Research Data Management and Curation

Design end-to-end data curation workflows for repositories and research teams. Covers ingest, quality checks, metadata enrichment, format migration, and long-term stewardship processes.

Get expert guidance on choosing the right data repository and preparing datasets for deposit. Covers Zenodo, Figshare, Dryad, domain-specific archives, and funder mandates.

Audit research datasets and repositories against FAIR principles — Findable, Accessible, Interoperable, Reusable. Identify gaps and get a prioritized remediation roadmap.

Generate correctly formatted data citations and advise on data citation standards, PIDs, and best practices for citing datasets in publications and data availability statements.

Map and optimize the full research data lifecycle from collection to archiving. Identify risks, bottlenecks, and governance gaps across planning, active research, and preservation phases.

Generate funder-compliant Data Management Plans (DMPs) for research grants. Covers FAIR principles, storage, sharing, and long-term preservation strategies.

Draft institutional research data policies and open data mandates. Aligns governance frameworks with funder requirements, GDPR, and international open science standards.

Create comprehensive README files, data dictionaries, and codebooks for research datasets. Ensures datasets are self-explanatory, reproducible, and ready for public sharing.

Design and document custom metadata schemas for research datasets. Aligns with domain standards like Dublin Core, DataCite, DDI, and ISO 19115 for maximum interoperability.

Get expert guidance on anonymising sensitive research data for sharing and publication. Covers pseudonymisation, k-anonymity, differential privacy, and GDPR-compliant disclosure control.