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Open Science Network (OSN): Building Open & Federated Social Networks for Open Science

Summary #

Open Science Network (OSN) will develop a breakthrough federated social infrastructure connecting researchers directly with FAIR data objects across open science infrastructures—including archives, publishers, data warehouses, software repositories, and research information providers. OSN enhances traditional repository experiences by embedding social interaction within scientific workflows, creating a virtuous cycle where discussions become properly attributed, machine-readable FAIR objects with persistent identifiers.

Unlike isolated commercial platforms, OSN leverages Bonfire' extensible federated architecture to ensure researchers and their organizations maintain complete digital sovereignty while creating comprehensive provenance chains between discussions and referenced data. By transforming informal knowledge exchange that typically disappears in email threads or closed platforms into an identified and searchable part of the scientific record, OSN addresses critical gaps in the current research ecosystem.

Project Consortium #

Key Challenges #

Current scientific infrastructure faces critical barriers measurably impeding research impact:

Proposed Solution #

Open Science Network implements a federated social layer through established W3C standard protocols (ActivityPub[^6] and OAI-PMH[^7]). This server-to-server federation enables real-time interconnection between research actors, institutions, and outputs, all properly identified through ORCID, ROR, and DOI persistent identifiers. Authenticated interactions become citable and searchable FAIR objects with complete attribution chains and machine-readable licensing. Through ORCID/OpenAlex API integration, the platform connects researchers' social interactions with their professional profiles, creating an open alternative to platforms like ResearchGate and Academia.edu without compromising data ownership or research integrity.

Our system strategically focuses on developing:

Scientific Impact #

Open Science Network will transform research practices through a rigorous co-design process with our diverse pilot partners—representing key stakeholders across the scientific production, distribution, preservation, and consumption ecosystem. This consortium-driven approach ensures OSN addresses real-world needs while integrating all angles of the scientific workflow.

Our consortium's strength lies in bringing together complementary expertise from consolidated scientific communities, data repositories, universities, and open journals, creating a comprehensive solution that will deliver four measurable impacts:

Scientific and Innovation Objectives #

Open Science Network (OSN) will establish a federated, FAIR, open-source infrastructure for scientific collaboration that transforms social interactions into formal research outputs. Through three strategic pilot deployments, we will validate this approach across diverse institutional contexts.

Our five measurable scientific objectives are:

1. Create an Interoperable Federation Layer

We will connect scientific open research infrastructures through standardized APIs and protocols, enabling researchers to interact with FAIR objects across institutional boundaries while maintaining digital sovereignty. Our implementation will include repository-specific connectors for:

2. Transform Scientific Discourse into FAIR Data Objects #

We will develop concrete methods to encode discussions as machine-readable, citable research outputs. Our FAIR Discussion Engine will:

3. Extend ActivityPub Federation Protocols for Scientific Collaboration #

We will implement or write new Federation Extension Proposals (FEPs) to handle:

4. Build and Pilot a Community-Governed Alternative to Commercial Platforms #

We will establish clear governance mechanisms including:

Our project will be validated through several strategic pilots:

  1. Michigan State University: Leveraging their vibrant Knowledge Commons**[^14]** community (50,000+ researchers) and integrating with "KC Works" repository (powered by InvenioRDM)
  2. Physikalisch-Technische Bundesanstalt[^15]: Germany's national metrology institute will pilot specialized scientific discussions around measurement standards and calibration datasets, demonstrating our platform's adaptability to rigorous data quality requirements and metrology research workflows
  3. UNIF^16: The Paris Region Digital University (Université Numérique Île-de-France) will provide technical infrastructure and hosting expertise for our federation model, leveraging their experience with open and FAIR infrastructure systems. Their participation will facilitate integration with French academic networks and ensure compliance with European digital infrastructure standards.
  4. Université de Lorraine[^17]: University is one of the largest universities in France, scoping most of the research disciplines. With Université de Strasbourg, it hosts a French labelled technical infrastructure. It will provide technical hosting for Bonfire instances. It will also provide its expertise in open science, the relevant infrastructures, the link with the research communities.
  5. eLife/Sciety^18: This collaboration will implement DocMaps protocol integration, demonstrating how peer review processes and evaluations can be captured as structured, machine-readable data across the federation, enhancing transparency in scientific assessment while preserving institutional review policies
  6. Software Heritage[^19]: Connecting papers, data, and software for reproducible science, supporting their mission as a global archive of software source code

These partners represent diverse governance models (public university, national research institution, global archive) to validate adaptability across contexts.

Benefits to the Scientific Community, European Society, and the European Research Area #

Open Science Network will deliver four concrete benefits:

For individual researchers:

OSN addresses platform lock-in by making scholarly social capital—profiles, discussions, and relationships—portable, persistent, and formally recognized through ORCID and DOIs attribution.

For institutions:

For the European Research Area:

Our open-source, federated, portable, interoperable, and community-governed design ensures resilience against commercial capture, safeguarding long-term sustainability, trust, and academic freedom.

For the general public:

Whereas platforms like Bluesky may be 'federatable in theory,' OSN is federated in practice from day one, with multi-institutional pilots, open protocols, and no single controlling authority. OSN provides both the technical and social means needed to overcome the fragmentation and inertia that have undermined previous platform migrations by academics. While other platforms come with lock-in or high switching costs, OSN’s federation and open standards ensure that researchers, institutions, and communities can move, fork, or self-host their networks and data at any time—eliminating lock-in and returning control to the academic sector.

Addressing Questions of High Societal Relevance #

1. Establishing Community-Governed Scientific Networks #

Recent studies show approximately 75% of researchers use commercial and closed academic platforms despite growing concerns about data ownership and privacy[^20].

The Open Science Network demonstrates a viable federation model where governance is distributed across institutions while maintaining interoperability. Our pilot partners represent diverse governance models (public university, national research institution, global archive, open access publisher) to validate adaptability across contexts.

2. Enhancing Reproducibility Across Disciplines #

The European Commission has recognized research waste as a critical challenge, establishing Open Research Europe specifically to "implement Open Science practices and to support research integrity, transparency and reproducibility as well as to prevent 'research waste'" (Open-access.network, 2021). By connecting discussions directly to data objects, code, and methods, Open Science Network creates environments where reproducibility challenges can be documented and addressed collaboratively. Our Software Heritage integration specifically enables linking discussions to preserved code versions, enhancing computational reproducibility.

3. Accelerating Interdisciplinary Collaboration on Complex Challenges #

Climate change, pandemic response, and sustainable development require cross-disciplinary approaches that current siloed repositories hinder. Our cross-repository discovery mechanisms will enable researchers to find relevant data through human social connections rather than keyword searches alone.

By addressing these questions, Open Science Network provides the technical foundation for researcher-governed scientific discourse that connects directly to research outputs, enabling a more integrated, transparent, and collaborative scientific process. This aligns with the 2020 Leiden Manifesto's emphasis on community governance of research evaluation and the European Open Science Cloud's mission to make research more discoverable, accessible, interoperable, and reusable.

Scientific impacts #

Open Science Network (OSN) will fundamentally transform scientific collaboration by creating the missing bridge between data repositories and scientific discourse—addressing critical gaps in the current research ecosystem while generating substantial new scientific knowledge through interconnected innovations that go beyond the state of the art.

Extending Scientific Knowledge Beyond Current Boundaries #

Currently, platforms like ResearchGate facilitate social interaction around publications but create closed ecosystems where valuable discussions remain inaccessible and non-FAIR. Conversely, data repositories store FAIR objects but lack the social engagement capabilities that drive scientific discovery. OSN resolves this contradiction by pioneering a federated social layer that preserves the context in which scientific insights emerge.

By implementing W3C Web Annotation standards and RDA's Data Citation guidelines, OSN will transform ephemeral scientific discussions into properly attributed, machine-readable FAIR data objects with permanent identifiers. This advancement preserves valuable scientific context that is currently lost in private communications, creating a new category of scientific objects that capture the genesis of ideas and critiques.

OSN pioneers federated group structures that enable multidisciplinary, cross-institutional research teams to collaborate seamlessly across traditional boundaries. Unlike existing tools that require centralized platforms or formal institutional agreements, our federation protocols allow spontaneous formation of research communities around emerging scientific questions, preserving both institutional autonomy and individual attribution while generating new FAIR data objects.

Engaging Multiple Scientific Communities #

OSN is uniquely positioned to engage diverse scientific ecosystems through our targeted pilot implementations:

  1. Knowledge Commons at Michigan State University (humanities/social sciences) with its community of 50,000+ active users
  2. Physikalisch-Technische Bundesanstalt (Germany's national metrology institute)
  3. UNIF (French University Digital Infrastructure)
  4. Université de Lorraine (Large multidisciplinary French university)
  5. eLife/Sciety (implementing DocMaps protocol integration)
  6. Software Heritage (global code archive) containing 12+ billion source files

This multi-domain approach ensures OSN addresses varying needs across research disciplines, facilitating collaboration across traditionally siloed fields. By connecting repositories from different domains through a unified social layer, we enable researchers to discover and engage with data outside their immediate field—a capability critical for addressing complex societal challenges requiring interdisciplinary approaches.

The federated architecture of OSN respects the diversity of scientific practice by allowing communities to maintain autonomy while participating in the broader network. Unlike centralized platforms that impose uniform policies, OSN enables communities to establish their own moderation policies and collaboration norms while ensuring interoperability—a critical consideration for cross-disciplinary engagement.

OSN also specifically addresses the "long tail of science" by providing open-source software that can be deployed with minimal requirements (single virtual machine). This democratizes access to sophisticated collaboration tools, enabling smaller research groups, individual researchers, and resource-constrained institutions to participate in the scientific ecosystem on equal footing with larger entities.

Our tiered authentication systems accommodate citizen scientists while maintaining verification standards, and our contribution taxonomies properly attribute diverse forms of participation. This inclusive approach broadens the scientific community and leverages diverse perspectives that enrich scientific discourse.

Supporting Research Infrastructures Beyond Science Clusters #

Measurable Scientific Impacts #

OSN will deliver five significant scientific impacts that will be systematically measured throughout the project:

  1. Enhanced Data Discovery and Reuse: We will establish baseline discovery rates through pre-project surveys and target substantial increases in dataset accesses and citations for connected repositories. This will be measured through access logs, DOI resolution statistics, and citation tracking via DataCite, with measurements at key project milestones.
  2. Accelerated Cross-Disciplinary Collaboration: Based on initial bibliometric analysis, we aim to significantly increase cross-disciplinary dataset utilization, measured through network analysis of researcher interactions and citation patterns across disciplinary boundaries. We will track this progress regularly throughout the project lifecycle.
  3. Democratized Access to Scientific Discourse: Building from current geographic and institutional diversity in repository usage, we target broad international participation with particular focus on Global South inclusion. We will conduct regular diversity tracking from launch with quarterly progress reports.
  4. Improved Scientific Transparency and Reproducibility: The connection between discussions and data objects will enhance scientific transparency by making the context around datasets explicitly visible. We will measure this by tracking how often dataset reuse incorporates references to Open Science Network discussions, with a focus on improved reproducibility confirmation rates for datasets with active discussions.
  5. New Research Question Generation: We will document the emergence of novel research questions spanning multiple disciplines by analyzing discussion threads and coding for question novelty and cross-disciplinarity, with validation from an independent expert panel. This qualitative and quantitative assessment will demonstrate how connected conversations around scientific objects spark new research directions.

These impact measurements will be incorporated into our regular reporting and final deliverables, providing concrete evidence of how OSN transforms scientific collaboration and knowledge creation.

Alignment with European Science Policy Objectives #

OSN directly supports multiple European science policy priorities:

Digital Sovereignty: By providing a community-governed alternative to commercial platforms, OSN advances European digital sovereignty in scientific infrastructure, aligning with the European Strategy for Data's emphasis on developing alternatives to dominant platforms.

Open Science Implementation: OSN contributes directly to EOSC by providing social infrastructure that enhances the utility of existing EOSC resources, supporting the goal of making open science the new normal by embedding FAIR principles in researchers' daily collaborative practices.

Responsible Research Assessment: By developing attribution mechanisms that recognize diverse contributions to scientific knowledge, OSN supports the transition toward more nuanced research assessment models beyond simple bibliometric measures.

Research Integrity Enhancement: The transparency afforded by connecting discussions directly to data objects enhances research integrity by making methodological considerations explicitly visible, fostering environments where critical engagement with methods and results is preserved.

Through this comprehensive approach to transforming scientific discourse, OSN creates lasting infrastructure for cross-disciplinary, cross-institutional collaboration that accelerates scientific discovery while ensuring equitable participation across the research ecosystem—directly supporting the European Open Science Cloud's mission to make research more discoverable, accessible, interoperable, and reusable.

Digital resources
Describe how the project pilots the use of data and services already on-boarded to the Science Clusters Open Science platforms and/or to the EOSC platform and/or bring new research digital objects and RI services to the EOSC Exchange. Illustrate, if applicable, the technological innovation potential of the proposed project and the capacity to strengthen the multi-domain/multi- competences cross-fertilization and/or training. Describe in detail the expected needs in terms of computing resources.(Max 6000 chars)

Open Science Network will integrate with established Science Clusters' repositories and contribute innovative FAIR digital objects to the EOSC ecosystem through a federated social layer that transforms scientific discourse into properly attributed data objects with complete provenance chains.

Integration with Research Repositories and EOSC Platforms #

Our project will pilot integration with several key repositories that are essential components of the Science Clusters' infrastructure:

Knowledge Commons Works Integration:

Dataverse Integration:

Zenodo Integration:

Sciety/eLife Integration:

Software Heritage Integration:

By connecting with these repositories, OSN creates seamless interoperability between diverse scientific resources, enabling researchers to engage with data across disciplinary boundaries while maintaining FAIR principles and proper attribution.

Contribution to EOSC Exchange #

Open Science Network will bring new digital objects to the EOSC Exchange platform through:

FAIR Discussion Objects: Our key innovation transforms scientific discussions into properly attributed, machine-readable FAIR data objects that will:

Scientific Federation Extensions: As outlined in our WP3 (Federation Protocol Implementation), we will develop and publish ActivityPub extensions for scientific contexts, creating reusable components that can be adopted by other EOSC services:

Technological Innovation Potential #

Open Science Network introduces several technological innovations that strengthen cross-domain scientific collaboration:

Cross-Repository Discussion Protocol: As part of our WP4 (FAIR Discussion Engine), we are developing a system that:

ORCID-Integrated Federation Authentication:

Metadata-Aware Social Graph: Unlike general-purpose social networks, our network architecture natively understands scientific metadata through:

Multi-Domain/Multi-Competence Cross-Fertilization #

Open Science Network strengthens cross-domain collaboration by:

Interdisciplinary Connection Points: Our federation architecture creates intersection points between different repositories and Science Clusters:

Multi-Competence Engagement: By integrating diverse repositories, we enable researchers with different expertise to collaborate around related data, as reflected in our WP6 (User Testing & Refinement):

This cross-fertilization directly supports the Science Clusters' mission of breaking down silos between research domains and enhancing interdisciplinary collaboration.

Project implementation and final deliverables #

Open Science Network will be implemented over a 18 months period using an agile methodology and co-design processes and validation with our pilots.
Our implementation strategy balances technical development with community engagement to ensure both technical excellence and meaningful adoption.

Preparation & Co-Design #

Repository connector development #

Federation implementation #

Fair discussion engine #

Cross-Repository Transformation System:

Pilot deployment #

User testing & Measurement #

Dissemination & Community building #

Sustainability Framework #

Deliverables & Open Science Commitment #

INTEGRATION DELIVERABLES:

1. Repository Connector Suite: Modular connectors for:

2. Federation Protocol Implementation: Extended ActivityPub protocols for scientific contexts

3. FAIR Discussion Engine: System for:

4. Integration Documentation Package: Comprehensive technical guides for all supported repository types

SCIENTIFIC IMPACT DELIVERABLES:

  1. Pilot Case Studies: Reports from all 5 pilot institutions measuring:
    1. Number of cross-repository discussions created
    2. Increase in dataset citations through social discovery
    3. Time reduction in finding relevant data
  2. Cross-Repository Knowledge Flow Analysis: Network analysis showing:
    1. Citation patterns between different domains (before/after)
    2. New interdisciplinary collaborations formed
    3. Dataset reuse metrics across repositories
  3. Scientific Paper: Published article containing:
    1. Federation protocol specifications
    2. API integration patterns
    3. Measured usage statistics and adoption rates

KNOWLEDGE PRESERVATION COMMITMENT:

Open Dissemination Strategy

Our project features a comprehensive open dissemination strategy:

  1. Open Source Development: All code will be developed openly on GitHub from day one, under the AGPLv3 license, enabling community involvement throughout development.
  2. Public Development Blog: We will maintain a public development blog documenting technical decisions, challenges, and solutions.
  3. Regular Demo Sessions: Monthly open demo sessions will be held to showcase progress and gather feedback from potential users.
  4. Integration Workshops: We will host quarterly integration workshops to help interested repositories implement Open Science Network connectors.
  5. Digital Object Publication: All discussion objects generated through the platform will be publicly accessible with proper metadata and licensing.
  6. FAIR Alignment Reports: Regular public reports documenting our FAIR alignment and federation logic.
  7. Community Standards Registration: Formal documentation of all extensions for scientific metadata exchange and registration with community resources like FAIRsharing and ActivityPub FEPs.

Through this structured implementation approach and comprehensive dissemination strategy, Open Science Network will deliver both technical innovation and community adoption, creating lasting infrastructure for open science collaboration.

[^2]: Unveiling Engagement Metrics: Social Media Platforms vs. Community Spaces

[^3]: Use of author identifier services (ORCID, ResearcherID) and academic social networks (Academia.edu, ResearchGate) by the researchers of the University of Caen Normandy (France): A case study, Christophe Boudry, Manuel Durand-Barthez, PLOS (2020), https://doi.org/10.1371/journal.pone.0238583

[^4]: Breaking down barriers to data sharing - Research Information quoting Donaldson, D.R., Koepke, J.W. A focus groups study on data sharing and research data management. Sci Data 9, 345 (2022). https://doi.org/10.1038/s41597-022-01428-w

[^5]: 6 Repositories to Share Research Data | Teamscope Blog

[^6]: ActivityPub protocol

[^7]: Open Archives Initiative Protocol for Metadata Harvesting

[^8]: InvenioRDM — inveniosoftware.org

[^9]: The Dataverse Project

[^12]: Archive ouverte HAL

[^13]: PROV-O: The PROV W3C Ontology

[^14]: Humanities Commons (also known as Knowledge Commons) and their repository KC Works, hosted by Michigan State University

[^15]: Physikalisch-Technische Bundesanstalt

[^17]: Université de Lorraine

[^19]: Software Heritage

[^20]: Meishar-Tal, H., & Pieterse, E. (2017). Why Do Academics Use Academic Social Networking Sites?. The International Review of Research in Open and Distributed Learning, 18(1). https://doi.org/10.19173/irrodl.v18i1.2643

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