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In today's digital age, data sharing and opendatahave emerged as key pillars for innovation, transparency and economic development. A number of companies and organisations around the world are adopting these approaches to foster open access to information and enhance data-driven decision making. Below, we explore some international and national examples of how these practices are being implemented.

Global success stories

One of the global leaders in data sharing is LinkedIn with its Data for Impactprogramme. This programme provides governments and organisations with access to aggregated and anonymised economic data, based on LinkedIn's Economic Graph, which represents global professional activity. It is important to clarify that the data may only be used for research and development purposes. Access must be requested via email, attaching a proposal for evaluation, and priority is given to proposals from governments and multilateral organisations. These data have been used by organisations such as the World Bank and the European Central Bank to inform key economic policies and decisions. LinkedIn's focus on privacy and data quality ensures that these collaborations benefit both organisations and citizens, promoting inclusive, green and digitally aligned economic growth.

On the other hand, the Registry of Open Data on AWS (RODA) is an Amazon Web Services (AWS) managed repository that hosts public datasets. The datasets are not provided directly by AWS, but are maintained by government organisations, researchers, companies and individuals. We can find, at the time of writing this post, more than 550 datasets published by different organisations, including some such as the Allen Institute for Artificial Intelligence (AI2) or NASAitself. This platform makes it easy for users to leverage AWS cloud computing services for analytics.

In the field of data journalism, FiveThirtyEight, owned by ABC News, has taken a radical transparency approach by publicly sharing the data and code behind its articles and visualisations. These are accessible via GitHub in easily reusable formats such as CSV. This practice not only allows for independent verification of their work, but also encourages the creation of new stories and analysis by other researchers and journalists. FiveThirtyEight has become a role model for how open data can improve the quality and credibility of journalism.

Success stories in Spain

Spain is not lagging behind in terms of data sharing and open data initiatives by private companies. Several Spanish companies are leading initiatives that promote data accessibility and transparency in different sectors. Let us look at some examples.

Idealista, one of the most important real estate portals in the country, has published an open data set that includes detailed information on more than 180,000 homes in Madrid, Barcelona and Valencia. This dataset provides the geographical coordinates and sales prices of each property, together with its internal characteristics and official information from the Spanish cadastre. This dataset is available for access through GitHub as an R package and has become a great tool for real estate market analysis, allowing researchers and practitioners to develop automatic valuation models and conduct detailed studies on market segmentation. It should be noted that Idealista also reuses public data from organisations such as the land registry or the INE to offer data services that support decisions in the real estate market, such as contracting mortgages, market studies, portfolio valuation, etc. For its part, BBVA, through its Foundation, offers access to an extensive statistical collection with databases that include tables, charts and dynamic graphs. These databases, which are free to download, cover topics such as productivity, competitiveness, human capital and inequality in Spain, among others. They also provide historical series on the Spanish economy, investments, cultural activities and public spending. These tools are designed to complement printed publications and provide an in-depth insight into the country's economic and social developments.

In addition, Esri Spain enables its Open Data Portal, which provides users with a wide variety of content that can be consulted, analysed and downloaded. This portal includes data managed by Esri Spain, together with a collection of other open data portals developed with Esritechnology. This significantly expands the possibilities for researchers, developers and practitioners looking to leverage geospatial data in their projects. Datasets can be found in the categories of health, science and technology or economics, among others.

In the area of public companies, Spain also has outstanding examples of commitment to open data. Renfe, the main railway operator, and Red Eléctrica Española (REE), the entity responsible for the operation of the electricity system ,have developed open data programmes that facilitate access to relevant information for citizens and for the development of applications and services that improve efficiency and sustainability. In the case of REE, it is worth highlighting the possibility of consuming the available data through  RESTAPIs, which facilitate the integration of applications on data sets that receive continuous updates on the state of the electricity markets.

Conclusion

Data sharing and open data represent a crucial evolution in the way organisations manage and exploit information. From international tech giants such as LinkedIn and AWS to national innovators such as Idealista and BBVA, they are providing open access to data in order to drive significant change in how decisions are made, policy development and the creation of new economic opportunities. In Spain, both private and public companies are showing a strong commitment to these practices, positioning the country as a leader in the adoption of open data and data sharing models that benefit society as a whole.

Content prepared by Juan Benavente, senior industrial engineer and expert in technologies linked to the data economy. The contents and points of view reflected in this publication are the sole responsibility of the author.

Data is a key part of Europe''s digital economy. This is recognised in the Data Strategy, which aims to create a single market that allows free movement of data in order to foster digital transformation and technological innovation. However, achieving this goal involves overcoming a number of obstacles. One of the most salient is the distrust that citizens may feel about the process.

In response to this need, the Data Governance Act or Data Governance Act (DGA), a horizontal instrument that seeks to regulate the re-use of data over which third party rights concur, and to promote their exchange under the principles and values of the European Union. The objectives of the DGA include strengthening the confidence of citizens and businesses that their data is re-used under their control, in accordance with minimum legal standards.

Among other issues, the DGA elaborates on the concept ofdata intermediaries , for whom it establishes a reporting and monitoring framework. 

What are data brokers?

The concept of data brokers is relatively new in the data economy, so there are multiple definitions. If focusing on the context of the DGAdata Intermediation Services Providers ( DISPs) are those "whose purpose is to establish commercial relationships for the exchange of data between an undetermined number of data subjects and data owners on the one hand, and data users on the other hand".

The Data Governance Act also differentiates betweenData Brokering Service Providers andData Altruism Organisations Recognised in the Union (RDAOs). The latter concept describes a data exchange relationship, but without seeking a profit for it, in an altruistic way.

What types of data brokering services exist according to the DGA?

Data brokering services are another piece of data sharing, as they make it easier for data subjects to share their data so that it can be reused. They canalso provide technical infrastructure and expertise to support interoperability between datasets, or act as mediators negotiating exchange agreements between parties interested in sharing, accessing or pooling data.

Chapter III of the Data Governance Act explains three types of data brokering services:

• Intermediation services between data subjects and their potential users, including the provision of technical or other means to enable such services. They may include the bilateral or multilateral exchange of data, as well as the creation of platforms, databases or infrastructures enabling their exchange or common use.
• Intermediation services between natural persons wishing to make their personal and non-personal data availableto potential users, including technical means. These services should make it possible for data subjects to exercise their rights as provided for in the General Data Protection Regulation (Regulation 2016/679).
• Data cooperatives. These are organisational structures made up of data subjects, sole proprietorships or SMEs. These entities assist cooperative members in exercising their rights over their data.

In summary, the first type of service can facilitate the exchange of industrial data, the second focuses mainly on the exchange of personal data and the third covers collective data exchange and related governance schemes.
 

Categories of data intermediaries in detail:

To explore these concepts further, the European Commission has published the report ''...Mapping the landscape of data intermediariesthereport examines in depth the types of data brokering that exist. The report''s findings highlight the fragmentation and heterogeneity of the field.

Types of data brokers range from individualistic and business-oriented to more collective and inclusive models that support greater participation in data governance by communities and individual data subjects. Taking into account the categories included in the DGA, six types of data intermediaries are described:

Source: Mapping the landscape of data intermediaries published by the European Comission

Each of these is described below:

1. Personal Information Management Systems (PIMS): provides tools for individuals to control and direct the processing of their data.
2. Data cooperatives: foster democratic governance through agreements between members. Individuals manage their data for the benefit of the whole community.
3. Data trusts: establish specific legal mechanisms to ensure responsible and independent management of data between two entities, an intermediary that manages the data and its rights, and a beneficiary and owner of the data.
4. Data syndicates: these are sectoral or territorial unions between different data owners that manage and protect the rights over personal data generated through platforms by both users and workers.
5. Data marketplaces: these drive platforms that match supply and demand for data or data-based products/services.
6. Data sharing pools: these are alliances between parties interested in sharing data to improve their assets (data products, processes and services) by taking advantage of the complementarity of the data pooled.

In order to consolidate data brokers, further research will be needed to help further define the concept of data brokers. This process will entail assessing the needs of developers and entrepreneurs on economic, legal and technical issues that play a role in the establishment of data brokers, the incentives for both the supply and demand side of data brokers, and the possible connections of data brokers with other EU data policy instruments.

The types of data intermediaries differ according to several parameters, but are complementary and may overlap in certain respects. For each type of data intermediary presented, the report provides information on how it works, its main features, selected examples and business model considerations.

Requirements for data intermediaries in the European Union

The DGA establishes rules of the game to ensure that data exchange service providers perform their services under the principles and values of the European Union (EU). Suppliers shall be subject to the law of the Member State where their head office is located. If you are a provider not established in the EU, you must appoint a legal representative in one of the Member States where your services are offered.

Any data brokering service provider operating in the EU must notify the competent authority. This authority shall be designated by each State and shall ensure that the supplier carries out its activity in compliance with the law. The notification shall include information on the supplier''s name, legal nature (including information on structure and subsidiaries), address, website with information on its activities, contact person and estimated date of commencement of activity. In addition, it shall include a description of the data brokering service it performs, indicating the category detailed in the GAD to which it belongs, i.e. brokering services between data subjects and users, brokering services between data subjects or individuals and data users or data cooperatives.

Furthermore, in its Article 12, the DGA lays down a number of conditions for the provision of data brokering services. For example, providers may not use the data in connection with the provision of their services, but only make them available. They must also respect the original formats and may only make transformations to improve their interoperability. They should also provide for procedures to prevent fraudulent or abusive practices by users. This is to ensure that services are neutral, transparent and non-discriminatory.

Future scenarios for data intermediaries

According to the report "Mapping the landscape of data intermediaries", on the horizon, the envisaged scenario for data intermediaries involves overcoming a number of challenges:

Identify appropriate business models that guarantee economic sustainability. Expand demand for data brokering services. Understand the neutrality requirement set by the DGA and how it could be implemented. Align data intermediaries with other EU data policy instruments. Consider the needs of developers and entrepreneurs. Meeting the demand of data intermediaries.

Navarra has been the chosen venue to bring together, for the first time, representatives of the Data Offices of the autonomous communities around the centrality of data in public management. The meeting, promoted by the Secretary of State for Digitalization and Artificial Intelligence (SEDIA) and the Government of Navarra, was aimed at sharing the advances in the world of data at the regional level, as well as the assumption of commitments to lay the foundations for a digital future linked to data and its transformative power.  

Focus on the transformative power of data  

The Councilor for University, Innovation and Digital Transformation of the Government of Navarra, Juan Cruz Cigudosa García, was in charge of opening the conference, emphasizing the need to strengthen the response to social challenges and stimulate innovation and economic development through data, highlighting the unavoidable commitment to innovation through the use of disruptive technologies such as Artificial Intelligence, always under an ethical prism and respect for European values and principles. In this last line of action, the launching of an Ethics Committee for the Navarra Data Office was announced. This committee, framed in the Digital Spain Strategy and the Navarra Digital Strategy 2030, is aligned with the active policies and the national and international leadership of SEDIA, reflected in its charter of digital rights.   

Next, the Chief Data Officer of the Government of Spain, Alberto Palomo, highlighted the strategy that had been designed at European level in relation to data and its sovereign management. He also pointed out the transformative power of data, a key element in the digital transformation and in the entry of technologies such as artificial intelligence. He also reported on the recent statement published as a result of the current Spanish Presidency of the Council of the European Union, which was signed at the beginning of November during the Gaia-X Summit meeting under the name "The Trinity of Trusted Cloud, Data and AI as Gateway to EU's competitiveness". This document is a declaration that shows the commitment of the participants in this meeting to boost data spaces in Europe through strategic autonomy in the cloud, data and artificial intelligence. It agrees, among other points, to expand and improve coordination in the development of European cloud and data initiatives, advocating interoperability as a backbone element and advocating the development of Artificial Intelligence based on high quality data and with solid governance. It also highlights the need to homogenize data sources to better model relationships, optimize processes and innovate and create new business models.   

The day continued as a communication forum, in which, as an example, direct experiences of the participants could be shared, thus creating a space for reflection and dialogue. The day was structured through three thematic blocks, about the who, the how and the what for, with each block being contextualized, before the specific presentations, by SEDIA's Data Office and grounded in practice by the Government of Navarra. 

1. The first thematic block was "The data ecosystem: who". It addressed some of the strategies around data from the Generalitat de Catalunya and from the Basque Government.  

2. This was followed by presentations in a second block entitled "Governance model, ethics and culture: how". The governments of Aragon, Andalusia, the Canary Islands, Valencia and the Spanish Federation of Municipalities and Provinces made presentations of their success stories in this area.  

3. In a final block entitled "Citizen service, innovation and data spaces: what for", presentations were given by Andalusia, the National Institute of Statistics, Castilla-la Mancha and the General Secretariat of Digital Administration, and Red.es, the latter presenting the services offered to the autonomous communities from the datos.gob.es platform. 

Seven key principles to drive the data economy forward  

 The meeting culminated with the presentation of seven principles to advance the joint formulation of strategies and policies related to data management and the digital future. These are:  

• Establish effective data governance by setting policies, standards and procedures for the effective management, exploitation and sharing of data, while implementing controls and evaluations to ensure compliance.  

• Perform an ethical treatment of data, assessing the lawfulness and legitimacy of all data practices, seeking to minimize any adverse impact on individuals and society. 

• Prioritize reliable administrative processing centered on data, prioritizing the transition from document to data, capable of enabling and catalyzing the use of advanced technologies and tools for descriptive, predictive and prescriptive analytics (BI, big data, machine learning, deep learning), generative algorithms (LLM, GPT) and process automation (RPA).  

• Deployment of sovereign data sharing as a resource whose value increases with its dissemination, establishing who can access what data and under what conditions of use, security and trust.  

• Encourage the open dissemination of information, promoting its effective reuse and publication in accordance with FAIR principles, i.e., ensuring that data is findable, accessible, interoperable and reusable.  

• Designing and analyzing public policies based on evidence, in order to make informed decisions that lead to effective services and public innovation.   

• Fostering data culture, promoting the creation of new profiles, positions and responsibilities related to working with data, without neglecting the training and transmission of knowledge around data. 

The success of the participation, the interventions and reflections raised show the consensus on advancing towards the achievement of a data-oriented Administration, capable of taking advantage, through the use of innovative technological means, of the potential of data, enabling the design, implementation and evaluation of public policies focused on the citizen, generating a data-oriented, sustainable, inclusive and social value-generating economy.   

The Forum has thus become a meeting point and a place to generate synergies between the different public administrations. Interoperability between the various public sector agencies and between the different levels of government in the processing and exchange of information boosts territorial cohesion and enables the effective use of available technologies in the quest to satisfy the common good.

The Canary Islands Statistics Institute (ISTAC) has added  more than 500 semantic assets and more than 2100 statistical cubes to its catalogue.

This vast amount of information represents decades of work by the ISTAC in standardisation and adaptation to leading international standards, enabling better sharing of data and metadata between national and international information producers and consumers.

The increase in datasets not only quantitatively improves the directory at datos.canarias.es and datos.gob.es, but also broadens the uses it offers due to the type of information added.

New semantic assets

Semantic resources, unlike statistical resources, do not present measurable numerical data , such as unemployment data or GDP, but provide homogeneity and reproducibility.

These assets represent a step forward in interoperability, as provided for both at national level with the National Interoperability Scheme ( Article 10, semantic assets) and at European level with the European Interoperability Framework (Article 3.4, semantic interoperability). Both documents outline the need and value of using common resources for information exchange, a maxim that is being pursued at implementing in a transversal way in the Canary Islands Government. These semantic assets are already being used in the forms of the electronic headquarters and it is expected that in the future they will be the semantic assets used by the entire Canary Islands Government.

Specifically in this data load there are 4 types of semantic assets:

• Classifications (408 loaded): Lists of codes that are used to represent the concepts associated with variables or categories that are part of standardised datasets, such as the National Classification of Economic Activities (CNAE), country classifications such as M49, or gender and age classifications.
• Concept outlines (115 uploaded): Concepts are the definitions of the variables into which the data are disaggregated and which are finally represented by one or more classifications. They can be cross-sectional such as "Age", "Place of birth" and "Business activity" or specific to each statistical operation such as "Type of household chores" or "Consumer confidence index".
• Topic outlines (2 uploaded): They incorporate lists of topics that may correspond to the thematic classification of statistical operations or to the INSPIRE topic register.
• Schemes of organisations (6 uploaded): This includes outlines of entities such as organisational units, universities, maintaining agencies or data providers.

All these types of resources are part of the international SDMX (Statistical Data and Metadata Exchange) standard, which is used for the exchange of statistical data and metadata. The SDMX provides a common format and structure to facilitate interoperability between different organisations producing, publishing and using statistical data.

The Canary Islands Statistics Institute (ISTAC) has added  more than 500 semantic assets and more than 2100 statistical cubes to its catalogue.

This vast amount of information represents decades of work by the ISTAC in standardisation and adaptation to leading international standards, enabling better sharing of data and metadata between national and international information producers and consumers.

The increase in datasets not only quantitatively improves the directory at datos.canarias.es and datos.gob.es, but also broadens the uses it offers due to the type of information added.

New semantic assets

Semantic resources, unlike statistical resources, do not present measurable numerical data , such as unemployment data or GDP, but provide homogeneity and reproducibility.

These assets represent a step forward in interoperability, as provided for both at national level with the National Interoperability Scheme ( Article 10, semantic assets) and at European level with the European Interoperability Framework (Article 3.4, semantic interoperability). Both documents outline the need and value of using common resources for information exchange, a maxim that is being pursued at implementing in a transversal way in the Canary Islands Government. These semantic assets are already being used in the forms of the electronic headquarters and it is expected that in the future they will be the semantic assets used by the entire Canary Islands Government.

Specifically in this data load there are 4 types of semantic assets:

• Classifications (408 loaded): Lists of codes that are used to represent the concepts associated with variables or categories that are part of standardised datasets, such as the National Classification of Economic Activities (CNAE), country classifications such as M49, or gender and age classifications.
• Concept outlines (115 uploaded): Concepts are the definitions of the variables into which the data are disaggregated and which are finally represented by one or more classifications. They can be cross-sectional such as "Age", "Place of birth" and "Business activity" or specific to each statistical operation such as "Type of household chores" or "Consumer confidence index".
• Topic outlines (2 uploaded): They incorporate lists of topics that may correspond to the thematic classification of statistical operations or to the INSPIRE topic register.
• Schemes of organisations (6 uploaded): This includes outlines of entities such as organisational units, universities, maintaining agencies or data providers.

All these types of resources are part of the international SDMX (Statistical Data and Metadata Exchange) standard, which is used for the exchange of statistical data and metadata. The SDMX provides a common format and structure to facilitate interoperability between different organisations producing, publishing and using statistical data.

On 20 October, Madrid hosted a new edition of the Data Management Summit Spain, an international summit that this year also took place in Italy (7 July) and Latam (20 September). The event brought together CiOs, CTOs, CDOs, Business Intelligence Officers and Data Scientists in charge of implementing emerging technologies in order to solve new technological challenges aligned with new business opportunities.

This event was preceded by a prologue held the previous evening, in collaboration with DAMA Spain and the Data Office. This was a session aimed exclusively at representatives of different levels of public administration and focused on open data and information sharing between administrations. During the day, participants discussed the transformative role of data and how its intensive use and enhancement are essential to achieve the digital transformation of public administrations.

As was mentioned in the session, data plays an essential role in the development of disruptive technologies such as Artificial Intelligence, and is a differential factor when it comes to launching an industrial and technological revolution that allows for the consolidation of a fairer, more inclusive digital economy in line with the SDGs and the 2030 Agenda. A true data economy with the vocation to nurture the development of two key and strategic processes for the reconstruction of our country: the digital transformation and the ecological transition.

Data spaces and open data, key to achieving data-driven government

The institutional opening was given by Carlos Alonso, Director of the Data Office Division. His speech focused on highlighting how the achievement of a data-oriented administration, an inseparable part of its digital transformation process, depends on the development of public sector data spaces, which enable data sharing with sovereignty and its large-scale exploitation. Data is a public good, to be preserved and processed in order to implement quality public services and policies. The aim is to achieve a data-driven, citizen-centred, open, transparent, inclusive, participatory and egalitarian administration, ensuring ethical, secure and responsible use of data.

In this process of designing public and private sector data spaces, open data is fundamental, as Carlos Alonso highlighted during his speech: "Data spaces are major consumers and generators of open data, and their availability must be ensured. That is, it is necessary to establish certain service level agreements to ensure access".

Sharing experiences between administrations

After this institutional opening, the conference addressed the opportunity provided by the creation of spaces for sharing and exploiting data in public administrations, and allowed for the dissemination of different data-related projects by representatives of the different administrative levels, including autonomous communities and local entities.

Andreu Francisco, Director General of the Localret consortium, formed by the local administrations of Catalonia for the development of telecommunications services and networks and the application of ICT, presented a digital metamodel, which aims to structure the technological architecture and services required in a digital city. It is a comprehensive solution that can be implemented in different territories and personalised according to the singularities of each city, making it easier for the inhabitants of the 877 Catalan municipalities to develop professionally and personally.

César Priol, Director General of Digitalisation and Citizen Services, of Bizkaiko Foru Aldundia (Basque Country) shared his experience in the creation of the Data Office, highlighting the importance of self-organising on an organisational, regulatory and legal level in order to have the capacity to transform not only the organisation, but also the territory with data.

Magda Lorente, Head of the Local Information Systems Assistance Section, and Sara Aguilar, Head of the Service of the Official Gazette of the Province of Barcelona and other Official Publications of the Barcelona Provincial Council, spoke of good practices in data management. Magda Lorente highlighted the importance of the Diputacions becoming data-oriented in order to assume their relevant role in the promotion of municipal data governance. According to a study carried out by the Diputació de Barcelona, which will be published at the end of November, 85% of municipalities could be left out of artificial intelligence and intelligent administration because their technical capacities do not allow them to materialise the necessary data orientation.

Sara Aguilar, for her part, presented an example of how the administrations are consolidating the way in decision-making based on quality data: the CIDO, a search engine for official information and documentation. This tool was created in 2000 with the aim of bringing government information closer to citizens in a user-friendly way. It provides access, for example, to more than 2,600 selection processes with open calls for applications and 1,600 open subsidies, thanks to the open data offered by the different municipalities of Catalonia. CIDO is based on a tag reader model and the use of artificial intelligence algorithms, which classify the information collected from the municipalities. They have more than 2 million ads, structured and documented open data that they serve through an API that can be integrated into any platform.

Roundtables and group dynamics to promote debate

During the course of the day, attendees were able to participate in different dynamics for the exchange of experiences. The first dynamic focused on open data and the second on interoperability.

In addition, two round tables were held, which allowed the subject to be approached from different points of view:

• The first round table, moderated by Carlos Alonso, focused on the challenges and barriers to data exchange in the public sector. Current methodologies, specifications and practices related to the processing of information, in order to achieve a fluid and continuous exchange of data between administrations, industrial sectors and citizens, were projected on a larger scale. The round table was attended by: Carlos Alonso, Jose Antonio Eusamio (General Secretariat for Digital Government), César Priol (Vizcaya Provincial Council), Miguel Angel Martinez Vidal (INE) and Magda Lorente.
• The second round table focused on how to accelerate the adoption of Open Linked Data in the public administration domain, moderated in this case by Oscar Alonso (IBM Consulting & DAMA Spain). Participants included Sara Aguilar (Barcelona Provincial Council), Oscar Alonso (DAMA Spain & IBM), Sonia Castro (datos.gob.es), Juan José Alonso (Orange) and Olga Quiros (ASEDIE). The conversation revolved around EU initiatives, such as the Data Governance Act, which are acting as a turning point in data policies. The act seeks to establish robust mechanisms to facilitate the re-use of certain categories of protected public sector data, increase trust in data brokering services and promote data altruism across the EU. This highlights how the EU is working to strengthen various data sharing mechanisms to promote the availability of data that can be used to drive advanced applications and solutions in artificial intelligence, personalised medicine, green mobility, smart manufacturing and many other areas. The importance of data ethics was also highlighted during the debate.

Materials available on the day

If you missed the session, the video is available on Youtube. The recording of the summit on the 20th has also been made public, a session that had a more business-oriented approach, with expert presentations and group dynamics focused on data governance, data quality, master data and data architecture, among other topics. Photos from the event are also available.

In addition, interviews with some of the speakers have been published on the summit's website, allowing a deeper insight into the projects they are carrying out.

The European Data Strategy aims to create a single market where data flows between countries and sectors. In this respect, the public sector holds a large amount of data of value to citizens. Much of this data are made openly available through various open data platforms, but there are also data over which third party rights apply, limiting its openness. These data can also be of great interest for scientific research purposes.

The existence of numerous administrative registers and public databases, as well as the evolution of the technologies that allow their management, have led to the availability of large amounts of information in all areas that can be used for the benefit of society, increasing the demand for access by researchers.

In this regard, on 3 June, the Data Governance Act was published in the Official Journal of the European Union. This Act seeks to encourage data sharing in the EU, promoting the so-called Data Economy. Among other issues, the new act contemplates the need to develop mechanisms that facilitate the reuse of this type of data, over which third party rights apply, with all the legal guarantees.

One of these mechanisms are the so-called Safe Reading Rooms, mentioned during the impact assessment prior to the approval of the Act.

What are Safe Rooms?

Safe Rooms are conceived as a single point of contact to support researchers in the re-use of certain protected categories of data held by the public sector. They allow for a controlled processing of the data, while preserving privacy or other rights attached to the data.

In Europe there are various initiatives of this type, such as the CASD (Centre d’Accès Sécurisé aux Données) and the Health Data Hub in France or the Microdata Research Laboratory in Portugal.  In Spain we also have several organisations that have already made Safe Reading Rooms available to researchers.  Let's look at 3 examples.

3 examples of Safe Rooms for data sharing in Spain

Bank of Spain Data Laboratory (BELab)

The Banco de España facilitates access to high-quality microdata, guaranteeing its confidentiality through Secure Rooms. Some of the data it offers are microdata from individual companies of Fintech entities or from the Financial Skills Survey.

Users can access the information both on-site (in Madrid and Barcelona) and remotely, depending on the degree of sensitivity of the information under study. The on-site lab stations, which are isolated without internet access, use Stata, R, Python and Octave for data processing.

To gain access, researchers must submit their CV and an application form explaining the purpose of the research. This application is assessed by a Research Technical Evaluation Committee. If accepted, a series of rules and restrictions are set (timetable, access without a mobile device, etc.).

To guarantee the proper use of the microdata, BELab prepares and supplies the methodological documentation. In addition, technical experts review the work to ensure compliance with the corresponding confidentiality clauses.

Once the work has been completed, the researcher is obliged to mention the source of the data and send a copy of the study carried out. He/she also undertakes not to make any attempt to re-identify the natural or legal persons linked to the data under study.

Social Security Investigation Chambers

Researchers and academics interested in Social Security databases and microdata have at their disposal three Secure Rooms in Madrid, Barcelona and Albacete, which can only be accessed by authorised personnel, without electronic devices. These rooms are equipped with tools such as SAS, STATA, R, Python and Microsoft Office. Remote access is also allowed through secure devices (called "bastioned devices") that are distributed among researchers.

Some of the data available are the Continuous Sample of Working Lives, the Monthly Affiliation or the ERTEs by COVID-19, among others.

As in the case of the Bank of Spain, the interested party will have to send a request by e-mail to solicitudes.sala-investigacion@seg-social.es. A Committee of Experts will evaluate the request. If approved, the necessary data will be prepared, access to which will be allowed through a private personal folder.

The Committee of Experts will also evaluate the outcome of the research, to ensure regulatory compliance. If everything is correct, the study will be published on the Social Security Data Portal.

National Statistics Institute (INE)

The National Statistical Institute is one of the main publishers of open data in our country, but it also holds sensitive data of value that must be treated with the corresponding confidentiality measures. Access to this information for scientific research purposes follows the protocol foreseen in Regulation (EC) No 223/2009 on European Statistics and in the European Statistics Code of Practice.

This service is intended for researchers working or collaborating in recognised research organisations. The process is similar to the previous cases. An application must be submitted, which will be evaluated by the INE. This request must be as detailed as possible, indicating the variables to be consulted, the geographical-temporal level and the justification of the need for this information. Some of these data may incur costs, as established in the Official State Gazette.

These three examples illustrate the importance of Safe Rooms in enabling the reuse of valuable data while guaranteeing the confidentiality and privacy of the information. This allows for more in-depth research, which can generate economic and social good. An intensive use of data allows to boost innovation in public sector performance, facilitating the contrast of ideas, promoting creativity and the maximum use of resources in the general framework of a modern, participative, open and useful public management to solve or improve social problems and challenges.

In the current context, digitalisation has expanded exponentially, reaching beyond the boundaries of the private sector and consolidating itself as one of the great challenges in all productive sectors of society. This process has brought with it the massive generation of data from which to extract value. However, according to an IDC/EMC study, it is believed that, despite the fact that the volume of data will multiply exponentially in the short term, only 1% of the data generated is used, processed and exploited. One of the reasons for this lies in the inconsistency and inflexibility of data models, which block data integration.

In this regard, the Spanish government's Recovery, Transformation and Resilience Plan, which details Spain's strategy for channelling EU funds to repair the damage caused by the pandemic, emphasises technological reforms and investments focused on building a more sustainable future. One of the main challenges in this area is to boost data sharing, mainly in those sectors with the greatest impact on society, such as health and tourism.

To this end, smart data models play a fundamental role. But what exactly are they?

visión común que proporciona una base técnica para lograr la apertura de la innovación.

What are Smart Data Models?

A traditional data model is a representation of the elements of a dataset and their relationships and connections to each other. Smart Data Models go one step further. They are common and compatible data models, with the objective of supporting a digital marketplace of interoperable and replicable smart solutions across multiple sectors, so that the availability of data in specific domains is homogenised.

These models propose a common vision that provides a technical basis for unlocking innovation.

SDM Initiative

The FIWARE Foundation, TM Forum, IUDX and OASC have joined forces to lead a joint collaborative initiative to bring together intelligent data models by domains, making them available to organisations and any user who wants them. This is known as the SDM (Smart data models) initiative, in which all data models are public.

In this way, it responds to the new data modelling needs at the speed required by the market, reusing models that have already been tested in real scenarios.

How does it work?

The fundamental objective of SDM is that organisations can evolve their vision of data exchange towards a sharing that supports both the so-called Data Economy and the data spaces.

The Data Economy is nothing more than the set of activities and initiatives whose business model is based on the discovery and exploitation of data to identify opportunities that generate products and services.

SDM classifies information by domains or industrial sectors, creating a repository for each of them. In addition, each domain contains sub-modules with the relevant topics for that domain and, within each topic, the related data models. However, shared cross-cutting elements are also available for all domains. For each of these repositories, models can be extracted free of charge. It is also possible to contribute to the initiative by filling in a collaboration form to create new ones.

To facilitate sharing and common understanding, each model includes three elements:

• The model's technical representation that defines the data and its relationships, using JSON structures.
• The specification or manual with the functional descriptions of each of the elements contained in the model.
• Examples to ensure understanding.

In addition to its public nature and free use, it has a licence that allows users to make modifications if they consider it necessary, as well as to share these modifications with the rest of the users. To this end, a workflow is defined according to the phases of the life cycle of the data models, which presents three stages:

• Official: the data models have already been accepted and are fully available to users with the three elements described above.
• In harmonisation: the models have already been accepted, but are still in progress to complete the elements.
• In incubation: the models are being developed and supported by the organisation to achieve an official model.

Through this initiative, data models sharing at all levels will be made more dynamic. For the moment, models have already been homogenised in the domains of smart cities, the agri-food sector, water treatment, energy, environment, sensor technology, robotics, aeronautics, tourist destinations, health and manufacturing industry, as well as some transversal ones such as social media or incident monitoring, although not all to the same extent, as shown in the following image with the number of models included in each domain.

It is, without a doubt, an initiative that facilitates the path towards the data-driven transformation of products and services, providing the opening of models as the technical basis on which the adoption of reference architectures will be based. If you want to go deeper, the SDM itself contains a "Learning zone" section to facilitate learning about the initiative and encourage its use, including self-explanatory videos.

There is also a whole series of tools for those users who, although experts in their sector of activity, are not experts in the generation of data models. Under the tools menu item, there are services that allow users to generate a draft data model with an example, an assisted online data model editor, options to generate examples from existing data models, and options to incorporate the @context element that allows connection to linked data solutions.

Global initiatives such as SDM are of great importance when it comes to agreeing benchmarks to optimise citizen services. They constitute a further step in the objective of achieving common data spaces, making available contrasted data models. This milestone is a major accelerator for its transcendence, even at European level, with major initiatives already underway, such as GAIA-X.

Content prepared by Juan Mañes, expert in Data Governance, with contributions from the Data Office.

The contents and views expressed in this publication are the sole responsibility of the author.

Data are fundamental to solving the social and economic challenges we face today. It allows us to understand the causes behind a given situation and the factors that influence it, to estimate how it is evolving and to make informed decisions for change.

The problem is that solving such challenges often requires a combination of data from different sources:

•     Data provided by the public sector
•     Data from multiple private sector companies
•     Citizen-generated data

But how can such collaboration be achieved? This is the question posed in the report "How to facilitate data collaboration to solve societal problems", written by Jose Luis Marín in the framework of the Aporta Initiative.

The report begins with a brief introduction outlining the current state of data openness in the public and private sectors, as well as in the citizenry. Then, it discusses the main barriers to data sharing by companies and citizens, the individual and collective benefits that can motivate these practices in the public interest, and the policies that can be put in place by public administrations to compensate and encourage collaboration.

Once the context is clear, it is time to look at some of the existing mechanisms for collaboration in data collection, sharing or processing to address a societal challenge. Although there are no systematised analyses of ideal forms of governance, four formulas have been identified for this report:

In order to illustrate and better understand each formula, the report includes multiple examples of international success stories, such as the Accelerating Medicines Partnership (AMP), which focuses on transforming the current model of developing new diagnostics and treatments, or the Open Apparel Registry (OAR), which aims to contribute to improving human rights and environmental conditions around factories.

The report concludes with a series of resources to help organisations collaborate successfully and reduce barriers, including collaboration networks, collaboration frameworks, courses and trainings.

Below, you can download the report, as well as access the complementary materials (executive summary, video-interview and summary presentation). The report is translated into English, but additional materials are available in Spanish version only.

In the framework of european data strategy, one of the issues on which the European Commission is working is to facilitate the exchange of data held by companies with the administrations to improve public services and guide policy decisions. According to the Commission's own definition, theB2G data exchange it is a collaboration in which a company or other private organization makes its data (or knowledge) available to the public sector (local, regional, national or EU) for a purpose of public interest.

In order to obtain legal advice, identify good practices and collect recommendations for its policies, in 2018, the European Commission appointed a group of high-level independent experts with experience in the public and private sector in the field of B2G data exchange. The conclusions and recommendations of the group to the Commission were included in a report final which has been used to advise possible Commission initiatives on this matter.

The report recognizes that much of the potential of data and knowledge, so that they can be used for the benefit of society, still unexploded. Organizational, technical, and legal obstacles, as well as a general lack of a data-sharing culture, are among the causes that make most current collaborations ad hoc. The report provides a detailed description of the barriers to collaboration and proposes a comprehensive framework of policy, legal, and funding recommendations to enable scalable, responsible, and sustainable B2G data sharing in the public interest. A good number of examples of European B2G collaborations that have been used in the analysis methodology and that are generally little known even to the most specialized public are also included.

The most interesting part perhaps lies in the key recommendations that are made to the European Commission and a Member States to consider data as critical public infrastructure for the future of the EU and take action accordingly to facilitate the use of private data for the public interest.

These recommendations are structured in three main categories that refer to the governance of exchanges, the transparency of said exchanges and the tools that facilitate exchanges. Specific measures are suggested for each of them.

Governance of B2G data exchange across the EU

The first recommendation made by the report is that all Member States establish governance structures that can monitor and provide advice on responsible B2G data sharing practices. Additionally, and in order to support this idea, it is recommended that private, public and civil society organizations promote the function of data administrator and that the European Commission encourage the creation of a network of such data managers, as a community of practice in the field.

Recommendations are also made regarding the application of reference conditions (including, in some cases, free conditions) applicable to the acquisition of privately owned data for purposes of public interest in accordance with the B2G data exchange principles.

Transparency, citizen participation and ethics in the exchange of B2G data

The first recommendation in this category is that B2G data collaborations between public, private, and civil society organizations should be transparent, including regarding the data used and the impact of the collaborations.

The recommendations also focus on the need for Member States and the European Commission to raise citizens' public awareness of the societal benefits of data (for example, by initiating data literacy programs) and to involve the general public in the choice of societal challenges to be addressed. This line of action calls on Member States to promote user-friendly data donation mechanisms and encourage the general public to share your data for the public interest purposes of your choice. In this sense, his own EU data portal acknowledges in a recently published report the enormous gaps, as well as the great opportunities, in relation to the publication of data generated by citizens.

The experts do not forget to remind the European Commission of the need to develop ethical guidelines on the use of data, including for the public interest and, where appropriate, taking into account the European Union Ethical Guidelines for Artificial Intelligence.

Finally, Member States are asked to invest in the training, education and up-skilling of policy makers and public sector workers to increase the readiness and operational capacity of the public sector to use and act on data.

Operating models, structures and technical tools to facilitate data exchange

Experts propose that the European Commission and Member States put in place incentives for B2G data sharing and mechanisms that ensure public recognition of private companies and civil society organizations involved in B2G data sharing.

Experts consider the programs of the new financial framework 2021-2027 and in particular the Digital Europe Program and the Horizon Europe Program as key pieces to implement the recommendations. Firstly, to finance the development and deployment of technologies (privacy preservation, security technologies and access control technologies) that favor B2G data exchange at scale and in a responsible and sustainable manner. But also, to promote the creation of a light governance structure that prioritizes standards that allow reducing the transaction costs of B2G data exchange and guaranteeing interoperability.

Finally, the European Commission is asked to carry out studies to obtain further empirical evidence of the macroeconomic and social benefits of B2G data sharing for the public interest.

In short, the EU seems determined to promote B2G collaborations by creating a common framework that allows the development of fast, responsible and sustainable B2G data exchange. And the list of areas in which the exchange of B2G data can have a great impact on the lives of citizens is endless: making health services be more efficient, improve the diagnosis of diseases in the population, react faster in emergencies and natural or humanitarian disasters, allow public research institutes access to data for the development of ethical artificial intelligence services, save energy for a more sustainable society, improve mobility, develop smarter cities, etc.

Content written by Jose Luis Marín, Senior Consultant in Data, Strategy, Innovation & Digitalization.

The contents and views reflected in this publication are the sole responsibility of the author.