help transform a general data management question into a concrete action plan: metadata, README, DMP, FAIR pre-check, repository deposit or Data Café.
How the process works
1. Request
You submit a consultation request and briefly describe your data management question, dataset, project or research workflow.
2. Initial clarification
The Competence Center clarifies the type of support needed: general consultation, DMP, metadata, README, FAIR assessment, repository publication or Data Café.
3. Case review
The available information is reviewed: data type, current documentation, publication plans, repository needs, project requirements and possible restrictions.
4. Consultation provided
The research group receives practical guidance, recommendations and references to relevant templates, checklists, services or workflows.
5. Next steps agreed
The consultation results in a concrete set of next steps for data preparation, publication, documentation or further expert support.
What users should prepare
To make the consultation effective, users are encouraged to prepare:
- short description of the research project or dataset;
- type of data or research output;
- current state of the data and documentation;
- main question or problem to be discussed;
- information about expected publication or sharing plans;
- related publication, project, DOI or repository link, if available;
- information about authors, contributors and responsible persons;
- metadata, README, DMP or repository draft, if available;
- known restrictions, licences or access conditions;
- expected result of the consultation.
Expected outcomes
Depending on the request, the outcome may include:
- general recommendations on research data management;
- a proposed data preparation pathway;
- recommendations on metadata, README or documentation;
- recommendations on DMP preparation;
- recommendations on repository publication;
- recommendations on licences and access conditions;
- recommendations on FAIR readiness;
- recommendations on OpenAIRE or EOSC compatibility;
- referral to a specific Competence Center service;
- proposal for a Data Café session;
- a practical list of next steps for the research group.
Typical consultation topics include:
1. How to organise research data before publication
This includes file structure, naming, versions, formats, documentation and preparation of a data package.
2. How to describe a dataset
This includes metadata, keywords, related publications, contributors, methods, funding information and repository fields.
3. How to prepare a README
This includes dataset structure, file descriptions, methods, software, licence, citation and reuse instructions.
4. How to choose a repository
This includes DataverseUA, institutional repositories, domain repositories, project repositories and repository requirements.
5. How to plan data management
This includes DMP preparation, data lifecycle, storage, backup, access, sharing, preservation and responsibilities.
6. How to assess FAIR readiness
This includes findability, accessibility, interoperability and reusability of a dataset or research output.
7. How to prepare data for OpenAIRE or EOSC-related services
This includes metadata quality, identifiers, links to publications and projects, resource descriptions and catalogue readiness.
8. When to use Data Café
Complex cases involving several data types, workflows, metadata profiles, licences or publication routes may be proposed for a Data Café session.
Submit a request
To request research data management consulting, please use the consultation request form.
Submit a consultation request
