Collection, Generation And Validation Of Datasets Suitable For Training AI Models For 6g Networks And For Aiaas
HORIZON JU Innovation Actions
Basic Information
- Identifier
- HORIZON-JU-SNS-2026-STREAM-B-01
- Programme
- HORIZON-JU-SNS-2026
- Programme Period
- 2021 - 2027
- Status
- Forthcoming (31094501)
- Opening Date
- January 29, 2026
- Deadline
- April 29, 2026
- Deadline Model
- single-stage
- Budget
- €1,000,000
- Min Grant Amount
- €1,000,000
- Max Grant Amount
- €1,000,000
- Expected Number of Grants
- 1
- Keywords
- HORIZON-JU-SNS-2026-STREAM-B-01HORIZON-JU-SNS-2026Communication engineering and systems telecommunications
Description
The target outcomes include:
• A curated collection of high-quality real-world datasets, that have enough quality to train AI models that can run in operations, capturing realistic deployment scenarios—including user density, mobility patterns, network conditions, and realistic data traffic patterns from various applications, including vertical applications (non-exhaustive list). The collection could be obtained by any means or tools indicatively including but not limited to operational networks (real data) and/or network digital twins or advanced (high TRL) experimental platforms (emulators) or trials, gen AI (augmenting field measurements), and be significant in scale and broad representativeness (in terms of technologies, use-cases and verticals) designed to ensure scalability, providing a robust foundation for the training and validation of AI models for 6G networks and for AIaaS.
• An open-source simulator to create synthetic data sets (correlated between different network layers, and across different network points) of high quality capturing realistic deployment scenarios—including user density, mobility patterns, network conditions, anomalies and network attacks and realistic data traffic patterns from various applications, including vertical applications, etc.
• A modular framework and related methodology for generating and processing (e.g., cleaning, preprocessing) high quality realistic synthetic datasets to train AI models usable by 6G systems.
• A data space of appropriate scale to manage the datasets foreseen in the first expected outcome, covering the full data lifecycle for managing datasets, produced by SNS JU projects, for different reference use-cases at different scales. The data space should follow a framework that supports data/metadata sharing and governance within the SNS JU ecosystem, facilitating collaboration and interoperability, ensuring data sovereignty, privacy, security and compliance with EU regulations. Existing solutions for managing SNS produced data sets including repositories should be considered to avoid duplication with existing initiatives.
• A framework to audit any synthetic data sets that the project will create so as to ensure the validity/credibility of produced datasets.
• Activities that will encourage widespread use of the dataset (e.g., the integration with CAMARA / Network APIs / agents as a means to expose / enrich / monetise datasets, or the design of new control plane functions) and the overall framework by the SNS community, other EC initiatives and eventually by standardization bodies.
The produced datasets are targeted to be used by the SNS community to train AI models that will improve the performance of 6G networks or serve to develop AI solutions for 6G services and applications (AIaaS) for SNS JU verticals.
Objective:Please refer to the "Specific Challenges and Objectives" section for Stream B-01 in the Work Programme, available under ‘Topic Conditions and Documents - Additional Documents’.
Scope:The focus is on:
• Collecting, and making available in an operationally effective way, high-quality real-world datasets from advanced (e.g., 5G Advanced, 6G) operational networks (real data) or network digital twins and/or advanced (high TRL), gen AI tools, experimental platforms (emulators) or trials, capturing realistic deployment scenarios—including user density, mobility patterns, network conditions, and realistic data traffic patterns from various applications, including verticals. Proponents should not consider datasets that have limitations in terms of, for example, coverage, capacity, number of devices, or where data and metadata do not have enough quality to train AI models. The datasets should originate from actors that have significant experience from operational networks and network components as well as service providers (including verticals), so that there is strong level of confidence that the datasets are useful for training AI models to be used by 6G networks. For the real-world datasets from advanced (e.g., beyond 5G, 6G) operational networks and/or advanced (high TRL) experimental platforms or trials and datasets produced by SNS JU projects this project should ensure the provision the presence of Metadata definition (to have a common descriptor for the data), methods to verify that the data is valuable for the training of realistic AI models, and ensure data reusability.
• Development of full protocol stack, end-to-end implementations enabling high-fidelity, system-level simulations of 6G networks building upon and enhancing existing open-source simulators for producing correlated reference datasets at different network layers, and across different network points. These simulations will span from the physical layer to the application layer and will include:
- Support for multi-radio access technologies, including e.g., cellular, Wi-Fi, and non-terrestrial systems.
- Disaggregated RAN architectures, enabling flexible and scalable deployment models.
- Multi-band operation with accurate propagation and channel modelling across various frequency ranges (e.g., FR3, mmWave, cmWave, sub-THz), incorporating ray tracing-based channel models for enhanced realism.
- Realistic traffic patterns that reflect anticipated data flows in future network scenarios.
- Anomalies and network attacks that can be eventually used to test the resilience of AI solutions in 6G networks.
• Design of an open-source framework and toolset for generating high quality realistic synthetic data, tailored to diverse environmental scenarios (e.g., urban, suburban, rural, indoor, industrial), user densities, security threats, mobility patterns, and node behaviour - including memory, CPU, storage, and energy consumption - as well as traffic profiles from a variety of vertical applications. These datasets should be produced following existing calibration directives from standardization bodies (e.g., 3GPP) and expected traffic patterns from European and international organizations (e.g., 5GAA, 5G-ACIA, etc.). The datasets should be validated from proponents that have significant experience from operational networks and network components as well as service providers (including verticals), so that there is strong level of confidence that the datasets are useful for training AI models to be used by 6G networks and for AIaaS. Optionally the tool may consider the use of reliable LLM solutions to enable a user-friendly interface for users and/or to calibrate the simulator and/or create the desired datasets.
• Creation of large-scale, open-source high quality synthetic datasets, following well established reference use-cases, containing measurements, channel and network indicators, and performance metrics across multiple protocol layers (RF, physical, MAC, network, transport, and application). These datasets will cover a broad range of network scenarios, architectures, technologies, and system configurations related to smart networks and services.
• Validation, quality assessment of the existing SNS JU project datasets, verifying the data’s accuracy, consistency, and completeness ensuring their alignment with the specific use case and performance requirements of the 6G network.
• For the real-world datasets from advanced (e.g., 5G Advanced, 6G) operational networks and/or advanced (high TRL) experimental platforms or trials and datasets produced by SNS JU project, this project should ensure the provision the presence of: Metadata definition (to have a common descriptor for the data), methods to verify that the data is valuable for the training of realistic AI models and ensure data reusability.
• Engagement with standardization bodies and relevant open-source communities to promote the adoption of the framework, the associated simulation tools, and open datasets enabling industry-wide collaboration on shared software platforms and data resource.
• Creation of tutorials and implementation of dissemination activities to encourage widespread use of the framework, its synthetic datasets, and the underlying simulation tools including the development of APIs, new intelligence control plane function, etc.
This Topic expects proposals with strong industrial participation with demonstrated AI and operational expertise to ensure credibility, usability, and engagement with standardisation bodies. Academic institutions and RTOs will complement consortia where their expertise adds clear value.
Eligibility & Conditions
General conditions
1. Admissibility Conditions: Proposal page limit and layout
General Annex A of the General Annexes to the Horizon Europe Work Programme 2026-2027 20 shall apply mutatis mutandis to the SNS call 2026 covered by this Work Programme, with the following derogations to page limits:
The limit for a full proposal is 70 pages for RIAs and IAs submitted under Stream B and C.
2. Eligible Countries
General Annex B of the General Annexes to the Horizon Europe Work Programme 2026-2027 shall apply mutatis mutandis to the SNS call 2026, with the following exceptions or amendments:
Restrictions on participation in accordance with Article 22(5) of the Horizon Europe Regulation
In order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, it is important to avoid a situation of technological dependency on a non-EU source, in a global context that requires the EU to take action to build on its strengths, and to carefully assess and address any strategic weaknesses, vulnerabilities and high-risk dependencies which put at risk the attainment of its ambitions. For this reason, for proposals under topics identified as “subject to restrictions on participation in accordance with Article 22(5) of the Horizon Europe Regulation” (in the specific conditions for eligibility), participation is limited to legal entities established in Member States and Associated Countries.
For the duly justified and exceptional reasons listed in the paragraph above, in order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country listed above, but which are directly or indirectly controlled by a non-eligible country or by a non-eligible country entity, may not participate in the action unless it can be demonstrated, by means of guarantees positively assessed by their eligible country of establishment, in so far this is a Member State or Associated Country, that their participation to the action would not negatively impact the Union’s strategic, assets, interests, autonomy, or security. Entities assessed as high-risk suppliers of mobile network communication equipment within the meaning of ‘restrictions for the protection of European communication networks’ (or entities fully or partially owned or controlled by a high-risk supplier) cannot submit guarantees.
The guarantees shall in particular substantiate that, for the purpose of the action, measures are in place to ensure that:
a. control over the applicant legal entity is not exercised in a manner that retrains or restricts its ability to carry out the action and to deliver results, that imposes restrictions concerning its infrastructure, facilities, assets, resources, intellectual property or know-how needed for the purpose of the action, or that undermines its capabilities and standards necessary to carry out the action;
b. access by a non-eligible country or by a non-eligible country entity to sensitive information relating to the action is prevented; and the employees or other persons involved in the action have a national security clearance issued by an eligible country, where appropriate;
c. ownership of the intellectual property arising from, and the results of, the action remain within the recipient during and after completion of the action, are not subject to control or restrictions by non-eligible countries or non-eligible country entity, and are not exported outside the eligible countries, nor is access to them from outside the eligible countries granted, without the approval of the eligible country in which the legal entity is established.
The participants directly subject to this eligibility condition are not only beneficiaries, affiliated entities and associated partners but also subcontractors. Their participation is therefore subject to an ex-ante ownership control assessment by the EC and, if relevant, the EC acceptance of a guarantee approved by an eligible country.
Restrictions for the protection of European communication networks
These restrictions apply in accordance with General Annex B of the General Annexes of the Horizon Europe Work Programme 2026-2027:
Entities that are assessed as high-risk suppliers of mobile network communication equipment within the meaning of ‘restrictions for the protection of European communication networks’ ( (and any entities they own or control) are not eligible to participate as beneficiaries, affiliated entities and associated partners.
Legal entities established in Russia, Belarus, or in non-government-controlled territories of Ukraine
Given the illegal invasion of Ukraine by Russia and the involvement of Belarus, there is currently no appropriate context allowing the implementation of the actions foreseen in this programme with legal entities established in Russia, Belarus, or in non-government-controlled territories of Ukraine. Therefore, even where such entities are not subject to EU restrictive measures, such legal entities are not eligible to participate in any capacity. This includes participation as beneficiaries, affiliated entities, associated partners, third parties giving in-kind contributions, subcontractors or recipients of financial support to third parties (if any). Exceptions may be granted on a case-by-case basis for justified reasons. With specific regard to measures addressed to Russia, following the adoption of the Council Regulation (EU) 2024/1745 of 24 June 2024 (amending Council Regulation (EU) No 833/2014 of 31 July 2014), legal entities established outside Russia but whose proprietary rights are directly or indirectly owned for more than 50% by legal persons established in Russia are also not eligible to participate in any capacity.
3. Other Eligible Conditions
described in Annex B of the Work Programme General Annexes.
At least half of the budget should be implemented by the SNS JU member (other than the Union) and their constituent or affiliated entities.
Applicants will be invited to fill a mandatory table of compliance at proposal stage in the Application Form Technical Description (Part B).
Proposals that do not fulfil the above Table App 3 conditions, including the mandatory table of compliance, at the time of the proposal submission, will be considered ineligible and, therefore, will not be evaluated.
Gender equality plans and gender dimension of R&I:
According to the General Annexes, provision of a gender equality plan for public bodies, research organisations or higher education establishments (including private research organisations and higher education establishments) applies as per Part B of the General Annexes to the Horizon Europe Work Programme 2026-2027. Additional gender issues (related to award sub-criterion consideration of the gender dimension in research and innovation content) shall be addressed as appropriate in case research results are expected to differ when applied to different gender populations of users.
4. Financial and operational capacity and exclusion
General Annex C of the General Annexes to the Horizon Europe Work Programme 2026-2027 shall apply mutatis mutandis to the SNS call 2026 covered by this Work Programme.
5a. Evaluation and award: Award criteria, scoring and thresholds
are described in Annex D of the Work Programme General Annexes.
General Annex D of the General Annexes to the Horizon Europe Work Programme 2026-2027 shall apply mutatis mutandis to the SNS call 2026 covered by this Work Programme with the following complements:
For IAs under Stream B and RIAs under Stream C, the award criteria table is complemented as follows:
- Introduction in the impact section of a sub-criterion assessing the proposal contribution to the overall SME objective as appropriate;
- Introduction in the impact section of a sub-criterion assessing the proposal contribution to the IKOP objectives;
5b. Evaluation and award: Submission and evaluation processes
are described in Annex F of the Work Programme General Annexes and the Online Manual.
5c. Evaluation and award: Indicative timeline for evaluation and grant agreement
General Annex F of the General Annexes to the Horizon Europe Work Programme 2026-2027 shall apply mutatis mutandis to the SNS call 2026 covered by this Work Programme with the following amendments related to the procedure to rank proposals:
- When two IA proposals are equally ranked and that it has not been possible to separate them using first the coverage criterion, second the impact criterion, and third the excellence criterion (i.e., after step 2 of the procedure outlined in part F of the General Annex), the level of SME participation will be taken as the next criterion to sort out the ties and if still un-conclusive, the level of IKOP will be considered as appropriate. If still inconclusive, the procedure outlined in part F of the General Annex will be resumed from step 3 onwards.
6. Legal and financial set-up of the grants
General Annex G of the General Annexes to the Horizon Europe Work Programme 2026-2027 shall apply mutatis mutandis to the SNS call 2026 covered by this Work Programme. In addition:
Participants of selected projects will be requested to cooperate in the SNS JU Programme for topics of common interests by signing a written agreement (called “collaboration agreement”) referred in the specific provisions of the Model Grant Agreement (Annex 5 of the MGA).
Further to Open science provisions set out in the General Annex G of the General Annexes to the Horizon Europe Work Programme 2026-2027, in the SNS topics under Streams B and C, AI/ML training data sets, which will be created and used in the context of the selected projects, have to be made available through a common repository that will be openly accessed and may be used by other SNS projects over the programme lifecycle.
Specific conditions
described in the [specific topic of the Work Programme]
Call Documents:
A call-specific application form will be used in this topic — call-specific application form will be available in the Submission System
Application and evaluation forms and model grant agreement (MGA):
Application form templates — the application form specific to this call is available in the Submission System
Standard application form (HE RIA, IA)
Evaluation form templates — will be used with the necessary adaptations
Standard evaluation form (HE RIA, IA)
Guidance
Model Grant Agreements (MGA)
Framework Partnership Agreement FPA
Additional documents:
HE Main Work Programme 2026-2027 – 1. General Introduction
HE Main Work Programme 2026-2027 – 7. Digital, Industry and Space
HE Main Work Programme 2026-2027 – 15. General Annexes
HE Framework Programme 2021/695
HE Specific Programme Decision 2021/764
EU Financial Regulation 2024/2509
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment
EU Grants AGA — Annotated Model Grant Agreement
Funding & Tenders Portal Online Manual
Frequently Asked Questions About Collection, Generation And Validation Of Datasets Suitable For Training AI Models For 6g Networks And For Aiaas
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