normativas

The future new version of the Technical Standard for Interoperability of Public Sector Information Resources (NTI-RISP) incorporates DCAT-AP-ES as a reference model for the description of data sets and services. This is a key step towards greater interoperability, quality and alignment with European data standards.

This guide aims to help you migrate to this new model. It is aimed at technical managers and managers of public data catalogs who, without advanced experience in semantics or metadata models, need to update their RDF catalog to ensure its compliance with DCAT-AP-ES. In addition, the guidelines in the document are also applicable for migration from other RDF-based metadata models, such as local profiles, DCAT, DCAT-AP or sectoral adaptations, as the fundamental principles and verifications are common. 

Why migrate to DCAT-AP-ES?

Since 2013, the Technical Standard for the Interoperability of Public Sector Information Resources has been the regulatory framework in Spain for the management and openness of public data. In line with the European and Spanish objectives of promoting the data economy, the standard has been updated in order to promote the large-scale exchange of information in distributed and federated environments. 

This update, which at the time of publication of the guide is in the administrative process, incorporates a new metadata model aligned with the most recent European standards: DCAT-AP-ES. These standards facilitate the homogeneous description of the reusable data sets and information resources made available to the public. DCAT-AP-ES adopts the guidelines of the European metadata exchange scheme DCAT-AP (Data Catalog Vocabulary – Aplication Profile), thus promoting interoperability between national and European catalogues. 

The advantages of adopting DCAT-AP-ES can be summarised as follows:

• Semantic and technical interoperability: ensures that different catalogs can understand each other automatically.
• Regulatory alignment: it responds to the new requirements provided for in the NTI-RISP and aligns the catalogue with Directive (EU) 2019/1024 on open data and the re-use of public sector information and Implementing Regulation (EU) 2023/138 establishing a list of specific High Value Datasets or HVD), facilitating the publication of HVDs and associated data services.
• Improved ability to find resources: Makes it easier to find, locate, and reuse datasets using standardized, comprehensive metadata.
• Reduction of incidents in the federation: minimizes errors and conflicts by integrating catalogs from different Administrations, guaranteeing consistency and quality in interoperability processes. 

What has changed in DCAT-AP-ES?

DCAT-AP-ES expands and orders the previous model to make it more interoperable, more legally accurate and more useful for the maintenance and technical reuse of data catalogues. 

The main changes are: 

• In the catalog: It is now possible to link catalogs to each other, record who created them, add a supplementary statement of rights to the license, or describe each entry using records.
• In datasets: New properties are added to comply with regulations on high-value sets, support communication, document provenance and relationships between resources, manage versions, and describe spatial/temporal resolution or website. Likewise, the responsibility of the license is redefined, moving its declaration to the most appropriate level.
• For distributions: Expanded options to indicate planned availability, legislation, usage policy, integrity, packaged formats, direct download URL, own license, and lifecycle status. 

A practical and gradual approach

Many catalogs already meet the requirements set out in the 2013 version of NTI-RISP. In these cases, the migration to DCAT-AP-ES requires a reduced adjustment, although the guide also contemplates more complex scenarios, following a progressive and adaptable approach. 

The document distinguishes between the minimum compliance required and some extensions that improve quality and interoperability.

It is recommended to follow an iterative strategy: starting from the minimum core to ensure operational continuity and, subsequently, planning the phased incorporation of additional elements, such as data services, contact, applicable legislation, categorization of HVDs and contextual metadata. This approach reduces risks, distributes the effort of adaptation, and favors an orderly transition. 

Once the first adjustments have been made, the catalogue can be federated with both the National Catalogue, hosted in datos.gob.es, and the Official European Data Catalogue, progressively increasing the quality and interoperability of the metadata. 

The guide is a technical support material that facilitates a basic transition, in accordance with the minimum interoperability requirements. In addition, it complements other reference resources, such as the DCAT-AP-ES Application Profile Model and Implementation Technical Guide, the implementation examples (Migration from NIT-RISP to DCAT-AP-ES and Migration from NTI-RISP to DCAT-AP-ES HHD), and the  complementary conventions to the DCAT-AP-ES model that define additional rules to address practical needs.

Context and need for an update

Data is a key resource in the digital transformation of public administrations. Ensuring its access, interoperability and reuse is fundamental to improve transparency, foster innovation and enable the development of efficient public services centered on citizens.

In this context, the Technical Standard for Interoperability for the Reuse of information Resources (NTI-RISP) is the regulatory framework in Spain for the management and opening of public data since 2013. The standard sets common conditions on selection, identification, description, format, terms of use and provision of documents and information resources produced or held by the public sector, relating to numerous areas of interest such as social, economic, legal, tourism, business, education information, etc., fully complying with the provisions of Law 37/2007, of November 16.

In recent months, the text has been undergoing modernization in line with the European and Spanish objective of boosting the data economy, promoting its large-scale exchange within distributed and federated environments, guaranteeing adequate cybersecurity conditions and respecting European principles and values.

The new standard, currently in the processing stage, refers to a new metadata model aligned with the latest versions of European standards, which facilitate the description of datasets and reusable information resources made publicly available.

This new metadata model, called DCAT-AP-ES, adopts the guidelines of the European metadata exchange schema DCAT-AP (Data Catalog Vocabulary – Application Profile) with some additional restrictions and adjustments. DCAT-AP-ES is aligned with the European standards DCAT-AP 2.1.1 and the extension DCAT-AP-HVD 2.2.0, which incorporates the requirements for High-Value Datasets (HVD) defined by the European Commission.

What is DCAT-AP and how is it applied in Spain?

DCAT-AP is an application profile based on the DCAT vocabulary from the W3C, designed to improve the interoperability of public sector open data catalogues in Europe. Its goal is to provide a common metadata model that facilitates the exchange, aggregation and federation of catalogues from different countries and organizations (interoperability).

DCAT-AP-ES, as the Spanish application profile of DCAT-AP, is designed to adapt to the particulars of the national context, ensuring efficient management of open data at the national, regional and local levels.

DCAT-AP-ES is established as the standard to be considered in the new version of the NTI-RISP, which in turn is framed within the National Interoperability Framework (ENI), regulated by Royal Decree 4/2010, which sets the conditions for the reuse of public sector information in Spain.

Main news in DCAT-AP-ES

The new version of DCAT-AP-ES introduces significant improvements that facilitate interoperability and data management in the digital ecosystem. Among others:

Alignment with DCAT-AP

• Greater compatibility with European open data catalogues by aligning NTI-RISP with the EU standard DCAT-AP.
• Inclusion of advanced properties to improve the description of datasets and data services, to ensure the possibilities indicated below.

Incorporation of metadata for the description of High-Value Datasets (HVD)

• Facilitates compliance with European regulation on high-value data.
• Enables detailed description of data in key sectors such as geospatial, meteorology, earth observation and environment, statistics, mobility and business.

Improvements in the description of data services

• Inclusion of specific metadata to describe APIs and data access services.
• Possibility to express a dataset in different contexts (e.g. geospatial, with a map server, or statistical, with a data API).

Support for provenance and data quality

• Incorporation of new properties to manage lifecycle, versioning and origin.
• Implementation of validation and quality control mechanisms using SHACL, ensuring consistency and structure of metadata in catalogues.

Use of controlled vocabularies and best practices

• Adaptation of standardized vocabularies for licenses, data formats, languages and themes.
• Greater clarity in data classification to facilitate discovery.

Data governance and improved agent management

• Specification of agent roles (creator, publisher) and contact points.
• Enhanced metadata to represent resource provenance.

Validation of conformity and metadata quality

• Guides to help validate metadata that comply with DCAT-AP-ES.
• Validation of DCAT-AP-ES graphs against SHACL templates.

Key benefits of the update

The adoption of DCAT-AP-ES represents a qualitative leap in the management and reuse of open data in Spain. Among its benefits are: 

✅ Facilitates the federation of catalogues and the discovery of data. 
✅ Improves interoperability with the European open data ecosystem. 
✅ Complies with European open data regulations. 
✅ Increases metadata quality through validation mechanisms. 
✅ Ensures that data are FAIR (Findable, Accessible, Interoperable, Reusable).

Implementation and next steps

When will it come into force?

The new application profile DCAT-AP-ES will be progressively implemented in Spain's open data catalogues. Its application will be mandatory once the modification text of the standard comes into force which, as mentioned earlier, is currently undergoing administrative processing but is already compatible with the datos.gob.es data federator.

Are there supporting materials and resources for implementing DCAT-AP-ES?

The management team of the datos.gob.es platform has developed the DCAT-AP-ES Technical guide and model, available in the datos.gob.es repository.

This repository will be enriched as new needs of users applying the standard are identified. Likewise, help guides and educational resources will be developed to facilitate its adoption by publishing organizations. All the news and resources produced in the context of the application profile will be announced and referenced punctually on datos.gob.es.

Where to find more information?

The updated documentation, guides and resources will be accessible on datos.gob.es and in the associated code repository. At present the following are available:

• DCAT-AP-ES Technical guide and model
• DCAT-AP-ES Conventions
• DCAT-AP-ES Implementation examples
• DCAT-AP-ES Frequently Asked Questions
• DCAT-AP-ES Metadata validation
• DCAT-AP explanatory video: Spanish / English
• datos.gob.es

Learn more in this video:

And this infographic (click to access the interactive and accessible version):

The Data Governance Act (DGA) is part of a complex web of EU public policy and regulation, the ultimate goal of which is to create a dataset ecosystem that feeds the digital transformation of the Member States and the objectives of the European Digital Decade:

• A digitally empowered population and highly skilled digital professionals.
• Secure and sustainable digital infrastructures.
• Digital transformation of companies.
• Digitisation of public services.

Public opinion is focusing on artificial intelligence from the point of view of both the opportunities and, above all, the risks and uncertainties. However, the challenge is much more profound as it involves in each of the different layers very diverse technologies, products and services whose common element lies in the need to favour the availability of a high volume of reliable and quality-checked data to support their development.

Promoting the use of data with legislation as leverage

At its inception the Directive 2019/1024 on open data and re-use of public sector information (Open Data Directive), the Directive 95/46/EC on the processing of personal data and on the free movement of such data, and subsequently the Regulation 2016/679 known as the General Data Protection Regulation(GDPR) opted for the re-use of data with full guarantee of rights. However, its interpretation and application generated in practice an effect contrary to its original objectives, clearly swinging towards a restrictive model that may have affected the processes of data generation for its exploitation. The large US platforms, through a strategy of free services - search engines, mobile applications and social networks - in exchange for personal data and with mere consent, obtained the largest volume of personal data in human history, including images, voice and personality profiles.

With the GDPR, the EU wanted to eliminate 28 different ways of applying prohibitions and limitations to the use of data. Regulatory quality certainly improved, although perhaps the results achieved have not been as satisfactory as expected and this is indicated by documents such as the Digital Economy and Society Index (DESI) 2022 or the Draghi Report (The future of European competitiveness-Part A. A competitiveness strategy for Europe).

This has forced a process of legislative re-engineering that expressly and homogeneously defines the rules that make the objectives possible. The reform of the Open Data Directive, the DGA, the Artificial Intelligence Regulation and the future European Health Data Space (EHDS) should be read from at least two perspectives:

• The first of these is at a high level and its function is aimed at preserving our constitutional values. The regulation adopts an approach focused on risk and on guaranteeing the dignity and rights of individuals, seeking to avoid systemic risks to democracy and fundamental rights.
• The second is operational, focusing on safe and responsible product development. This strategy is based on the definition of process engineering rules for the design of products and services that make European products a global benchmark for robustness, safety and reliability.

A Practical Guide to the Data Governance Law

Data protection by design and by default, the analysis of risks to fundamental rights, the development process of high-risk artificial intelligence information systems validated by the corresponding bodies or the processes of access and reuse of health data are examples of the legal and technological engineering processes that will govern our digital development. These are not easy procedures to implement. The European Union is therefore making a significant effort to fund projects such as TEHDAS, EUHubs4Data or Quantum , which operate as a testing ground. In parallel, studies are carried out or guides are published, such as the Practical Guide to the Data Governance Law.

This Guide recalls the essential objectives of the DGA:

• Regulate the re-use of certain publicly owned data subject to the rights of third parties ("protected data", such as personal data or commercially confidential or proprietary data).
• Boost data sharing by regulating data brokering service providers.
• Encourage the exchange of data for altruistic purposes.
• Establish the European Data Innovation Board to facilitate the exchange of best practices.

The DGA promotes the secure re-use of data through various measures and safeguards. These focus on the re-use of data from public sector bodies, data brokering services and data sharing for altruistic purposes.

To which data does it apply? Legitimation for the processing of protected data held by public sector bodies

In the public sector they are protected:

• Confidential business data, such as trade secrets or know-how.
• Statistically confidential data.
• Data protected by the intellectual property rights of third parties.
• Personal data, insofar as such data do not fall within the scope of the Open Data Directive when irreversible anonymisation is ensured and no special categories of data are concerned.

An essential starting point should be underlined: as far as personal data are concerned, the General Data Protection Regulation (GDPR) and the rules on privacy and electronic communications (Directive 2002/58/EC) also apply. This implies that, in the event of a collision between them and the DGA, the former will prevail.

Moreover, the DGA does not create a right of re-use or a new legal basis within the meaning of the GDPR for the re-use of personal data. This means that Member State or Union law determines whether a specific database or register containing protected data is open for re-use in general. Where such re-use is permitted, it must be carried out in accordance with the conditions laid down in Chapter I of the DGA.

Finally, they are excluded from the scope of the DGA:

• Data held by public companies, museums, schools and universities.
• Data protected for reasons of public security, defence or national security.
• Data held by public sector bodies for purposes other than the performance of their defined public functions.
• Exchange of data between researchers for non-commercial scientific research purposes.

Conditions for re-use of data

It can be noted that in the area of re-use of public sector data:

▪ The DGA establishes rules for the re-use of protected data, such as personal data, confidential commercial data or statistically sensitive data.

▪ It does not create a general right of re-use, but establishes conditions where national or EU law allows such re-use.

▪ The conditions for access must be transparent, proportionate and objective, and must not be used to restrict competition. The rule mandates the promotion of data access for SMEs and start-ups, and scientific research. Exclusivity agreements for re-use are prohibited, except in specific cases of public interest and for a limited period of time.

▪ Attributes to public sector bodies the duty to ensure the preservation of the protected nature of the data. This will require the deployment of intermediation methodologies and technologies. Anonymisation and access through secure processing environments (Secure processing environments or SPE) can play a key role. The former is a risk elimination factor, while PES can define a processing ecosystem that provides a comprehensive service offering to re-users, from the cataloguing and preparation of datasets to their analysis. The Spanish Data Protection Agency has published an Approach to data spaces from a GDPR perspective that includes recommendations and methodologies in this area.

▪ Re-users are subject to obligations of confidentiality and non-identification of data subjects. In case of re-identification of personal data, the re-user must inform the public sector body and there may be security breach notification obligations.

▪ Insofar as the relationship is established directly between the re-user and the public sector body, there may be cases in which the latter must provide support to the former for the fulfilment of certain duties:

• To obtain, if necessary, the consent of the persons concerned for the processing of personal data.
• In case of unauthorised use of non-personal data, the re-user shall inform the legal entities concerned. The public sector body that initially granted the permission for re-use may provide support if necessary.

▪ International transfers of personal data are governed by the GDPR. For international transfers of non-personal data, the re-user is required to inform the public sector body and to contractually commit to ensure data protection. However, this is an open question, since, as with the GDPR, the European Commission has the power to:

1. Propose standard contractual clauses that public sector bodies can use in their transfer contracts with re-users.

2. Where a large number of requests for re-use from specific countries justify it, adopt "equivalence decisions" designating these third countries as providing a level of protection for trade secrets or intellectual property that can be considered equivalent to that provided for in the EU.

3. Adopt the conditions to be applied to transfers of highly sensitive non-personal data, such as health data. In cases where the transfer of such data to third countries poses a risk to EU public policy objectives (in this example, public health) and in order to assist public sector bodies granting permissions for re-use, the Commission will set additional conditions to be met before such data can be transferred to a third country.

▪ Public sector bodies may charge fees for allowing re-use. The DGA's strategy aims at sustainability of the system, as fees should only cover the costs of making data available for re-use, such as the costs of anonymisation or providing a secure processing environment. This would include the costs of processing requests for re-use. Member States must publish a description of the main cost categories and the rules used for their allocation.

▪ Natural or legal persons directly affected by a decision on re-use taken by a public sector body shall have the right to lodge a complaint or to seek a judicial remedy in the Member State of that public sector body.

Organisational support

It is entirely possible that public sector bodies offering intermediation services will multiply. This is a complex environment that will require technical and legal support, backstopping and coordination.

To this end, Member States should designate one or more competent bodies whose role is to support public sector bodies granting re-use. The competent bodies shall have adequate legal, financial, technical and human resources to carry out the tasks assigned to them, including the necessary expertise. They are not supervisory bodies, they do not exercise public powers and, as such, the DGA does not set specific requirements as to their status or legal form. In addition, the competent body may be given a mandate to allow re-use itself.

Finally, States must create a Single Point of Information or one-stop shop. This Point will be responsible for transmitting queries and requests to relevant public sector bodies and for maintaining an asset list with an overview of available data resources (metadata). The single information point may be linked to local, regional or sectoral information points where they exist. At EU level, the Commission created the European Register of Protected Data held by the Public Sector (ERPD), a searchable register of information collected by national single points of information to further facilitate the re-use of data in the internal market and beyond.

EU regulations are rules that are complex to implement. Therefore, a special pro-activity is required to contribute to its correct understanding and implementation. The EU Guide to the Deployment of the Data Governance Act is a first tool for this purpose and will allow a better understanding of the objectives and possibilities offered by the DGA.

This episode focuses on data governance and why it is important to have standards, policies and processes in place to ensure that data is correct, reliable, secure and useful. For this purpose, we analyze the Model Ordinance on Data Governance of the Spanish Federation of Municipalities and Provinces, known as the FEMP, and its application in a public body such as the City Council of Zaragoza. This will be done by the following guests:

• Roberto Magro Pedroviejo, Coordinator of the Open Data Working Group of the Network of Local Entities for Transparency and Citizen Participation of the Spanish Federation of Municipalities and Provinces and civil servant of the Alcobendas City Council.

• María Jesús Fernández Ruiz, Head of the Technical Office of Transparency and Open Government of Zaragoza City Council.

Listen to the full podcast (only available in Spanish)

Summary of the interview

1. What is data governance?

Roberto Magro Pedroviejo: We, in the field of Public Administrations, define data governance as an organisational and technical mechanism that comprehensively addresses issues related to the use of data in our organisation. It covers the entire data lifecycle, i.e. from creation to archiving or even, if necessary, purging and destruction. Its purpose is that data is of quality and available to all those who need it: sometimes it will be only the organisation itself internally, but many other times it will be the general public, re-users, the university environment, etc. Data governance must facilitate the right of access to data. In short, data governance makes it possible to respond to the objective of managing our administration effectively and efficiently and achieving greater interoperability between all administrations.

2. Why is this concept important for a municipality?

María Jesús Fernández Ruiz: Because we have found that, within organisations, both public and private, data collection and management is often carried out without following homogeneous criteria, standards or appropriate techniques. This translates into a difficult and costly situation, which is exacerbated when we try to develop a data space or develop data-related services. Therefore, we need an umbrella that obliges us to manage data, as Roberto has said, effectively and efficiently, following homogeneous standards and criteria, which facilitates interoperability.

3. To meet this challenge, it is necessary to establish a set of guidelines to help local administrations set up a legal framework. For this reason, the FEMP Model Ordinance on Data Governance has been created. What was the process of developing this reference document like?

Roberto Magro Pedroviejo: Within the Open Data Network Group that was created back in 2017, one of the people we have counted on and who has contributed a lot of ideas has been María Jesús, from Zaragoza City Council. We were leaving COVID, just in March 2021, and I remember perfectly the meeting we had in a room lent to us by the Madrid City Council in the Cibeles Palace. María Jesús was in Zaragoza and joined the meeting by videoconference. On that day, seeing what things and what work we could tackle within this multidisciplinary group, María Jesús proposed creating a model ordinance. The FEMP and the Network already had experience in creating model ordinances to try to improve, and above all help, municipalities and local entities or councils to create regulations.

We started working as a multidisciplinary team, led by José Félix Muñoz Soro, from the University of Zaragoza, who is the person who has coordinated the regulatory text that we have published. And a few months later, in January 2022 to be precise, we held a meeting. We met in person at the Zaragoza City Council and there we began to establish the basis for the model ordinance, what type of articles it should have, what type of structure it should have, etc. And we got together a multidisciplinary team, as we said, which included experts in data governance and jurists from the University of Zaragoza, staff from the Polytechnic University of Madrid, colleagues from the Polytechnic University of Valencia, professionals from the local public sphere and journalists who are experts in open data.

The first draft was published in May/June 2022. In addition, it was made available for public consultation through Zaragoza City Council's Citizen Participation platform. We contacted around 100 national experts and received around 30 contributions of improvements, most of which were included, and which allowed us to have the final text by the end of last year, which was passed to the legal department of the FEMP to validate it. The regulations were published in February 2024 and are now available on the Network's website for free download.

I would like to take this opportunity to thank the excellent work done by all the people involved in the team who, from their respective points of view, have worked selflessly to create this knowledge and share it with all the Spanish public administrations.

4. What are the expected benefits of the ordinance?

María Jesús Fernández Ruiz: For me, one of the main objectives of the ordinance, and I think it is a great instrument, is that it takes the whole life cycle of the data. It covers from the moment the data is generated, how the data is managed, how the data is provided, how the documentation associated with the data must be stored, how the historical data must be stored, etc. The most important thing is that it establishes criteria for managing the data while respecting its entire life cycle.

The ordinance also establishes some principles, which are not many, but which are very important and which set the tone, which speak, for example, of effective data governance and describe the importance of establishing processes when generating the data, managing the data, providing the data, etc.

Another very important principle, which has been mentioned by Roberto, is the ethical treatment of data. In other words, the importance of collecting data traceability, of seeing where the data is moving and of respecting the rights of natural and legal persons.

Another very important principle that generates a lot of noise in the institutions is that data must be managed from the design phase, the management of data by default. Often, when we start working on data with openness criteria, we are already in the middle or near the end of the data lifecycle. We have to design data management from the beginning, from the source. This saves us a lot of resources, both human and financial.

Another important issue for us and one that we advocate within the ordinance is that administration has to be data-oriented. It has to be an administration that is going to design its policies based on evidence. An administration that will consider data as a strategic asset and will therefore provide the necessary resources.

And another issue, which we often discuss with Roberto, is the importance of data culture. When we work on and publish data, data that is interoperable, that is easy to reuse, that is understood, etc., we cannot stop there, but we must talk about the data culture, which is also included in the ordinance. It is important that we disseminate what is data, what is quality data, how to access data, how to use data. In other words, every time we publish a dataset, we must consider actions related to data culture.

5. Zaragoza City Council has been a pioneer in the application of this ordinance. What has this implementation process been like and what challenges are you facing?

María Jesús Fernández Ruiz: This challenge has been very interesting and has also helped us to improve. It was very fast at the beginning and already in June we were going to present the ordinance to the city government. There is a process where the different parties make private votes on the ordinance and say "this point I like", "this point seems more interesting", "this one should be modified", etc. Our surprise is that we have had more than 50 private votes on the ordinance, after having gone through the public consultation process and having appeared in all the media, which was also enriching, and we have had to respond to these votes. The truth is that it has helped us to improve and, at the moment, we are waiting for it to go to government.

When they tell me how do you feel, María Jesús? The answer is well, we are making progress, because thanks to this ordinance, which is pending approval by the Zaragoza City Council government, we have already issued a series of contracts. One that is extremely important for us: to draw up an inventory of data and information sources in our institution, which we believe is the basic instrument for managing data, knowing what data we have, where they originate, what traceability they have, etc. Therefore, we have not stopped. Thanks to this framework that has not yet been approved, we have been able to make progress on the basis of contracts or something that is basic in an institution: the definition of the professionals who have to participate in data management.

6. You mentioned the need to develop an inventory of datasets and information sources, what kind of datasets are we talking about and what descriptive information should be included for each?

Roberto Magro Pedroviejo: There is a core, let's say a central core, with a series of datasets that we recommend in the ordinance itself, referring to other work done in the open data group, which is to recommend 80 datasets that we could publish in Spanish public administrations. The focus is also on high-value datasets, those that can most benefit municipal management or can benefit by providing social and economic value to the general public and to the business community and reusers. Any administration that wants to start working on the issue of datasets and wonders where to start publishing or managing data has to focus, in my view, on three key areas in a city:

• The personal data, i.e. our beloved census: who are the people living in our city, their ages, gender, postal addresses, etc.
• The urban and territorial data, that is, where these people live, what the territorial delimitation of the municipality is, etc. Everything that has to do with these sets of data related to streets, roads, even sewerage, public roads or lighting, needs to be inventoried, to know where these data are and to have them, as we have already said, updated, structured, accessible, etc.
• And finally, everything that has to do with how the city is managed, of course, with the tax and budget area.

That is: the personal sphere, the territorial sphere and the taxation sphere. That is what we recommend to start with. And in the end, this inventory of datasets describes what they are, where they are, how they are and will be the first basis on which to start building data governance.

María Jesús Fernández Ruiz: Another issue that is also very fundamental, which is included in the ordinance, is to define the master datasets. Just a little anecdote. When creating a spatial data space, the street map, the base cartography and the portal holder are basic. When we got together to work, a technical commission was set up and we considered these to be master datasets for Zaragoza City Council. The quality of the data is determined by a concept in the ordinance, which is respecting the sovereignty of the data: whoever creates the data is the sovereign of the data and is responsible for the quality of the data. Sovereignty must be respected and that determines quality.

We then discovered that, in Zaragoza City Council, we had five different portal identifiers. To improve this situation, we define a descriptive unique identifier which we declare as master data. In this way, all municipal entities will use the same identifier, the same street map, the same cartography, etc. and this will make all services related to the city interoperable.

7. What additional improvements do you think could be included in future revisions of the ordinance?

Roberto Magro Pedroviejo: The ordinance itself, being a regulatory instrument, is adapted to current Spanish and European regulations. In other words, we will have to be very vigilant -we are already - to everything that is being published on artificial intelligence, data spaces and open data. The ordinance will have to be adapted because it is a regulatory framework to comply with current legislation, but if that regulatory framework changes, we will make the appropriate modifications for compliance.

I would also like to highlight two things. There have been more town councils and a university, specifically the Town Council of San Feliu de Llobregat and the University of La Laguna, interested in the ordinance. We have received more requests to know a little more about the ordinance, but the bravest have been the Zaragoza City Council, who were the ones who proposed it and are the ones who are suffering the process of publication and final approval. From this experience that Zaragoza City Council itself is gaining, we will surely all learn, about how to tackle it in each of the administrations, because we copy each other and we can go faster. I believe that, little by little, once Zaragoza publishes the ordinance, other city councils and other institutions will join in. Firstly, because it helps to organise the inside of the house. Now that we are in a process of digital transformation that is not fast, but rather a long process, this type of ordinance will help us, above all, to organise the data we have in the administration. Data and the management of data governance will help us to improve public management within the organisation itself, but above all in terms of the services provided to citizens.

And the last thing I wanted to emphasise, which is also very important, is that, if the data is not of high quality, is not updated and is not metadata-driven, we will do little or nothing in the administration from the point of view of artificial intelligence, because artificial intelligence will be based on the data we have and if it is not correct or updated, the results and predictions that AI can make will be of no use to us in the public administration.

María Jesús Fernández Ruiz: What Roberto has just said about artificial intelligence and quality data is very important. And I would like to add two things that we are learning in implementing this ordinance. Firstly, the need to define processes, i.e. efficient data management has to be based on processes. And another thing that I think we should talk about, and we will talk about within the FEMP, is the importance of defining the roles of the different professionals involved in data management. We are talking about data manager, data provider, technology provider, etc. If I had the ordinance now, I would talk about that definition of the roles that have to be involved in efficient data management. That is, processes and professionals.

Interview clips

Data governance is crucial for the digital transformation of organisations.  It is developed through various axes within the organisation, forming an integral part of the organisational digital transformation plan. In a world where organisations need to constantly reinvent themselves and look for new business models and opportunities to innovate, data governance becomes a key part of moving towards a fairer and more inclusive digital economy, while remaining competitive. 

Organisations need to maximise the value of their data, identify new challenges and manage the role of data in the use and development of disruptive technologies such as Artificial Intelligence. Thanks to data governance, it is possible to make informed decisions, improve operational efficiency and ensure regulatory compliance, while ensuring data security and privacy.

To achieve this, it is essential to carry out a planned digital transformation, centred on a strategic data governance plan that complements the organisation's strategic plan. The UNE 0085 guide helps to implement data governance in any organisation and does so by placing special emphasis on the design of the programme through an evaluation cycle based on gap analysis, which must be relevant and decisive for senior management to approve the launch of the programme.

The data governance office, key body of the programme

A data governance programme should identify what data is critical to the organisation, where it resides and how it is used.. This must be accompanied by a management system that coordinates the deployment of data governance, management and quality processes. An integrated approach with other management systems that the organisation may have, such as the business continuity management system or the information security system, is necessary.

The Data Governance Office is the area in charge of coordinating the development of the different components of the data governance and management system, i.e. it is the area that participates in the creation of the guidelines, rules and policies that allow the appropriate treatment of data, as well as ensuring compliance with the different regulations.

The Data Governance Office should be a key body of the programme. It serves as a bridge between business areas, coordinating data owners and data stewards at the organisational level.

UNE 0085: guidelines for implementing data governance

Implementing a data governance programme is not an easy task. To help organisations with this challenge, the new UNE 0085  has been developed, which follows a process approach as opposed to an artefact approach and summarises as a guide the steps to follow to implement such a programme, thus complementing the family of UNE standards on data governance, management and quality 0077, 0078, 0079 and 0080.

This guide:

• It emphasises the importance of the programme being born aligned with the strategic objectives of the organisation, with strong sponsorship.
• Describes at a high level the key aspects that should be covered by the programme.
• Detalla diferentes escenarios tipo, que pueden ayudar a una organización a clarificar por dónde empezar y qué iniciativas debería priorizar, el modelo operativo y roles que necesitará para el despliegue.
• It presents the design of the data governance programme through an evaluation cycle based on gap analysis.  It starts with an initial assessment phase (As Is) to show the starting situation of the organisation followed by a second phase in which the scope and objectives of the programme are defined and aligned with the strategic objectives of the organisation phase (To be), to carry out the gap analysis phase. It ends with a business case that includes deliverables such as scope, frameworks, programme objectives and milestones, budget, roadmap and measurable benefits with associated KPIs among other aspects. This use case will serve as the launch of the data governance programme by management and thus its implementation throughout the organisation. The different phases of the cycle in relation to the UNE 0077 data governance system are presented below:

Finally, beyond processes and systems, we cannot forget people and the roles they play in this digital transformation. Data controllers and the entities involved are central to this organisational culture change. It is necessary to manage this change effectively in order to deploy a data governance operating model that fits the needs of each organisation.

It may seem complex to orchestrate and define an exercise of this magnitude, especially with abstract concepts related to data governance. This is where the new data governance office, which each organisation must establish, comes into play. This office will assist in these essential tasks, always following the appropriate frameworks and standards.

It is recommended to follow a methodology that facilitates this work, such as the UNE specifications for data governance, management and quality (0077, 0078, 0079 and 0080). These specifications are now complemented by the new UNE 0085, a practical implementation guide that can be downloaded free of charge from the AENOR website.

The content of this guide can be downloaded freely and free of charge from the AENOR portal through the link below by accessing the purchase section. Access to this family of UNE data specifications is sponsored by the Secretary of State for Digitalization and Artificial Intelligence, Directorate General for Data. Although the download requires prior registration, a 100% discount on the total price is applied at the time of finalizing the purchase. After finalizing the purchase, the selected standard or standards can be accessed from the customer area in “my products” section.

• ESPECIFICACION UNE 0085:2024 | Normas AENOR

One of the main requirements of the digital transformation of the public sector concerns the existence of optimal interoperability conditions for data sharing. This is an essential premise from a number of points of view, in particular as regards multi-entity actions and procedures. In particular, interoperability allows:

• The interconnection of the electronic registers powers and the filing of documents with public entities. 
• The exchange of data, documents and files in the exercise of the respective competences, which is essential for administrative simplification and, in particular, to guarantee the right not to submit documents already in the possession of the public administrations;
• The development of advanced and personalised services based on the exchange of information, such as the citizen folder.

Interoperability also plays an important role in facilitating the integration of different open data sources for re-use, hence there is even a specific technical standard. It aims to establish common conditions to "facilitate and guarantee the process of re-use of public information from public administrations, ensuring the persistence of the information, the use of formats, as well as the appropriate terms and conditions of use".

Interoperability at European level

Interoperability is therefore a premise for facilitating relations between different entities, which is of particular importance in the European context if we take into account that legal relations will often be between different states. This is therefore a great challenge for the promotion of cross-border digital public services and, consequently, for the enforcement of essential rights and values in the European Union linked to the free movement of persons.

For this reason, the adoption of a regulatory framework to facilitate cross-border data exchange has been promoted to ensure the proper functioning of digital public services at European level. This is Regulation (EU) 2024/903 of the European Parliament and of the Council of 13 March 2024 laying down measures for a high level of public sector interoperability across the Union (known as the Interoperable Europe Act), which is directly applicable across the European Union from 12 July 2024.

This regulation aims to provide the right conditions to facilitate cross-border interoperability, which requires an advanced approach to the establishment and management of legal, organisational, semantic and technical requirements. In particular, trans-European digital public services, i.e. those requiring interaction across Member States' borders through their network and information systems, will be affected. This would be the case, for example, for the change of residence to work or study in another Member State, the recognition of academic diplomas or professional qualifications, access to health and social security data or, as regards legal persons, the exchange of tax data or information necessary to participate in a tendering procedure in the field of public procurement. In short, "all those services that apply the "once-only" principle for accessing and exchanging cross-border data".

What are the main measures it envisages?

• Interoperability assessment: prior to decisions on conditions for trans-European digital public services by EU entities or public sector bodies of States, the Regulation requires them to carry out an interoperability assessment, although this will only be mandatory from January 2025. The result of this evaluation shall be published on an official website in a machine-readable format that allows for automatic translation.
• Sharing of interoperability solutions: the above mentioned entities shall be obliged to share interoperability solutions supporting a trans-European digital public service, including technical documentation and source code, as well as references to open standards or technical specifications used. However, there are some limits to this obligation, such as in cases where there are intellectual property rights in favour of third parties. In addition, these solutions will be published on the Interoperable Europe Portal, which will replace the current Joinup portal.
• Enabling of sandboxes: one of the main novelties consists of enabling public bodies to proceed with the creation of sandboxes or controlled interoperability test areas which, in the case of processing personal data, will be managed under the supervision of the corresponding supervisory authority competent to do so. The aim of this figure is to encourage innovation and facilitate cooperation based on the requirements of legal certainty, thereby promoting the development of interoperability solutions based on a better understanding of the opportunities and obstacles that may arise.
• Creation of a governance committee: as regards governance, it is envisaged that a committee will be set up comprising representatives of each of the States and of the Commission, which will be responsible for chairing it. Its main functions include establishing the criteria for interoperability assessment, facilitating the sharing of interoperability solutions, supervising their consistency and developing the European Interoperability Framework, among others. For their part, Member States will have to designate at least one competent authority for the implementation of the Regulation by 12 January 2025, which will act as a single point of contact in case there are several. Its main tasks will be to coordinate the implementation of the Act, to support public bodies in carrying out the assessment and, inter alia, to promote the re-use of interoperability solutions.

The exchange of data between public bodies throughout the European Union and its Member States with full legal guarantees is an essential priority for the effective exercise of their competences and, therefore, for ensuring efficiency in carrying out formalities from the point of view of good administration. The new Interoperable European Regulation is an important step forward in the regulatory framework to further this objective, but the regulation needs to be complemented by a paradigm shift in administrative practice. In this respect, it is essential to make a firm commitment to a document management model based mainly on data, which also makes it easier to deal with regulatory compliance with the regulation on personal data protection, and is also fully coherent with the approach and solutions promoted by the Data Governance Regulation when promoting the re-use of the information generated by public entities in the exercise of their functions.

Content prepared by Julián Valero, Professor at the University of Murcia and Coordinator of the Research Group "Innovation, Law and Technology" (iDerTec). The contents and points of view reflected in this publication are the sole responsibility of its author.

The Council of Ministers approved in February this year the Sustainable Mobility Bill (PL), a commitment to a digital and innovative transport system in which open mobility data will play a key role.

Inaddition to regulating innovative solutions such as on-demand transport, car sharing or temporary use of vehicles, the regulation will encourage the promotion ofopen data by administrations, infrastructure managers and public and private operators. All this, as stated in Chapter III Title V of the Draft Law "will bring enormous benefits to citizens, e.g. for new mobility and their contribution to the European Green Pact".

This Bill is aligned with the European Data Strategy, which has among its objectives to create a single market for data that ensures Europe' s global competitiveness and data sovereignty through the creation of common European data spaces common European data spaces in nine strategic sectors. In particular, it foresees the creation and development of a common European mobility data space to put Europe at the forefront of the development of a smart transport system, including connected cars and other modes of transport. Along these lines, the European Commission presented its Sustainable and Intelligent Mobility Strategywhich includes an action dedicated to innovation, data and artificial intelligence for smarter mobility. Following in Europe's footsteps, Spain has launched this Sustainable Mobility Bill.

In this post we look at the benefits that the use of open data can bring to the sector, the obligations that the PL will place on data, and the next steps in building the Integrated Mobility Data Space.

Benefits of using open data on sustainable mobility

The Ministry of Transport and Sustainable Mobility, in the web section created for the Law, identifies some of the benefits that access to and use of open transport and mobility data can offer both to the business community and to public administrations and citizens in general:

• Encourage the development of applications that enable citizens to make decisions on the planning of their journeys and during the course of their journeys.
• Improve the conditions of service provision and the travel experience .
• Incentivise research, create new developments and businesses from the data generated in the transport and mobility ecosystem.
• Enable public administrations to have a better understanding of the transport and mobility system in order to improve the definition of public policies and the management of the system.
• Encourage the use of this data for other public interest purposes that may arise.

Ensuring access to open mobility data

In order to make good use of these data and thus take advantage of all the benefits they offer, the Draft Law determines a strategy to ensure the availability of open data in the field of transport and mobility. This strategy concerns:

•  transport companies and infrastructure managers, which must drive digitalisation and provide a significant part of the data, with specific characteristics and functionalities.
• administrations and public entities were already obliged to ensure the openness of their data by design, as well as its re-use on the basis of the already existing

In short, the guidelines for re-use already defined in Law 37/2007 for the public sector are respected, and the need to regulate access to this information and the way in which this data is used by third parties, i.e. companies in the sector, is also included.

Integrated Mobility Data Space

In line with the European Data Strategy mentioned at the beginning of the post, the PL determines the obligation to create the Integrated Mobility Data Space (EDIM) under the direction of the Ministry of Transport and Sustainable Mobility, in coordination with the Secretary of State for Digitalisation and Artificial Intelligence. In the EDIM, the aforementioned transport companies, infrastructure managers and administrations will share their data, which will optimise the decision making of all actors when planning the implementation of new infrastructures and the launch of new services. 

The Draft Law defines some characteristics of the Integrated Mobility Data Space such as the modular structure, which will include information in a systematic way on different areas of urban, metropolitan and interurban mobility, both for people and goods.

Specifically, the EDIM, according to Article 14, would collect data "in digital form in a free, non-discriminatory and up-to-date manner" on:

• Supply and demand of the different modes of transport and mobility, information on public transport services and mobility services under the responsibility of the administrations
• Financial situation and costs of providing services for all modes of public transport, investments in transport infrastructure, inventory of transport infrastructure and terminals, conditions and degree of accessibility.
• Other data to be agreed at the Sectoral Conference on Transport.

It identifies examples of this type of data and information on the responsibility for its provision, format, frequency of updating and other characteristics.

As referred to in the CP, the data and information managed by the EDIM will provide an integrated vision to analyse and facilitate mobility management, improving the design of sustainable and efficient solutions, and transparency in the design of public transport and mobility policies. In addition, the Law will promote the creation of a sandbox or test environment to serve as an incubator for innovative mobility projects. The outcome of the tests will allow both the developer and the administration to learn by observing the market in a controlled environment.

National Bimodal Transport Access Point

On the other hand, the Bill also provides for the creation of a National Bimodal Transport Access Point that will collect the information communicated to the Ministry of Transport and Sustainable Mobility in the framework of the priority action "Provision of information services on multimodal journeys throughout the Union" of Directive 2010/40/EU which refers to the transport of goods and/or persons by more than one means of transport.

This information will be freely accessible and will also serve to feed the EDIM in the area related to the characterisation of transport and mobility of persons, as well as the National Catalogue of Public Information maintained by the General State Administration.

The Bill defines that the provision of services to citizens using transport and mobility data from the National Multimodal Transport Access Point must be done in a fair, neutral, impartial, non-discriminatory and transparent manner. It adds that the Ministry of Transport and Sustainable Mobility will propose rules for the use of such data within 12 months after the entry into force of this law.

The Sustainable Mobility Bill is currently in parliamentary procedure, as it has been sent to the Spanish Parliament for urgent processing and approval in 2024.

The Spanish Federation of Municipalities and Provinces (FEMP) approved at the end of 2023 two model ordinances that address progress in two key areas: transparency and data governance. Both documents will not only improve the quality of processes, but also facilitate access, management and re-use of data. In this post, we will analyse the second ordinance drafted within the FEMP's Network of Entities for Transparency and Citizen Participation in its quest to define common reference models. In particular, the ordinance on data governance.

The usefulness and good work of the Model Ordinance on Data Governance in Local Entities has been highlighted by the Multisectoral Association of Information (ASEDIE), which awarded it the prize in the category 'Promoting data literacy' at its 15th ASEDIE International Conference.

Under this premise, the document addresses all elements related to the collection, management and exploitation of data in order to approach them as a commongood, i.e. ensuring their openness, accessibility and re-use. This is a relevant objective for local administrations, as it enables them to improve their functioning, service delivery and decision-making. Data governance is the framework that guides and guarantees this process and this ordinance proposes a flexible regulatory framework that different administrations can adapt according to their specific needs.

What is data governance?

 Data Governance comprehensively addresses all aspects related to the collection, management and exploitation of data, as well as its openness and re-use by society as a whole on an equal basis. Itcan therefore bedefined as an organisational function responsible for being accountable for the effective, efficient and acceptable use of databy the organisation, which is necessary to deliver the business strategy. This is described in the specifications UNE 0077:2023 on Data Governance and UNE 78:2023 on Data Management, which include standardised processes to guide organisations in the establishment of approved and validated mechanisms that provide organisational support to aspects related to the opening and publication of data, for subsequent use by citizens and other institutions.

How was the FEMP Data Governance Ordinance developed?

In order to develop the Model Ordinance on Data Governance in the Local Entity, a multidisciplinary working group was set up in 2022, which included workers from the Public Administrations, private companies, representatives of the infomediary sector, the Data Office, universities, etc. This team set out two main objectives that would mark the content of the document:

• Develop guidelines for municipalities and other public authorities defining the strategy to be followed in order to implement an open data project.
• Create a reference model of datasets common to all public administrations to facilitate the re-use of information.

With these two challenges in mind, in early 2023 the FEMP working group started to establish aspects, structure, contents and work plan. During the following months, work was carried out to draft, elaborate and reach consensus on a single draft.

In addition, a participatory process was organised on the Idea Zaragoza platform to nurture the document with contributions from experts from all over the country and FEMP partners.

The result of all the work was based on the Open Data Charter (ODC), the recommendations issued by the Spanish Government's Data Office and the existing European and national regulations on this matter.

New features and structure of the Data Governance Ordinance

The FEMP's Model Ordinance on Data Governance is in line with the context in which it has been presented, i.e. it recognises relevant aspects of the current moment we are living in. One of the document's salient features is the premise of guaranteeing and enhancing the rights of both natural and legal persons and respecting the General Data Protection Regulation. The regulation places particular emphasis on the proportionality of anonymisation to ensure the privacy of individuals.

Another novel aspect of the standard is that it brings the vision of high-value data defined by the European Commission from the perspective of local government. In addition, the Model Ordinance recognises a single regime for access and re-use of public information, in accordance with Law 19/2013 of 9 December on transparency, access to public information and good governance, and Law 37/2007 on the re-use of public sector information.

Beyond ensuring the legal and regulatory framework, the FEMP Ordinance also addresses the data associated with artificial intelligence, a cutting-edge technological synergy that every day offers great innovative solutions. For an artificial intelligence to function properly, it is necessary to have quality data to help train it. In relation to this point, the ordinance defines quality requirements (Article 18) and metrics for their assessment that are adapted to each specific context and address issues such as accuracy, portability or confidentiality, among others.  The document establishes guarantees that the use of the data will be carried out in a way that respects the rights of individuals.

All these new aspects are part of the FEMP's Model Ordinance on Data Governance for Local Entities, which is organised in the following structure:

1. General provisions: This first section presents data as the main digital asset of Public Administrations as a strategic asset, and the object, principles and right of citizenship.
2. Planning, organisation and tools for data governance: Here the organisation and competencies for data governance are defined. In addition, the importance of maintaining an inventory of datasets and information sources is stressed (Article 9).
3. The data: This chapter recognises the publication requirements and security standards, the importance of the use of reference vocabularies, and the categories of datasets whose openness should be prioritised, namely the 80 typologies referred to by FEMP as most relevant.
4. Life cycle: This section highlights, on the one hand, the collection, opening, storage and use of data; and, on the other hand, the limits, deletion and destruction of data when these actions are required.  when these actions are required.
5. Access, publication and re-use: The fifth chapter deals with issues related to the exploitation of data such as the use of specific licences, exclusive rights, payment for re-use or prior request for access to certain datasets.
6. Liability and guarantees: The last point describes the sanctioning and disciplinary regime and the civil and criminal liabilities of the re-user.

In short, the publication of the Ordinance on Data Governance in Local Entities provides local administrations with a flexible regulation and defines administrative structures that seek to improve management, reuse and the promotion of a data-driven society.

You can access the full document here: Standard Ordinance on Data Governance in the Local Entity

The year is coming to an end and it is a good time to review some of the issues that have marked the open data and data sharing ecosystem in Spain, a community that continues to grow and build alliances for the development of innovative technologies. A synergy that lays the foundations to face an interconnected, digital future full of possibilities.   

With 2024 just a few days away, we take stock of the news, events and training of interest that have marked the year behind us. In this compilation we review some regulatory developments, new portals and projects promoted by the public sector, as well as various educational resources and reference documentation that 2023 has left us. 

Legal regulation for the development of collaborative environments  

During this year, in datos.gob.es we have echoed relevant news in the open data and data sharing sector. All of them have contributed to consolidate the appropriate context for interoperability and the promotion of the value of data in our society. The following is a review of the most relevant announcements: 

• At the beginning of the year, the European Commission published a first list of high-value datasets that are of great value to the economy, the environment and society because of the information they contain. For this reason, member states must make them available to the public by summer 2024. This first list of categories includes geospatial, earth observation and environmental, meteorological, statistical, business and mobility data. On the other hand, at the end of 2023, the same body made a proposal to expand the list of categories of datasets to be considered of high value, adding another seven proposals for categories that could be included in the future: climate loss, energy, financial, public administration and government, health, justice and language. 

• In the first quarter of the year, Law 37/2007 on the reuse of public sector information was amended in light of the latest European Open Data Directive. Now, public administrations will have to comply with, among others, two essential requirements: to focus on the publication of high-value data through APIs and to designate a unit responsible for information to ensure the correct opening of data. These measures are intended to be aligned with the demands of competitiveness and innovation raised by technologies such as AI and with the key role played by data when it comes to configuring data spaces.  

• The publication of the UNE data specifications was another milestone in standardization that marked 2023. The volume of data continues to grow and mechanisms are needed to ensure its proper use and exploitation. To this end, there are: 

  • UNE 0077 on Data Governance  

  • UNE 0078 on Data Management  

  • UNE 0079 on Data Quality Management  

  • UNE 0080, Data Governance, Management and Quality Evaluation Guide  

  • UNE 0081, Guide to Data Quality Evaluation.  

• Another noteworthy advance has been the approval of the consolidated wording of the European Data Regulation (Data Act), which seeks to provide harmonized standards for fair access to and use of data. The legal structure that will drive the data economy in the EU is now a reality. The Data Act and the Data Governance Act also passed in 2023 will contribute to the development of a European Digital Single Market.  

• In October 2023 the future Interoperable Europe Act (Interoperable Europe Act) entered the final legislative stage after getting the go-ahead from the member states. The aim of the Interoperable Europe Act is to strengthen interoperability between public sector administrations in the EU and to create digital public services focused on citizens and businesses. 

Advances in the open data ecosystem in Spain  

 In the last year, many public bodies have opted for opening their data in formats suitable for reuse, many of them focused on specific topics, such as meteorology. Some examples are:  

•  The Diputación de Segovia premiered an open data portal with information from city councils.  

• The Cabildo de Palma launched a new open and real-time weather data portal that provides information on current and historical weather and air quality.  

• The City Council of Soria also created a georeferenced information viewer that allows to consult parameters such as air quality, noise level, meteorology or traffic of people, among other variables.   

• The Malaga City Council has recently allied with the CSIC to develop a marine observatory that will collect and share open data in real time on coastal activity.   

• Progress on new portals will continue during 2024, as there are city councils that have expressed their interest in developing projects of this type. One example is the City Council of Las Torres de Cotillas: it recently launched a municipal website and a citizen participation portal in which they plan to enable an open data space in the near future. 

On the other hand, many institutions that already published open data have been expanding their catalog of datasets throughout the year. This is the case of the Canary Islands Statistics Institute (ISTAC), which has implemented various improvements such as the expansion of its semantic open data catalog to achieve better data and metadata sharing. 

Along these lines, more agreements have also been signed to promote the opening and sharing of data, as well as the acquisition of related skills. For example, with universities:  

• The Navarra Open Data portal incorporated information provided by the Public University of Navarra (UPNA) on its structure, activity, economic data and workforce.   

• The University of Valladolid (UVa) has presented a Chair of Transparency and Open Government that will address issues such as data governance, among others.   

• The University of Burgos has implemented an open science policy to foster collaboration and knowledge sharing and provide equal access to scientific and research work.   

• The Carlos III University of Madrid (UC3M) has partnered with the Community of Madrid to establish the Chair on Territorial Dynamism that will promote research and the development of open data analysis activities, among others. 

Disruptive solutions using open data   

The winning combination of open data and technology has driven the development of multiple initiatives of interest as a result of the efforts of public administrations, such as, for example:  

• The Community of Madrid managed to optimize by 25% the reliability of the prediction of pollen levels in the territory thanks to artificial intelligence and open data. Through the CAM's open data portal, citizens can access an interactive map to find out the level of pollen in the air in their area.    

• The Valencia City Council's Chair of Governance at the Polytechnic University (UPV) published a study that uses open data sources to calculate the carbon footprint by neighborhoods in the city of Valencia.   

• The Xunta de Galicia presented a digital twin project for territorial management that will have information stored in public and private databases.   

• The Consejo Superior de Investigaciones Científicas (CSIC) initiated the TeresIA project for terminology in Spanish that will generate a meta-search engine for access to terminologies of pan-Hispanic scope based on AI and open data.   

During 2023, Public Administrations have not only launched technological projects, but have also boosted entrepreneurship around open data with activities such as the Castilla y León Open Data contest. An event in which projects developed with open data as products or services, ideas, data journalism works and didactic resources were awarded. 

Trainings and events to keep up with the trends  

Educational materials on open data and related technologies have only grown in 2023. We highlight some free and virtual resources that are available:  

• The European Open Data Portal is a reference source in all aspects, also at the training level. Over the last year, it has shared educational resources such as this free course on data visualization, this one on the legal aspects of open data or this one on how to incorporate open data into an application.  

• In 2023, the European Interoperability Academy published a free online short course on open source licensing for which no prior knowledge of the subject is required.   

• In 2023, we have published more practical exercises from the 'Visualizations step by step' series such as this tutorial to learn how to generate a customized tourist map with MyMaps or this analysis of meteorological data using the "ggplot2" library. 

In addition, there are many activities that have been carried out in 2023 to promote the data culture. However, if you missed any of them, you can re-watch the online recordings of the following ones:   

• In March, the European Conference on Data and Semantics was broadcast, presenting trends in multilingual data.  

• In September, the 2nd National Open Data Meeting was held under the theme "Urgent Call to Action for the Environment".  The event continued the tradition started in 2022 in Barcelona, consolidating itself as one of the main meetings in Spain in the field of public sector data reuse and presenting training materials of interest to the community.  

• In October, the European benchmark interoperability conference SEMIC 2023, Interoperable Europe in the age of AI, was organized in Madrid. 

Reports and other reference documents published in 2023  

Once we have reviewed the news, initiatives, trainings and events, we would like to highlight a compendium of extensive knowledge such as the set of in-depth reports that have been published in 2023 on the open data sector and innovative technologies. Some noteworthy ones are:  

• The Asociación Multisectorial de la Información (ASEDIE) presented in April 2023 its 11th edition of the Infomediary Sector Report in which it reviews the health of companies working with data, a sector with growth potential. Here you can read the main conclusions.  

• From October 2023 Spain co-chaired the Steering Committee of the Open Government Partnership (OGP), a task that has involved driving OGP initiatives and leading open government thematic areas. This organization presented its global Open Government Partnership report in 2023, a document that highlights good practices such as the publication of large volumes of open data by European countries. In addition, it also identifies several areas for improvement such as the publication of more high-value data (HDV) in reusable and interoperable formats. 

• The Organisation for Economic Co-operation and Development (OECD) published a report on public administration principles in November 2023 in which it highlighted, among others, digitization as a tool for making data-driven decisions and implementing effective and efficient processes.  

• During this year, the European Commission published a report on the integration of data spaces in the European data strategy. Signed by experts in the field, this document lays the groundwork for implementing European dataspaces.  

• On the other hand, the open data working group of the Red de Entidades Locales por la Transparencia y la Participación Ciudadana and the Spanish Federation of Municipalities and Provinces presented a list of the 80 datasets to be published to continue completing the guides published in previous years. You can consult it here. 

These are just a few examples of what the open data ecosystem has given of itself in the last year. If you would like to share with datos.gob.es any other news, leave us a comment or send us an email to dinamizacion@datos.gob.es. 

Today, data quality plays a key role in today's world, where information is a valuable asset. Ensuring that data is accurate, complete and reliable has become essential to the success of organisations, and guarantees the success of informed decision making.

Data quality has a direct impact not only on the exchange and use within each organisation, but also on the sharing of data between different entities, being a key variable in the success of the new paradigm of data spaces. When data is of high quality, it creates an environment conducive to the exchange of accurate and consistent information, enabling organisations to collaborate more effectively, fostering innovation and the joint development of solutions.

Good data quality facilitates the reuse of information in different contexts, generating value beyond the system that creates it. High-quality data are more reliable and accessible, and can be used by multiple systems and applications, which increases their value and usefulness. By significantly reducing the need for constant corrections and adjustments, time and resources are saved, allowing for greater efficiency in the implementation of projects and the creation of new products and services.

Data quality also plays a key role in the advancement of artificial intelligence and machine learning. AI models rely on large volumes of data to produce accurate and reliable results. If the data used is contaminated or of poor quality, the results of AI algorithms will be unreliable or even erroneous. Ensuring data quality is therefore essential to maximise the performance of AI applications, reduce or eliminate biases and realise their full potential.

With the aim of offering a process based on international standards that can help organisations to use a quality model and to define appropriate quality characteristics and metrics, the Data Office has sponsored, promoted and participated in the generation of the specification UNE 0081 Data Quality Assessment that complements the already existing specification UNE 0079 Data Quality Management, focused more on the definition of data quality management processes than on data quality as such.

UNE Specification - Guide to Data Quality Assessment

The UNE 0081 specification, a family of international standards ISO/IEC 25000, makes it possible to know and evaluate the quality of the data of any organisation, making it possible to establish a future plan for its improvement, and even to formally certify its quality. The target audience for this specification, applicable to any type of organisation regardless of size or dedication, will be data quality officers, as well as consultants and auditors who need to carry out an assessment of data sets as part of their functions.

The specification first sets out the data quality model, detailing the quality characteristics that data can have, as well as some applicable metrics, and once this framework is defined, goes on to define the process to be followed to assess the quality of a dataset. Finally, the specification ends by detailing how to interpret the results obtained from the evaluation by showing some concrete examples of application.

Data quality model

The guide proposes a series of quality characteristics following those present in the ISO/IEC 25012 standard , classifying them between those inherent to the data, those dependent on the system where the data is hosted, or those dependent on both circumstances. The choice of these characteristics is justified as they encompass those present in other frameworks such as DAMA, FAIR, EHDS, IA Act and GDPR.