Beyond the dataset: Four ideas that improve how we streamline digital science

In Greece and Sweden, emergency departments face a common challenge: patients arriving with ambiguous symptoms that could signal either minor issues or life-threatening conditions. Doctors at AHEPA Hospital in Thessaloniki and hospitals using the CLEOS system in Sweden have been collecting rich triage data, vital signs, symptoms, medical histories, but sharing and jointly analyzing these datasets has been nearly impossible. The data contain sensitive personal information that cannot simply be transferred across borders. By the time researchers manually anonymize and harmonize formats, months have passed."

This scenario is taken from the health pilot of the HE RAISE project to illustrate a friction point that slows scientific progress across all domains. Building on these real-world experiences, the new RAISE Suite project transforms how Europe handles research data. At the kick-off meeting in Thessaloniki, the 14-partner consortium revealed an approach where data management systems are no longer passive actors but active contributors in the process of discovery.

This article shares four most impactful takeaways of the project's innovations that could reshape how science handles data.

Takeaway 1: Data Management Plans as orchestrators

For most researchers, the Data Management Plan (DMP) is a familiar, often dreaded, requirement: a static document written at project launch, filed away, and rarely revisited until final reporting. This approach fails to match the dynamic nature of modern research.

RAISE Suite transforms this static paperwork into an active system component through machine-actionable DMPs (maDMPs): structured files that systems can read and execute. Instead of a PDF describing intended practices, the maDMP becomes a set of executable instructions. When a project starts, it automatically provisions storage with appropriate permissions, configures metadata collection, and establishes quality checks. As data flows in from sensors or experiments, the system validates it against the plan in real time.

Project Coordinator Evdokimos Konstantinidis describes this as making the DMP "the main orchestrator for research activities." The OpenAIRE ARGOS DMP service, already deployed across national, institutional, and thematic infrastructures, serves as the engine for this orchestration, coordinating storage systems, repositories, and analytical tools based on researchers' specifications.

For emergency department researchers, this means triage data could arrive pre-structured with privacy controls configured, compliance verification automated, and cross-border analysis workflows established from day one. All of this would be specified once in the maDMP rather than negotiated repeatedly for each collaboration.

RAISE Suite extends this foundation by integrating maDMPs with laboratory sensor networks, creating closed-loop systems where data management decisions happen at the speed of data generation.

Takeaway 2: Direct pipelines from sensors to policy

RAISE Suite aims to operate, in Konstantinidis's words, "between the sensor and the exploitation of data." This philosophy extends beyond managing data to creating a traceable chain from raw observations to policy-relevant outputs.

Translating research findings into policy recommendations typically requires multiple manual steps: data export, reformatting, analysis, report writing, and dissemination. Each step risks introducing errors or delays. At the kick-off meeting, EC Project Officer Ourania Skondra emphasised the need for results to reach policy officers and for outputs to be "meaningfully integrated into policy contexts."

The integration of ARGOS's orchestration capabilities with the RAISE Portal creates these pathways. Well-managed data flows directly into policy-relevant dashboards, maintaining full provenance from sensor reading to policy briefing. When an emergency department AI system identifies patterns that could improve triage protocols, validated findings could reach healthcare policymakers without months of manual reformatting, building trust through transparency. 

Takeaway 3: Blockchain for scientific integrity

In technical sessions, the consortium outlined plans to use blockchain technology to secure identity transactions and maintain audit trails across RAISE's distributed node network of research institutions and data centres spanning Europe.

As research workflows become more automated, accountability grows crucial. When systems make decisions based on machine-actionable plans and sensor data, tamper-evident records of every action provide a foundation for trust. The blockchain approach creates immutable logs of data transactions, analysis steps, and access events.

This addresses a key lesson from the predecessor RAISE project: when multiple institutions collaborate on sensitive data, trust requires more than agreements. It requires verifiable audit trails.

Takeaway 4: A new curriculum for cultural change

Technology alone will not transform research culture. Alongside technical innovations, RAISE Suite places strong emphasis on education, including inter-departmental programmes and MOOCs to teach both practical tool use and a fundamental reconceptualisation of data as an active research asset.

This builds on training materials developed in the predecessor RAISE project, particularly the RAISE Training Programme that is already available on OpenPlato. ecessor RAISE project, particularly the RAISE Training Programme available on OpenPlato. RAISE Suite will enhance these materials with practical lessons on workflow automation and machine-actionable planning, informed by real pilot experiences like the cross-border emergency department collaboration.

The goal is to reshape how researchers think about data from the start of their careers, treating FAIR practices, documentation, and reproducibility as integral to research rather than administrative burdens. By embedding these ideas in curricula, RAISE Suite aims to create lasting change that outlives its funding period....

OpenAIRE's Role: From standards to implementation

RAISE Suite operationalises years of groundwork in European research infrastructure. The maDMP standards at its core were developed through the Research Data Alliance and refined through the OSTrails project. OpenAIRE brings both standards expertise and deployment experience through ARGOS, already serving research communities across more than 15 countries.

The project also builds on its predecessor's, RAISE project, lessons. The health pilot revealed that data-sharing barriers often concern trust and workflow integration as much as technical interoperability, insights that shaped RAISE Suite's emphasis on automated orchestration and blockchain-based audit trails.

What comes next

RAISE Suite project points toward a unified rethinking of the research data lifecycle: automated data capture, workflow orchestration guided by maDMPs, policy translation formats, integrity checks, and targeted training come together as parts of a single, integrated vision. Building on the foundations of the project.

The question isn't whether this vision is technically possible since pilots like the RAISE emergency department collaboration demonstrated both the need and the feasibility. The question is whether the research community will embrace systems that act as partners in discovery rather than obstacles to navigate.

As RAISE Suite evolves, we will continue sharing how this vision materialises in practice and how European researchers can benefit from these advances through OpenAIRE and beyond.