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Data interoperability (RP 2026)

(A.) Policy and legislation  

(A.1)   Policy objectives

In its communication A European strategy for data (COM (2020) 66 final), the Commission describes the vision of a common European data space, a Single Market for data in which data could be used irrespective of its physical location of storage in the Union in compliance with applicable law. Various policy initiatives that have been undertaken since then, see section 3.0.1 Data Economy for an overview.

The EU data strategy communication specifically mentions the importance of data interoperability and data quality:  Data interoperability and quality, as well as their structure, authenticity and integrity are key for the exploitation of the data value, especially in the context of AI deployment. Data producers and users have identified significant interoperability issues which impede the combination of data from different sources within sectors, and even more so between sectors. The application of standard and shared compatible formats and protocols for gathering and processing data from different sources in a coherent and interoperable manner across sectors and vertical markets should be encouraged through the rolling plan for ICT standardisation and (as regards public services) a strengthened European Interoperability Framework.

The importance of data quality and data standards is further underlined in the Data Union Strategy (published in November 2025), which announces further standardisation initiatives see chapter 3.0.1 Data Economy.

Open data

The DIRECTIVE on open data and the re-use of public sector information ((EU) 2019/1024) mentions the need for the use of formal open standards:

Article 5 Available formats:

1. Without prejudice to Chapter V, public sector bodies and public undertakings shall make their documents available in any pre-existing format or language and, where possible and appropriate, by electronic means, in formats that are open, machine-readable, accessible, findable and re-usable, together with their metadata. Both the format and the metadata shall, where possible, comply with formal open standards. 

The COMMISSION IMPLEMENTING REGULATION laying down a list of specific high-value datasets and the arrangements for their publication and re-use ((EU) 2023/138) mentions interoperability in its opening statements:

(3) Harmonising the implementation of the re-use conditions of high-value datasets entails the technical specification for making the datasets available in a machine-readable format and via application programming interfaces (APIs). Making high-value datasets available under optimal conditions strengthens the open data policies in the Member States, building on the principles of findability, accessibility, interoperability and reusability (FAIR principles).

(9) In addition to Directive (EU) 2019/1024, other Union legal acts, including Directive 2007/2/EC of the European Parliament and of the Council and Directive 2005/44/EC of the European Parliament and of the Council may be of relevance for the re-use of public sector information falling within the scope of this Implementing Regulation, notably where those Union acts lay down common requirements for data quality and interoperability.

Common European data spaces

The need for interoperability is mentioned in several places in the Data Governance Act, in particular in the article on the European Data Innovation Board – an expert group introduced in the DGA: 

Article 30, Tasks of on the European Data Innovation Board

(f) to advise the Commission, in particular taking into account the input from standardisation organisations, on the prioritisation of cross-sector standards to be used and developed for data use and cross-sector data sharing between emerging common European data spaces, cross-sectoral comparison and exchange of best practices with regard to sectoral requirements for security and access procedures, taking into account sector-specific standardisation activities, in particular clarifying and distinguishing which standards and practices are cross-sectoral and which are sectoral;

(g) to assist the Commission, in particular taking into account the input from standardisation organisations, in addressing fragmentation of the internal market and the data economy in the internal market by enhancing cross-border, cross-sector interoperability of data as well as data sharing services between different sectors and domains, building on existing European, international or national standards, inter alia with the aim of encouraging the creation of common European data spaces;

(h) to propose guidelines for common European data spaces, namely purpose- or sector-specific or cross-sectoral interoperable frameworks of common standards and practices to share or jointly process data for, inter alia, the development of new products and services, scientific research or civil society initiatives, such common standards and practices taking into account existing standards, complying with the competition rules and ensuring non-discriminatory access to all participants, for the purpose of facilitating data sharing in the Union and reaping the potential of existing and future data spaces, addressing, inter alia:

(i) cross-sectoral standards to be used and developed for data use and cross-sector data sharing, cross-sectoral comparison and exchange of best practices with regard to sectoral requirements for security and access  
procedures, taking into account sector-specific standardisation activities, in particular clarifying and distinguishing which standards and practices are cross-sectoral and which are sectoral; 
(ii) requirements to counter barriers to market entry and to avoid lock-in effects, for the purpose of ensuring fair competition and interoperability; 
(iii) adequate protection for lawful data transfers to third countries, including safeguards against any transfers prohibited by Union law; 
(iv) adequate and non-discriminatory representation of relevant stakeholders in the governance of common European data spaces; 
(v) adherence to cybersecurity requirements in accordance with Union law;

Article 33 of the Data Act specifies the interoperability requirements for participants in data spaces:

1.   Participants in data spaces that offer data or data services to other participants shall comply with the following essential requirements to facilitate the interoperability of data, of data sharing mechanisms and services, as well as of common European data spaces which are purpose- or sector-specific or cross-sectoral interoperable frameworks for common standards and practices to share or jointly process data for, inter alia, the development of new products and services, scientific research or civil society initiatives:

(a) the dataset content, use restrictions, licences, data collection methodology, data quality and uncertainty shall be sufficiently described, where applicable, in a machine-readable format, to allow the recipient to find, access and use the data;

(b) the data structures, data formats, vocabularies, classification schemes, taxonomies and code lists, where available, shall be described in a publicly available and consistent manner;

(c) the technical means to access the data, such as application programming interfaces, and their terms of use and quality of service shall be sufficiently described to enable automatic access and transmission of data between parties, including continuously, in bulk download or in real-time in a machine-readable format where that is technically feasible and does not hamper the good functioning of the connected product;

(d) where applicable, the means to enable the interoperability of tools for automating the execution of data sharing agreements, such as smart contracts shall be provided.

(A.2) EC perspective and progress report

Data interoperability can be defined as the ability to exchange and use data across multiple systems or applications. The HLF Workstream 14 report on Data Interoperability by the High-Level Forum for European Standardisation provides a comprehensive set of recommendations, closely aligned the FAIR principles and the European Interoperability Framework (EIF). The report served as the basis for a standardisation request on a European Trusted Data Framework, which features as one of the top priorities in the Annual Union Work Programme 2024 and Annual Union Work Programme 2025. 

While the European Trusted Data Framework primarily addresses data sharing in the context of data spaces, the intention is to provide a general framework for data sharing scenarios in the European single market for data (see chapter 3.0.1 Data Economy).

The standardisation request on a European Trusted Data Framework comprises 5 main elements:

  • Trusted data transaction: Harmonised standard(s) addressing the core data sharing process in line with the FAIR principles. Will enable participants to demonstrate conformity with the essential requirements in Article 33 of the Data Act.
  • Data catalogue implementation framework: Technical specification(s) defining a framework for standardised catalogue metadata. Addresses the findability of data in data catalogues within and across data spaces.
  • Semantic assets implementation framework: Technical specification(s) defining a framework for semantic assets (vocabularies, classification schemes, taxonomies, code lists and ontologies) and detailed metadata. Supports the interpretation and analysis of shared data within and across data spaces.
  • Data governance standard for data space participants: European standard(s) for internal data governance of data space participants. Enables the quality assessment of data governance processes and systems of parties participating in data spaces.
  • Maturity model for Common European Spaces: Technical specification(s) defining a maturity model for Common European Data Spaces. Enables the self-assessment and benchmarking of data spaces and related data sharing initiatives based on a set of standard key performance indicators and a supporting reporting structure. Aims to establish Common European Data Spaces as a brand or quality label.

Another important element is the preservation of data, for which standards and guidelines already have been established:

  • eArchiving implementation framework: Technical specifications(s) defining a framework for packaging data and metadata to ensure interoperability of archival solutions and data repositories.

It is the intention to further expand the European Trusted Data Framework in support of the Data Union Strategy, addressing emerging needs in the areas of data quality, data capturing and data annotation and labelling (see also chapter 3.0.1 Data Economy).

CEN, CENELEC and ETSI have established dedicated committees to support the work on the European Trusted Data Framework: 

  • CEN and CENELEC: JTC 25 on Data management, Data spaces, Cloud and Edge
  • ETSI: TC DATA.

Other significant standardisation developments include the deliverables developed under the leadership of the Data Spaces Support Centre and the SEMIC solutions developed by the Interoperable Europe initiative.  

Trusted Data Transactions

The objective is to consolidate and align the approaches for trusted data sharing that have emerged in the European data spaces community, including standardised protocols and policy mechanisms and supporting trust frameworks.

The two CEN workshop agreements: CWA 18125 Trusted Data Transaction and CWA 18245 Trusted Data Transaction - Part 2: Trustworthiness requirements will be important inputs to the formal standardisation process.

Other relevant standards include vocabularies to express policies, usage terms and consent.

Note: Trusted Data Transactions are likely to also be relevant to the sharing of open data. Regarding data sharing agreements, the Open Data Directive encourages the use of standard licenses, see (Article 8(2)), which is further emphasised in the High Value Datasets Implementing Act, Article 4(3).

Data catalogue implementation framework

The objective is to further strengthen and formalise the developments related to standardised data catalogue metadata.

Several Interoperable Europe solutions exist that are based on the W3C Data Catalogue Vocabulary (DCAT) standard, The Application Profile for data portals in Europe (DCAT-AP) enables to describe public-sector data catalogues and datasets. The common application profile is substantially improving the interoperability among data catalogues and the data exchange between Member States. The DCAT standard and DCAT-AP profile are starting to be applied in projects related to common European data spaces.

Semantic assets implementation framework

The objective is to further strengthen and formalise the developments related to standardised semantic assets, such as ontologies, vocabularies, and taxonomies.

Several standards-based frameworks exist, including:

Core Vocabularies and the Asset Description Metadata Schema Application Profile/ADMS-AP (EC - SEMIC),

Asset Administration Shell (IEC),

ISO/IEC 19115 metadata standards,

Smart Applications REFerence/SAREF Ontology (ETSI).

Initiatives on common reference data, such as the EC countries and territories reference data for geospatial data for commodities and locations, are relevant as well.

Data governance standard for data space participants

The objective is to provide practical guidance on internal data governance to participants in data spaces, addressing both the data holder and data user perspectives.

Several existing standards address data governance and data management, elements of which may be relevant.

Guidelines and papers on data governance, developed by stakeholders in the data spaces community, are relevant as well.  

Maturity model for Common European Data Spaces

The objective is to formalise the principles regarding the governance and architecture of data spaces and related initiatives in the European single market for data.

Ongoing pre-standardisation work includes the DSSC Data Spaces Blueprint and the Data Spaces Maturity Model.

ISO/IEC SC 38 is developing a standard on Dataspace concepts and characteristics.

Data quality implementation framework

The objective is to support define guidelines and best practices in support of collaborative data quality programmes in the context of data spaces and specific use cases.

Existing data quality management standards can be of help in defining relevant concepts such as the data quality dimensions.

Since data quality management starts at the source, data capture standards may also play a role, for example in the context of data from connected products and sensors.

Existing industry programmes regarding data quality can provide useful examples.

eArchiving implementation framework

Data lifecycle management, including data collection, record keeping, archival and - when necessary - long term preservation of information, supports society’s demand for trustworthy records and legal certainty associated with Data Strategy key instruments and application of AI algorithms. Important information should be kept accessible and reusable for years to come, regardless of the system used to store it. eArchiving (in the Digital Europe Programme eArchiving) provides core specifications, software, training and knowledge to help people preserve and reuse information over the long-term.

Regarding public sector data, the European Interoperability Framework (EIF) recommends that a long-term preservation policy is formulated for records and information in electronic form held by public administrations for the purpose of documenting procedures and decisions, to keep their legibility, reliability and integrity for as long as need be accessed. 

(A.3) References 

(B.) Requested actions 

Action 1: SDOs to optimize the management of DCAT and DCAT-AP (data discovery) in line with the standardisation request on a European Trusted Data Framework.

  • Related legal requirements: Open Data Directive, implementing act on High Value Data Sets, Data Act
  • Help to establish a governance framework for DCAT profiles
  • Develop rules for the management of new requirements, including criteria to decide whether to implement these in the base DCAT-AP standard or as extensions
  • Consider the development of interface standards for DCAT-AP publication and querying
  • Evaluate the suitability of DCAT for sharing of closed data, for example in a data spaces context

Action 2: SDOs to define a framework for the sharing of data from smart devices (data sharing, data usage, data retention, security of data in transit and data at rest)

  • Related legal requirements: Data Governance Act, Data Act, GDPR, eIDAS

Action 3: SDOs to consider existing standards and open source developments in the definition of a framework for the sharing of consent-based data (data altruism by organisations or persons), including metadata standards to define the consent attributes (e.g. purpose) and mechanisms to manage withdrawal of consent (data sharing, data governance).

  • Related legal requirements: Data Governance Act, GDPR
  • Support the fair access to and use of data and as well trusted, legally compliant data sharing across parties, including data intermediaries and altruism organisations.
  • Provide interoperability based on widely accepted European and international standards (included open source), in order to support cross-border data flows, between EU and other markets outside Europe.

Action 4: SDOs to optimize the management of domain ontologies:

Related legal requirements: Open Data Directive, implementing act on High Value Data Sets, Data Act

Help to establish a common governance framework for ontologies

Address long-term sustainability aspects such as maintenance funding 

Develop standard criteria to evaluate quality of ontologies, e.g. avoiding bias, ensuring completeness, use of persistent URLs

Develop standard methods for the automated testing of ontologies

Action 5: SDOs to identify standards for data integration, semantic mapping / tagging, data fabric. Also addressing the way this can help to leverage common domain ontologies (data usage)

Action 6: SDOs to identify standardisation needs and gaps in existing standards and, where needed, define or update standards for data governance, addressing the following levels:

Data governance standards to support individual parties, for example certification of internal data governance processes and tools.

Data governance standards to support collaborative data sharing, in particular open data portals and data spaces.

Data governance standards to support collaboration with existing communities for the creation and evolution of each specification / standard. 

Action 7: Support standardisation needs of the European open data infrastructure, especially the European Data Portal and the SEMIC.

(C.) Activities and additional information 

(C.1) Related standardisation activities 

CEN & CENELEC

CEN/CLC JTC 25 ‘Data management, Dataspaces, Cloud and Edge’ was established in September 2024 to address standardisation in data management and interoperability, including:

  • Data governance, data quality and data lifecycle management
  • Interoperability, portability and switch ability
  • Data model specifications and frameworks

The committee addresses data interoperability through its Working Groups, particularly:

  • WG 2: Dataspaces, focusing on dataspace interoperability standards
  • WG 3: Data Management and Governance, addressing data quality and metadata standards

The JTC aims to develop standards that support the European data strategy implementation and, in particular, the Data Act standardisation activities, such as the harmonized standard on interoperability. The committee’s work directly supports the objectives outlined in Article 33 of the Data Act regarding interoperability requirements for data space participants and works in close connection with the CEN Workshop ‘Trusted Data Transactions’, that developed and published the CEN/CWA 18125 series.

Details about JTC 25 and its Work Programme are available at:
https://standards.cencenelec.eu/dyn/www/f?p=205:22:0::::FSP_ORG_ID,FSP_LANG_ID:3485479,25&cs=1E76BC90CC192CD8A7BF6B69906CB7BA0

CEN/TC 468 ‘Preservation of digital information’ works on the functional and technical aspects of the preservation of digital information. In this field, the committee will develop a structured set of standards, specifications and reports, addressing business requirements, including compliance with the European legislative and regulatory framework (e.g. GDPR, eIDAS). This committee is developing a TR ‘Mapping of existing standardisation deliverables on European digital archiving and preservation’ and is working on a revision of the CEN/TS 18170 ‘Policy and functional requirements for the electronic archiving services’. The TC has established WG 1 ‘General concepts for preservation of digital information’.

ETSI

ETSI TC DATA is working in partnership with CEN/CENELEC JTC19 on eWallet and JTC25 on the European Trusted Data Framework.

The following work items and published deliverables are relevant to the Digital interoperability:

Two ENs are being developed in response to the Standardisation Request on the European Trusted Data Framework, in co-operation with CEN/CENELEC JTC25:

  • EN 303 760: Guidelines Semantic Interoperability
  • EN 304 199: Guidelines for Data Catalogue Framework.

ETSI TC SmartM2M was developing a set of reference ontologies, mapped onto the oneM2M Base Ontology. This work has commenced with the SAREF ontology, for Smart Appliances, but was extended to add semantic models for data associated with smart cities, industry and manufacturing, smart agriculture and the food chain, water, automotive, eHealth/aging well and wearables (https://saref.etsi.org/). ETSI TC SmartM2M has been transferred to ETSI TC DATA where the work continues.

ETSI ISG CIM (cross-cutting Context Information Management) has developed the NGSI-LD API (GS CIM 009 v1.9.1) which builds upon the work done by OMA Specworks and the FIWARE Foundation. NGSI-LD is an open framework for the exchange of contextual information for smart services, aligned with best practices in linked open data. The NGSI-LD API is based on the NGSI-LD Information Model (GS CIM 006 v1.3.1). It is now capable of attesting the provenance of information as well as supporting fine-grained encryption (GS CIM 019). Ongoing activities involve increased interoperability with oneM2M data sources. Applications and use cases are extended to Digital Twins, eHealth, analytics for government services, federated data spaces, and GDPR-compatible data sharing. Furthermore, GR CIM 048 reports about handling DCAT data catalogues and data services with NGSI-LD. ETSI ISG CIM is in the process of being closed and the responsibility for the work is transferred to TC DATA.

ETSI’s ISG MEC continues to expand upon developing its set of standardised Application Programming Interfaces (APIs) for Multi-Access Edge Computing (MEC). MEC technology offers IT service and Cloud computing capabilities at the edge of the network. Shifting processing power away from remote data centres and closer to the end user enables an environment that is characterized by proximity and ultra-low latency and provides exposure to real-time network and context information.

ETSI’s TC ATTM committee has specified a set of KPIs for energy management for data centres (ETSI ES 205 200-2-1). These have been combined into a single global KPI for data centres, called DCEM, by ETSI’s ISG on Operational energy Efficiency for Users (OEU), in ETSI GS OEU 001. TC ATTM took into account ETSI Position Paper GR OEU 036 on «Data interoperability format with applications for connected buildings» from ETSI ISG OEU. On this basis, TC ATTM started to work on Building Information Modelling (BIM) standardisation to support smart sustainable efficient communities.

SC USER:  has produced a set of documents related to “User-Centric approach in the digital ecosystem”.
Note: this body of work also applies to several other sections of the ICT rolling plan, such as, IoT, eHealth, Cyber security, e-privacy, accessibility, but are documented only once. 

ETSI TR 103 438            User Group; User centric approach in Digital Ecosystem
ETSI EG 203 602            User Group; User Centric Approach: Guidance for users; Best practices to interact in the Digital Ecosystem
ETSI TR 103 603            User Group; User Centric Approach; Guidance for providers and standardisation makers
ETSI TR 103 604            User Group; User centric approach; Qualification of the interaction with the digital ecosystem
ETSI TR 103 437            Quality of ICT services; New QoS approach in a digital ecosystem

SC USER has initiated an action to finalise the project by defining and implementing a proof of Concept of a “Smart interface for digital ecosystem”, which is a user interface that meets the needs and expectations of the user at his request, and is an “Intelligent”, “highly contextualised” personalisation, agile and proactive interface with an integrated QoS. This project will be based on the Smart Identity concept.

GS1

GS1 has developed a semantic web vocabulary that applies Linked Data principles and enables interoperability at the data level across databases and platforms. The GS1 Web Vocabulary   and the  GS1 Digital Link standard  allow structured product-related data to be shared in machine-readable form (e.g. JSON-LD/RDF), supporting the FAIR data principles and aligning with EU strategies on metadata harmonisation.

Key standards and assets:

Together, these standards and tools support the technical and semantic linking of data from heterogeneous sources, enabling scalable and trusted data interoperability across European data spaces.

ISO

ISO/TC 46/SC 4 Technical interoperability

  • ISO 15836 Information and documentation — The Dublin Core metadata element set

ISO/IEC JTC1

ISO/IEC JTC 1/SC 38 Cloud computing and distributed platforms develops standards in the area of Cloud Computing and Distributed Platforms including:

  • Foundational concepts and technologies,
  • Operational issues, and
  • Interactions among Cloud Computing systems and with other distributed systems

The work programme of SC 38 can be found following the link: ISO/IEC JTC 1/SC 38 - Cloud computing and distributed platforms

In 2018 JTC 1/SC 42 Artificial Intelligence was formed, and contains a WG 2 which is responsible for the Big Data work program.

SC 42 has published the following published big data standards:

ISO/IEC 20546:2019 Information technology -- Big Data -- Overview and Vocabulary (https://www.iso.org/standard/68305.html?browse=tc)

ISO/IEC TR 20547-2:2018 Information technology -- Big data reference architecture -- Part 2: Use cases and derived requirements (https://www.iso.org/standard/71276.html?browse=tc)

ISO/IEC TR 20547-5:2018 Information technology -- Big data reference architecture -- Part 5: Standards roadmap (https://www.iso.org/standard/72826.html?browse=tc)

ISO/IEC 20547-1: Information technology -- Big Data reference architecture -- Part 1: Framework and application process

ISO/IEC 20547-3: Information technology -- Big Data reference architecture -- Part 3: Reference architecture

SC 42 is progressing the following current big data projects, which are expected to complete in the next year:

ISO/IEC 24688: Information technology -- Artificial Intelligence -- Process management framework for Big data analytics

See for further information: https://www.iso.org/committee/6794475.html 

Built on its foundation standard that is ISO/IEC 38500 (Information technology - Governance of IT for the Organization), JTC 1/SC 40 IT service management and IT governance has developed or is developing the following standards on Governance of Data:

38505-1: Information technology - Governance of IT - Part 1: Application of ISO/IEC 38500 to the governance of data

38505-2: Information technology - Governance of IT - Part2: Implications of ISO/IEC38505-1 for Data Management

38505-3: Information technology - Governance of Data - Part3: Guidelines for Data Classification

See for further information https://www.iso.org/committee/5013818.html

ISO/IEC JTC1 SC32 on “Data management and interchange” work on standards for data management within and among local and distributed information systems environments. SC 32 provides enabling technologies to promote harmonization of data management facilities across sector-specific areas. https://www.iso.org/committee/45342.html

ISO/IEC 5207 Information technology — Data usage — Terminology and use cases

ISO/IEC 5212 Information technology — Data usage — Guidance for data usage

ISO/IEC 9075 Series Information technology — Database languages SQL

ISO/IEC 11179 Series Information technology — Metadata registries (MDR)

ISO/IEC 15944 Series Information technology — Business operational view

ISO/IEC 19583 Series Information technology — Concepts and usage of metadata

ISO/IEC 19763 Series Information technology — Metamodel framework for interoperability (MFI)

ISO/IEC 39075 Information technology — Database languages — GQL

ISO/IEC JTC 1/SC 7 Software and systems engineering

ISO/IEC 25024:2015 Systems and software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Measurement of data quality

ISO/IEC CD 25040.2 Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – Quality evaluation framework

ISO/IEC TS 27560:2023 Privacy technologies — Consent record information structure

ITU

ITU-T

ITU-T SG11 developed Q.Suppl.76 which defines common approaches and interfaces for data exchange between the central equipment identity register and the equipment identity register. It can be used to combat counterfeit and the use of stolen ICT devices as well as for other purposes. Also, based on the increasing demand for data-based smart agriculture services, ITU-T SG11 developed three new standards defining data management interfaces:

  • 5028 “Data management interfaces for intelligent edge computing-based smart agriculture service”;
  • 5029 “Data management interfaces in digital twin smart aquaculture system with intelligent edge computing”;
  • 5030 “Data management interfaces for intelligent edge computing-based flowing-water smart aquaculture system”.

Currently, SG11 continues developing data management interfaces for educational robot systems, public decision-making frameworks, smart pest and disease management services.

ITU-T SG13 Recommendation ITU-T Y.3600 “Big data - Cloud computing based requirements and capabilities” covers use-cases of cloud computing based big data to collect, store, analyse, visualize and manage varieties of large volume datasets:
https://www.itu.int/rec/T-REC-Y.3600/en

SG13 has 9 ongoing work items on big data, in particular, it is working on  architecture and mechanism of knowledge construction (Y.bDDN-ArchMec-KC) etc.

Recently approved ITU-T Recommendations on big data include Y.3659 (04/2025) with requirements, architecture and mechanism of application awareness and Y.3660 (04/2025) with functional requirements and functional architecture of operation aspect for public network integrated non-public network service.

See a flipbook “Big Data - Concept and application for telecommunications”:
https://www.itu.int/en/publications/Documents/tsb/2019-Big-data/mobile/index.html.

The work programme of SG13 is available at:  http://itu.int/itu-t/workprog/wp_search.aspx?sg=13

More info:  https://www.itu.int/en/ITU-T/studygroups/2025-2028/13/Pages/default.aspx

ITU-T SG20 has approved Recommendation ITU-T Y.4505 “Minimal Interoperability Mechanisms for Smart and Sustainable Cities and Communities” and Recommendation ITU-T Y.4812 “Interoperability of IoT devices’ identity across metaverse platforms”.

Additionally, ITU-T SG20 is working on the following work items: draft Supplement ITU-T Y.Sup-datainterop-usecases “Use cases of data interoperability in Internet of things”, draft Recommendation ITU-T Y.AIoT-dfs-arc “Reference architecture of data fusion service in artificial intelligence of things”, draft Recommendation ITU-T Y.AIoT-dpsm “Requirements and framework of data processing for smart manufacturing with Artificial Intelligence of Things”, draft Recommendation ITU-T Y.DSE-LISF “Reference architecture of data sharing and exchange based on lightweight intelligent software framework for Internet of things devices”, draft Recommendation ITU-T Y.Interop-DPM “Integrated Interoperability framework for Data Processing and Management”, draft Technical Report ITU-T YSTR.GenAI-Sem-Interop “Implications of Generative Artificial Intelligence on Semantic Interoperability for Data Use”, draft Recommendation ITU-T Y.Evaluation-dfp “Quality evaluation framework of data as a factor of production for smart sustainable cities” and draft Recommendation ITU-T Y.MIMbased-arch “MIM-based Architectural framework for interoperability in support of data sharing ecosystems”.

The work programme of SG20 is available at:  https://www.itu.int/ITU-T/workprog/wp_search.aspx?sg=20

More info: https://itu.int/go/tsg20

The ITU-T Focus Group on Data Processing and Management (FG-DPM) to support IoT and Smart Cities & Communities was set up in 2017. The Focus Group played a role in providing a platform to share views, develop a series of deliverables, and showcase initiatives, projects, and standards activities linked to data processing and management and establishment of IoT ecosystem solutions for data focused cities. This Focus Group concluded its work in July 2019 with the development of 10 Technical Specifications and 5 Technical reports. The complete list of deliverables is available here: https://itu.int/en/ITU-T/focusgroups/dpm

ITU-T SG17 (security) studies security requirements, architectures, guidelines and best practices for big data infrastructures. It has published 4 Recommendations in ITU-T X.1750-series on big data security. More details here: https://itu.int/go/tsg17

ITU-R

  • ITU-R SG 3 is developing studies on the use of machine learning methods for radiowave propagation studies.
  • ITU-R SG 6 developed studies on the use of artificial intelligence for broadcasting, including Report ITU-R BT.2447.

IEEE

The IEEE “Big Data Governance and Metadata Management: Standards Roadmap” has been developed to guide IEEE standards and pre-standardisation projects related to Big Data (mobile health, energy efficient processing, personal agency and privacy) and open data. 

Relevant standards activities include:

  • IEEE 1752 series of standards on mobile health data
  • IEEE 3652.1, Guide for Architectural Framework and Application of Federated Machine Learning
  • IEEE 7002, Standard for Data Privacy Process
  • IEEE 7005, Standard for Transparent Employer Data Governance
  • IEEE P3800, Data Trading System: Overview, Terminology, and Reference Model
  • IEEE P7004, Standard for Child and Student Data Governance
  • IEEE P7015 , Standard for Data and Artificial Intelligence (AI) Literacy, Skills, and Readiness.

There also are pre-standards programs, including:

  • IC16-001 Open Data
  • IC19-004 Technology and Data Harmonization for Enabling Clinical Decentralized Clinical Trials
  • IC21-007 Ethical Assurance of Data-Driven Technologies for Mental Healthcare
  • IC21-013 Synthetic Data

 For more information, see: https://ieee-sa.imeetcentral.com/eurollingplan/ .

IETF

The  A Semantic Definition Format for Data and Interactions of Things (asdf) Working Group  is tasked with developing  Semantic Definition Format (SDF)  into a standards-track specification for thing interaction and data modelling. In the process of developing this specification, further functional requirements that emerge in the usage of SDF for model harmonization will be addressed.

https://wiki.ietf.org/en/group/iab/Multi-Stake-Holder-Platform#h-313-data-interoperability

OASIS

The OASIS Open Data Protocol (Odata) TC works to simplify the querying and sharing of data across disparate applications and multiple stakeholders for re-use in the enterprise, Cloud, and mobile devices. A REST-based protocol, OData builds on HTTP and JSON using URIs to address and access data feed resources. OASIS OData standards have been approved as ISO/IEC 20802-1:2016 and ISO/IEC 20802-2:2016.

The NIEMOpen OASIS project is a framework for exchanging information between public and private sector organizations, with particular focus on issued and vocabularies for e-government and public administration issues. The framework, updated in 2023 as  NIEM Model v6, includes a reference data model for objects, properties, and relationships, allowing data elements to be shared, extended and harmonized across vertical topics and governmental functions, as well as a set of technical specifications for using and extending the data model in information exchanges. 

The Code List Representation (genericode) v1.0 final standard is a semantic model of code lists and accompanying XML serialization that can encode a broad range of lists of information elements such as country codes, abbreviations and lookup tables.  This serialization is designed to enable automatic interchange or distribution of machine-readable code list information between systems, and so more widely reuse existing categorizations.

The OASIS ebCore TC maintains the ebXML RegRep (‘registry and repository’) standard, also approved as ISO 15000-3:2023, that defines the service interfaces, protocols and information model for an integrated registry and repository. The repository stores digital content while the registry stores metadata that describes the content in the repository. RegRep was used in the EU TOOP project, which was concluded in 2021.

RegRep can be used in conjunction with ebXML Messaging including AS4 using a recently developed binding for the Registry Services of the OASIS ebXML RegRep Version 4.0 OASIS Standard. This binding is compatible with the AS4 profile of ebXML Messaging as used, for example, in the European Commission’s eDelivery Building Block, and complements the existing protocol bindings specified in OASIS RegRep Version 4.0. This AS4 binding is also of relevance to the Once-Only Technical System for the Single Digital Gateway (see section 3.2.4, eGovernment).

The OASIS  Data Provenance Standards (DPS) technical committee, launched in 2025, is developing cross-functional standards for data provenance, pedigree, lineage, and metadata tagging frameworks. These will facilitate tracing of data sources consumed by AI and similar dense data resources, as well as metadata for graph databases, NoSQL databases, and data exchanged via APIs or other non-database structures. The work is based on, among other things, the  open source donation of provenance specifications  from the  Data and Trust Alliance.

OGC

The Open Geospatial Consortium (OGC) defines and maintains standards for location-based, spatio-temporal data and services. The work includes, for instance, schema allowing description of spatio-temporal sensor, image, simulation, and statistics data (such as “datacubes”), a modular suite of standards for Web services allowing ingestion, extraction, fusion, and (with the web coverage processing service (WCPS) component standard) analytics of massive spatio-temporal data like satellite and climate archives. OGC develops community standards, often based from standards from CEN and ISO. OGC also contributes to the INSPIRE project.

http://www.opengeospatial.org

oneM2M

The oneM2M Partnership Project has specified the oneM2M Base Ontology (oneM2M TS-0012, ETSI TS 118 112) to enable syntactic and semantic interoperability for IoT data. The oneM2M standard defined a middleware layer, residing between a lower layer, comprising IoT devices and communications technologies, and an upper layer of IoT applications. Thus, it enables a wide range of interactions between applications and the underlying technologies needed to source data from connected devices and sensors as well as sharing of data from many sensors that are managed by different device owners and service providers. All oneM2M specifications are publicly accessible at Specifications (onem2m.org).

W3C

DCAT Version 3 now contains also provisions on Application Profiles (DCAT-AP) The application profiles themselves are hosted by the stakeholders creating them. There is currently no registry for Application Profiles: 

ODRL serves to express constraints with respect to data and metadata: 

RDF 1.2 works toward interoperability between Linked data and the world of Property Graphs. This also includes work on the SPARQL query language and an entire suite of further technical specifications:

Work on Spatial Data in cooperation with OGC continues, improving best practices and working towards increased interoperability

There are further Technical Specifications that can be found in :

(C.2) Other activities related to standardisation

ISA and ISA2 programme of the European Commission

The DCAT application profile (DCAT-AP) has been defined. DCAT-AP is a specification based on DCAT (a RDF vocabulary designed to facilitate interoperability between data catalogues published on the web) to enable interoperability between data portals, for example to allow metasearches in the European Data Portal that harvests data from national open data portals.

Extensions of the DCAT-AP to spatial (GeoDCAT-AP: https://semiceu.github.io/GeoDCAT-AP/drafts/latest/) and statistical information (StatDCAT-AP: https://joinup.ec.europa.eu/collection/semantic-interoperability-community-semic/solution/statdcat-application-profile-data-portals-europe ) have also been developed.

https://joinup.ec.europa.eu/asset/dcat_application_profile/description

DCAT-AP | Joinup (europa.eu)

        https://semiceu.github.io/DCAT-AP/releases/2.2.0-hvd/

Core Vocabularies can be used and extended in the following contexts:

  • Development of new systems: the Core Vocabularies can be used as a default starting point for designing the conceptual and logical data models in newly developed information systems.
  • Information exchange between systems: the Core Vocabularies can become the basis of a context-specific data model used to exchange data among existing information systems.
  • Data integration: the Core Vocabularies can be used to integrate data that comes from disparate data sources and create a data mesh-up.
  • Open data publishing: the Core Vocabularies can be used as the foundation of a common export format for data in base registries like cadastres, business registers and public service portals.

The Core Public Service Vocabulary Application Profile allows harmonised ways and common data models to represent life events, business events and public services across borders and across-sectors to facilitate access.

ADMS is a standardised vocabulary which aims at helping publishers of semantic assets to document what their assets are about (their name, their status, theme, version, etc) and where they can be found on the Web. ADMS descriptions can then be published on different websites while the asset itself remains on the website of its publisher.

More info can be found in the following links:

https://joinup.ec.europa.eu/collection/semantic-interoperability-community-semic/core-vocabularies

Core Vocabularies | Joinup (europa.eu)

https://ec.europa.eu/isa2/solutions/core-public-service-vocabulary-application-profile-cpsv-ap_en

https://joinup.ec.europa.eu/collection/semantic-interoperability-community-semic/adms 

Fair Principles and the GO Fair Initiatives 

FAIR Principles stands for F indability,  A ccessibility,  I nteroperability, and  
R euse of digital assets. The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) data as a result of the increase in volume, complexity, and creation speed of data. GO FAIR is a community that has been working towards implementations of the  FAIR Guiding Principles. 

IDSA standardisation activities

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