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A Research Information Management System (RIMS) is a centralized platform that helps universities and research institutions collect, manage, and make use of their research data. It typically aggregates information from multiple sources — HR, finance, publication databases, and more — into a single authoritative system. Institutions use a RIMS to track research outputs, manage funding and awards, demonstrate impact, and meet reporting and compliance requirements. By unifying research data in one place, a RIMS saves time, improves data quality, and supports more informed, strategic decision-making across the institution.

Yes. Pure is built on a modular architecture, allowing institutions to begin with the capabilities they need most and expand over time. The Pure Core — covering research outputs, funding, researchers and organizational data — forms the foundation. From there, institutions can add the Reporting Module, Pure Portal, Award Management Module, Community Module and national assessment modules such as REF or SEP/KUOZ as their needs evolve. This approach reduces upfront investment, limits implementation complexity and allows institutions to build toward a comprehensive research information management capability at their own pace.

Pure implementation typically takes three months for smaller institutions with minimal integrations, and six to nine months for larger, more complex deployments. Rĭga Stradīņš University — the first institution in Latvia to adopt Pure — completed implementation in three months and achieved 95% researcher uptake in year one.

Pure implementation follows four phases: initiation (scoping data sources and aligning stakeholders), configuration (building the system and data integrations), launch (controlled rollout with training), and post-launch support. Elsevier offers a range of service options, from guided self-implementation through to a fully managed service with a dedicated Implementation Manager. Success depends on clear data ownership and strong stakeholder engagement from the outset.

Pure addresses data quality through automated de-duplication, source prioritization and workflow-driven validation. When data is ingested from multiple sources — publication databases, HR systems and manual input — Pure identifies and merges duplicate records using persistent identifiers such as DOI, ORCID and Scopus Author ID. Institutions configure trusted sources and quality thresholds to determine what is accepted automatically versus routed for human review. Role-based validation workflows then allow editors and administrators to review, approve and enrich records before they are published or included in reports — ensuring only accurate, verified data underpins institutional decision-making.

A RIMS integrates through data synchronization — automatically pulling data from systems where it is actively maintained, such as HR, finance and student records, keeping it continuously up to date. It can also connect to external publication databases like Scopus, Web of Science, and PubMed to automate capture of research outputs, as well as to researcher identifier systems such as ORCID. Systems like Elsevier's Pure use standards-based XML data ingestion and a REST API, enabling seamless connection with both institutional systems and a wide ecosystem of third-party platforms.