The recentmaDMP API Hackathon, heldon 27 May in Vienna, marked a significant milestone in the journey towards making research data management (RDM) more efficient andmachine-actionable. This collaborative event brought together experts withaclearobjective:tostandardise the waythatData ManagementPlanning platformsinteract in an automated way with other RDM services.

Key takeaways from the event

• The "Common maDMP API - preliminary design" is officially closed following the hackathon, providing a stable foundation for implementation.

• A common CRUD (Create, Retrieve, Update, Delete) operation was firmly established for each entity within the API.

• Decisions were made regarding consistent HTTP status codes and error handling.

• It was agreed that each tool will handle its own authentication and authorisation mechanisms, offering flexibility, though OpenID Connect (OIDC) was recommended for future common ground.

• DMP versioning will not be supported in the API.

What was the main message?

In this context, the hackathon served as a catalyst for finalising critical design discussions on the topic, leading to a successful outcome: the establishment of a stable, common blueprint for a machine-actionable Data Management Plan (maDMP) API. This API will primarily enable the seamless creation, modification, updating, filtering, and even potential deletion of DMPs, forming the essential baseline for future interoperability of data.

Why is it important for OSTrails?

ForOSTrails, this hackathon is a crucial step towards its mission of delivering the Commons to Plan-Track-Assess research in European Open Science Cloud (EOSC). OSTrails aims to streamline FAIRness, interconnectivity, and machine-actionability across all phases of research. Data Management Plans are a core pillar of the OSTrails project, and a standardised maDMP API is vital for achieving its goal of co-developing and testing fit-for-purpose solutions for FAIRness and machine-actionability across diverse domains and national settings. Building on theOSTrails Reference Architecture, which provides the foundational blueprint for interoperable research tools and ensures alignment across all OSTrails pillars (FAIR, SKG, and DMP), the finalised API directly supports making Data Management Plans more robust and integrated within the broader research ecosystem.

Why is it important for Open Science in general?

This API is important for Open Science because it facilitates the machine-actionability of Data Management Plans, moving them beyond static documents to dynamic, integrable entities. This advancement is key to enhancing the FAIR principles (Findable, Accessible, Interoperable, Reusable) for research data. By standardising how DMPs interact across different tools and platforms, the API fosters greater interoperability within EOSC. This means better governance, tracking, and assessment of research data, ultimately contributing to a more efficient and transparent research landscape globally.

Impressions

The hackathon was characterised by lively discussions and a strong collaborative spirit, especially when tackling complex topics. One of the key outcomes was the successful conclusion of ongoing negotiations around the API design, culminating in the closure of the Common maDMP API - preliminary design document,now considered stable. This outcome reflected a focused and productive working environment, with participants working effectively together to reach consensus on critical technical matters.

Conclusions

The hackathon marks a major leap forward in making Data Management Plans truly machine-actionable and interoperable. The consensus reached and the finalised preliminary design provide a solid foundation for DMP providers to begin implementing the API. This collaborative effort is essential for building a robust infrastructure that supports researchers, institutions, and funders in creating a cohesive, machine-actionable Open Science ecosystem aligned with FAIR-by-design principles and the broader EOSC vision. The event also underscores the power of community-driven development in addressing complex technical challenges for the benefit of the wider research community.

On 12 March 2025, OSTrails hosted a series of high-impact hackathons in Athens, held just prior to itsGeneral Assembly. These full-day events convened developers and domain experts from across scientific clusters and research infrastructure communities to collaboratively advance Data Management Planning (DMP) Platforms, Scientific Knowledge Graphs (SKG), and FAIR Assessment Tools, that are vital for effective research data management and sharing.

The hackathon brought together experts and service providers from well-established research data management platforms, bothwithin the consortium and beyond, to build on the Plan-Track-Assess (PTA) Framework (theReferenceArchitecture andPathwayspresented in projectdeliverableD1.4 andD1.1), and test key components in practice.

DMP-IF Hackathon: Laying the Groundwork for a CommonmaDMP API 

The DMP Hackathongathereddevelopers and service providers, including  platform providers from the consortium and severalfrom outsideEurope. The event focused on advancing machine-actionable Data Management Plans (maDMPs) by fostering collaborationaround two keyobjectives: 1) Maintaining the Research Data AllianceDMPCommon Standard (RDA DMP CS), 2)Initiating work on a CommonmaDMPAPI specification. 

As outlined in theOSTrailsArchitecture,theDMP-IFaimsto meet funder and community needsbyextending theRDA DMP CS data model, whileenabling real-time communication between systems through the introduction of anewApplication Profile Interfaces (APIs).Thediscussionscentredaround improving date handling, identifier usage, and specification governance—resulting in concrete proposals to besubmitted to theRDA Working Group for inclusion in the standard.In parallel, participants reviewed existing APIs and user requirements, drafted a shared API designformaDMPs, and agreed to continue development through close collaboration within thenewly establishedRDA group.

Developers exchanging ideas at the DMP IF Hackathon

SKG-IF Hackathon: Advancing Interoperability for Scientific Knowledge Graphs 

The SKG-IF Hackathon brought together providers of SKG services and infrastructure onboarded in OSTrails to advance interoperability through hands-on experimentation with the SKG-IF OpenAPI specification and metadata model. The session focused on mapping institutional data to the SKG-IF model and exploring its capacity to accommodate diverse research outputs.

Building on the RDA SKG-IF core data model, OSTrails aims to enhance the framework with a flexible extension mechanism to support domain-specific entities—such as instruments and provenance information, while supporting seamless discovery and integration of graph data with the introduction of a new API. The hackathon focused on validating the SKG-IF model through real-world data mapping and collected detailed feedback via the GitHub issue tracker. Major discussion topics were:  1) Gaps in the SKG-IF data model, such as missing fields, insufficient documentation, and the need for greater extensibility; 2) Issues in the OpenAPI specification, including unclear documentation and undefined field requirements.

The model’s scope was also extended to support a broader range of research products by introducing new product types aligned with community needs: literature, research data, and research software. Hackathon contributions were fed directly into the roadmap of the RDA SKG-IF Working Group, supporting the finalisation of the specification. 

 Hands-on collaboration during the SKG-IF Hackathon

FAIR-IF Hackathon: Making FAIR Assessments More Interoperable 

Running in parallel, the FAIR-IF Hackathon brought together developers from various FAIR-related tools, including thoseonboarded in the project as well as several external platforms. The focus was on aligning assessment services and harmonising API formats to improve interoperability across FAIR tools.

In the first part of the hackathon, participants discussed howkey components of the FAIR-IF, such as benchmarks, could help ensure consistent outcomes with minimal or no manual curation. They also emphasised the need to harmonise APIs through standards such as OpenAPI and highlighted transparency and record provenance as essential for trust and reproducibility.

The second part of the hackathon was hands-on, building on the earlier discussions. It focused on API functionality and tool alignment, showing that the proposed common API structure provided a solid foundation for implementation, integration, and mapping across existing tools—advancing interoperability within the FAIR-IF ecosystem.

Insights from the FAIR-IF Hackathon

Looking Ahead 

These hackathons not only advanced technical developments but also reaffirmed OSTrails' commitment to open collaboration across diverse research domains and settings. By bringing together experts from across Europe and beyond, OSTrails is setting the stage for truly interoperable research infrastructures.

Learn more about the OSTrails Architecture and Interoperability Frameworks by exploring ourblog, reading thedocumentation, and watching theInteroperability Webinar Series

Stay tuned for upcoming events and learn more about future OSTrails hackathons by visiting our page:OSTrails Hackathons.

-Written by Tassos Stavropoulos (OpenAIRE)

FromJune11th to12th2025, theEuropean Synchrotron Radiation Facility (ESRF) in Grenoblehosted theOSTrails Hackathon: Building Assessment‑IF & SKG‑IF Solutions Together, a two-day collaborative event that brought togetherOSTrails’ tooldevelopers, domain experts, and open science advocates, as well as experts fromGraspOS project.The aim was to co-develop and refine the core components of theOSTrails Interoperability Reference Architecture, focusing on theAssessment Interoperability Framework (Assessment‑IF, previously FAIR‑IF) and theScientific Knowledge Graph InteroperabilityFramework (SKG‑IF).

Key takeaways

• A common REST API specification for FAIR assessment operations was refined
• Benchmarks were defined in terms of authorship, scope, and execution
• The distinction between Benchmarks and Algorithms was formalised
• Metadata needed for describing a Benchmark and Algorithm (basic) has been discussed
• A mock DMP Evaluation walk-through showed how even staged scenarios align with Assessment‑IF
• Developers contributed real-world dataset examples and tested the SKG‑IF API
• The SKG-IF extension process was refined, and documentation improvements were proposed
• Collaboration with GraspOS and Athena RC ensured alignment with community needs and RDA SKG‑IF WG

Sharpening the Assessment‑IF

For theAssessment‑IF, the hackathon centred on two of its essential elements: API and Benchmarks. 

API:the meeting described a first version of the Assessment-IF REST API, refining the operations for interchanging metadata and results that result fromFAIR assessment tools. 

Benchmarks: These represent community expectations for how digital objects should behave and serve as the foundation for assessing conformance and quality. Until now, Benchmarks were acknowledged as necessary, but their practical definition, authorship, and implementation had not been formalised. This event addressed that by:

• Defining how Benchmark are authored and tied to user or community expectations

• Clarifying how Benchmarks are executed and how user feedback is produced

• Distinguishing Benchmarks from the Scoring Algorithms that implement them

A key example was themock-up of theDMP Evaluation Service, showcasing how real-world scenarios for evaluating machine-actionable Data Management Plans (maDMPs) fully align with the structure and semantics of the Assessment‑IF and are compliant with theDMP Common Standard (DCS). Specifically, the example demonstrated how the evaluation can be applied across different stages of a DMP’s lifecycle, confirming the framework’s robustness and flexibility.

Advancing the SKG‑IF

The SKG‑IF provides a shared framework for exchanging structured metadata across a wide array of research entities, including publications, datasets, software, organisations, and more. Sessions focused on advancing theSKG-IF through standardisation of a common API and refinement of the model’s extension mechanism. These sessions involvedclose collaboration with theGraspOS project and colleagues from the Athena Research Center, reinforcing OSTrails' alignment with current implementations and theRDA SKG‑IF Working Group.With thefirst public release of the SKG‑IF API specification scheduled for late 2025, this hackathon served as a critical milestone in its development.

Key outcomes included:

• Real-world testing of the SKG‑IF API in pilot implementations.

• Contributions of community-driven dataset examples to the officialSKG‑IF GitHub repository.

• Review and refinement of the SKG‑IF extension process, leading to planned improvements in documentation and onboarding materials.

• Strengthened collaboration with GraspOS and Athena RC to ensure SKG‑IF remains aligned with evolving community and infrastructure needs

Importance for OSTrails 
The hackathon was a key checkpoint for validating and refining core elements of the OSTrails Interoperability Reference Architecture. ForAssessment‑IF, it confirmed that the architecture is generic and flexible enough to support multiple assessment across different domains. Clarifying the roles of Benchmarks and Algorithms also improved internal coherence and communication across teams.

On the SKG‑IF side, the event enabledearly pilot testing of the API specification and strengthened the approach for community-driven extensions. Collaboration with GraspOS and Athena RC helped ensure the work remains grounded in real-world needs and existing international efforts.

Why it matters for the broader Open Science community 
Across the research landscape, tools for FAIR assessment and metadata exchange often lack common structures, terms, or protocols. This fragmentation limits interoperability and reduces transparency.

The harmonisation work advanced during this hackathon, including shared terminology, standardised APIs, and modular design, lays the foundation for:

• Greater compatibility between assessment tools and their results

• Seamless metadata integration across infrastructures

• Stronger alignment between technical systems and researcher needs

Together, these efforts support a more open, interoperable, and scalable research ecosystem.

Impressions 
The in-person format created space for rapid iteration, immediate feedback, and deep technical exchange. From architecture discussions to hands-on testing, the setting proved highly productive.

“Sometimes a few hours of discussion are more important than a few days of coding.”

-Renaud Duyme, ESRF

Looking ahead 
The hackathons solidified core design decisions for both Assessment‑IF and SKG‑IF. For Assessment-IF, the API now provides a consistent way to discover and run assessments, and the benchmark framework has been formally defined, with pilot data to be added before implementation across use cases. For SKG-IF, the API has been tested in real-world scenarios, and its extension mechanism is progressing toward wider adoption.