Empleo

The open data sector is very active. To keep up to date with everything that happens, from datos.gob.es we publish a compilation of news such as the development of new technological applications, legislative advances or other related news.

Six months ago, we already made the last compilation of the year 2024. On this occasion, we are going to summarize some innovations, improvements and achievements of the first half of 2025.

Regulatory framework: new regulations that transform the landscape

One of the most significant developments is the publication of the Regulation on the European Health Data Space by the European Parliament and the Council. This regulation establishes a common framework for the secure exchange of health data between member states, facilitating both medical research and the provision of cross-border health services. In addition, this milestone represents a paradigmatic shift in the management of sensitive data, demonstrating that  it is possible to reconcile privacy and data protection with the need to share information for the common good. The implications for the Spanish healthcare system are considerable, as it will allow greater interoperability with other European countries and facilitate the development of collaborative research projects.

On the other hand, the entry into force of the European AI Act establishes clear rules for the development of this technology, guaranteeing security, transparency and respect for human rights. These types of regulations are especially relevant in the context of open data, where algorithmic transparency and the explainability of AI models become essential requirements.

In Spain, the commitment to transparency is materialised in initiatives such as the new Digital Rights Observatory, which has the participation of more than 150 entities and 360 experts. This platform is configured as a space for dialogue and monitoring of digital policies, helping to ensure that the digital transformation respects fundamental rights.

Technological innovations in Spain and abroad

One of the most prominent milestones in the technological field is the launch of ALIA, the public infrastructure for artificial intelligence resources. This initiative seeks to develop open and transparent language models that promote the use of Spanish and Spanish co-official languages in the field of AI.

ALIA is not only a response to the hegemony of Anglo-Saxon models, but also a strategic commitment to technological sovereignty and linguistic diversity. The first models already available have been trained in Spanish, Catalan, Galician, Valencian and Basque, setting an important precedent in the development of inclusive and culturally sensitive technologies.

In relation to this innovation, the practical applications of artificial intelligence are multiplying in various sectors. For example, in the financial field, the Tax Agency has adopted an ethical commitment in the design and use of artificial intelligence. Within this framework, the community has even developed a virtual chatbot trained with its own data that offers legal guidance on fiscal and tax issues.

In the healthcare sector, a group of Spanish radiologists is working on a project for the early detection of oncological lesions using AI, demonstrating how the combination of open data and advanced algorithms can have a direct impact on public health.

Also combining AI with open data, projects related to environmental sustainability have been developed. This model developed in Spain combines AI and open weather data to predict solar energy production over the next 30 years, providing crucial information for national energy planning.

Another relevant sector in terms of technological innovation is that of smart cities. In recent months, Las Palmas de Gran Canaria has digitized its municipal markets by combining WiFi networks, IoT devices, a digital twin and open data platforms. This comprehensive initiative seeks to improve the user experience and optimize commercial management, demonstrating how technological convergence can transform traditional urban spaces.

Zaragoza, for its part, has developed a vulnerability map using artificial intelligence applied to open data, providing a valuable tool for urban planning and social policies.

Another relevant case is the project of the Open Data Barcelona Initiative, #iCuida, which stands out as an innovative example of reusing open data to improve the lives of caregivers and domestic workers. This application demonstrates how open data can target specific groups and generate direct social impact.

Last but not least, at a global level, this semester DeepSeek has launched DeepSeek-R1, a new family of generative models specialized in reasoning, publishing both the models and their complete training methodology in open source, contributing to the democratic advancement of AI.

New open data portals and improvement tools

In all this maelstrom of innovation and technology, the landscape of open data portals has been enriched with new sectoral initiatives. The Association of Commercial and Property Registrars of Spain has presented its open data platform, allowing immediate access to registry data without waiting for periodic reports. This initiative represents a significant change in the transparency of the registry sector.

In the field of health, the 'I+Health' portal of the Andalusian public health system collects and disseminates resources and data on research activities and results from a single site, facilitating access to relevant scientific information.

In addition to the availability of data, there is a treatment that makes them more accessible to the general public: data visualization. The University of Granada has developed 'UGR in figures', an open-access space with an open data section that facilitates the exploration of official statistics and stands as a fundamental piece in university transparency.

On the other hand, IDENA, the new tool of the Navarre Geoportal, incorporates advanced functionalities to search, navigate, incorporate maps, share data and download geographical information, being operational on any device.

Training for the future: events and conferences

The training ecosystem in this ecosystem is strengthened every year with events such as the Data Management Summit in Tenerife, which addresses interoperability in public administrations and artificial intelligence. Another benchmark event in open data that was also held in the Canary Islands was the National Open Data Meeting.

Beyond these events, collaborative innovation has also been promoted through  specialized hackathons, such as the one dedicated to generative AI solutions for biodiversity or the Merkle Datathon in Gijón. These events not only generate innovative solutions, but also create communities of practice and foster emerging talent.

Once again, the open data competitions of Castilla y León and the Basque Country have awarded projects that demonstrate the transformative potential of the reuse of open data, inspiring new initiatives and applications.

International perspective and global trends: the fourth wave of open data

The Open Data Policy Lab spoke at the EU Open Data Days about what is known as the "fourth wave" of open data, closely linked to generative AI. This evolution represents a quantum leap in the way public data is processed, analyzed, and used, where natural language models allow for more intuitive interactions and more sophisticated analysis.

Overall, the open data landscape in 2025 reveals a profound transformation of the ecosystem, where the convergence between artificial intelligence, advanced regulatory frameworks, and specialized applications is redefining the possibilities of transparency and public innovation.

Data science is all the rage. Professions related to this field are among the most in-demand, according to the latest study ‘Posiciones y competencias más Demandadas 2024’, carried out by the Spanish Association of Human Resources Managers. In particular, there is a significant demand for roles related to data management and analysis, such as Data Analyst, Data Engineer and Data Scientist. The rise of artificial intelligence (AI) and the need to make data-driven decisions are driving the integration of this type of professionals in all sectors.

Universities are aware of this situation and therefore offer a large number of degrees, postgraduate courses and also summer courses, both for beginners and for those who want to broaden their knowledge and explore new technological trends. Here are just a few examples of some of them. These courses combine theory and practice, allowing you to discover the potential of data.

1. Data Analysis and Visualisation: Practical Statistics with R and Artificial Intelligence. National University of Distance Education (UNED).

This seminar offers comprehensive training in data analysis with a practical approach. Students will learn to use the R language and the RStudio environment, with a focus on visualisation, statistical inference and its use in artificial intelligence systems. It is aimed at students from related fields and professionals from various sectors (such as education, business, health, engineering or social sciences) who need to apply statistical and AI techniques, as well as researchers and academics who need to process and visualise data.

• Date and place: from 25 to 27 June 2025 in online and face-to-face mode (in Plasencia).

2. Big Data. Data analysis and automatic learning with Python. Complutense University.

Thanks to this training, students will be able to acquire a deep understanding of how data is obtained, managed and analysed to generate valuable knowledge for decision making. Among other issues, the life cycle of a Big Data project will be shown, including a specific module on open data. In this case, the language chosen for the training will be Python. No previous knowledge is required to attend: it is open to university students, teachers, researchers and professionals from any sector with an interest in the subject.

• Date and place: 30 June to 18 July 2025 in Madrid.

3. Challenges in Data Science: Big Data, Biostatistics, Artificial Intelligence and Communications. University of Valencia.

This programme is designed to help participants understand the scope of the data-driven revolution. Integrated within the Erasmus mobility programmes, it combines lectures, group work and an experimental lab session, all in English. Among other topics, open data, open source tools, Big Data databases, cloud computing, privacy and security of institutional data, text mining and visualisation will be discussed.

• Date and place: From 30 June to 4 July at two venues in Valencia. Note: Places are currently full, but the waiting list is open.

4. Digital twins: from simulation to intelligent reality. University of Castilla-La Mancha.

Digital twins are a fundamental tool for driving data-driven decision-making. With this course, students will be able to understand the applications and challenges of this technology in various industrial and technological sectors. Artificial intelligence applied to digital twins, high performance computing (HPC) and digital model validation and verification, among others, will be discussed. It is aimed at professionals, researchers, academics and students interested in the subject.

• Date and place: 3 and 4 July in Albacete.

5. Health Geography and Geographic Information Systems: practical applications. University of Zaragoza.

The differential aspect of this course is that it is designed for those students who are looking for a practical approach to data science in a specific sector such as health. It aims to provide theoretical and practical knowledge about the relationship between geography and health. Students will learn how to use Geographic Information Systems (GIS) to analyse and represent disease prevalence data. It is open to different audiences (from students or people working in public institutions and health centres, to neighbourhood associations or non-profit organisations linked to health issues) and does not require a university degree.

• Date and place: 7-9 July 2025 in Zaragoza.

6. Deep into data science. University of Cantabria.

Aimed at scientists, university students (from second year onwards) in engineering, mathematics, physics and computer science, this intensive course aims to provide a complete and practical vision of the current digital revolution. Students will learn about Python programming tools, machine learning, artificial intelligence, neural networks or cloud computing, among other topics. All topics are introduced theoretically and then experimented with in laboratory practice.

• Date and place: from 7 to 11 July 2025 in Camargo.

7. Advanced Programming. Autonomous University of Barcelona.

Taught entirely in English, the aim of this course is to improve students' programming skills and knowledge through practice. To do so, two games will be developed in two different languages, Java and Python. Students will be able to structure an application and program complex algorithms. It is aimed at students of any degree (mathematics, physics, engineering, chemistry, etc.) who have already started programming and want to improve their knowledge and skills.

• Date and place: 14 July to 1 August 2025, at a location to be defined.

8. Data visualisation and analysis with R. Universidade de Santiago de Compostela.

This course is aimed at beginners in the subject. It will cover the basic functionalities of R with the aim that students acquire the necessary skills to develop descriptive and inferential statistical analysis (estimation, contrasts and predictions). Search and help tools will also be introduced so that students can learn how to use them independently.

• Date and place: from 14 to 24 July 2025 in Santiago de Compostela.

9. Fundamentals of artificial intelligence: generative models and advanced applications. International University of Andalusia.

This course offers a practical introduction to artificial intelligence and its main applications. It covers concepts related to machine learning, neural networks, natural language processing, generative AI and intelligent agents.  The language used will be Python, and although the course is introductory, it will be best used if the student has a basic knowledge of programming. It is therefore aimed primarily at undergraduate and postgraduate students in technical areas such as engineering, computer science or mathematics, professionals seeking to acquire AI skills to apply in their industries, and teachers and researchers interested in updating their knowledge of the state of the art in AI.

• Date and place: 19-22 August 2025, in Baeza.

10. IA Generative AI to innovate in the company: real cases and tools for its implementation. University of the Basque Country.

This course, open to the general public, aims to help understand the impact of generative AI in different sectors and its role in digital transformation through the exploration of real cases of application in companies and technology centres in the Basque Country.  This will combine talks, panel discussions and a practical session focused on the use of generative models and techniques such as Retrieval-Augmented Generation (RAG) and Fine-Tuning.

• Date and place: 10 September in San Sebastian.

Investing in technology training during the summer is not only an excellent way to strengthen skills, but also to connect with experts, share ideas and discover opportunities for innovation. This selection is just a small sample of what's on offer. If you know of any other courses you would like to share with us, please leave a comment or write to dinamizacion@datos.gob.es

Data reuse continues to grow in Spain, as confirmed by the last report of the Multisectorial Association of Information (ASEDIE), which analyses and describes the situation of the infomediary sector in the country. The document, now in its 13th edition, was presented last Friday, 4 April, at an event highlighting the rise of the data economy in the current landscape.

The following are the main key points of the report.

An overall profit of 146 million euros in 2023

Since 2013, ASEDIE's Infomediary sector report has been continuously monitoring this sector, made up of companies and organisations that reuse data - generally from the public sector, but also from private sources - to generate value-added products or services.  Under the title "Data Economy in its infomediary scope", this year's report underlines the importance of public-private partnerships in driving the data economy and presents relevant data on the current state of the sector.

It should be noted that the financial information used for sales and employees corresponds to the financial year 2023, as financial information for the year 2024 was not yet available at the time of reporting. The main conclusions are:

• Since the first edition of the report, the number of infomediaries identified has risen from 444 to 757, an increase of 70%. This growth reflects its dynamism, with annual peaks and troughs, showing a positive evolution that consolidates its recovery after the pandemic, although there is still room for development.
• The sector is present in all the country's Autonomous Communities, including the Autonomous City of Melilla. The Community of Madrid leads the ranking with 38% of infomediaries, followed by Catalonia, Andalusia and the Community of Valencia, which represent 15%, 11% and 9%, respectively. The remaining 27% is distributed among the other autonomous communities.
• 75% of infomediary companies operate in the sub-sectors of geographic information, market, economic and financial studies, and infomediation informatics (focused on the development of technological solutions for the management, analysis, processing and visualisation of data).
• The infomediary sector shows a growth and consolidation trend, with 66% of companies operating for less than 20 years. Of this group, 32% are between 11 and 20 years old, while 34% are less than a decade old. Furthermore, the increase in companies between 11 and 40 years old indicates that more companies have managed to sustain themselves over time.
• In terms of sales, the estimated volume amounts to 2,646 million euros and the evolution of average sales increases by 10.4%.  The average turnover per company is over 4.4 million euros, while the median is 442,000 euros. Compared to the previous year, the average has increased by 200,000 euros, while the median has decreased by 30,000 euros.
• It is estimated that the infomediary sector employs some 24,620 people, 64% of whom are concentrated in three sub-sectors. These figures represent a growth of 6% over the previous year. Although the overall average is 39 employees per company, the median per sub-sector is no more than 6, indicating that much of the employment is concentrated in a small number of large companies. The average turnover per employee was 108,000 euros this year, an increase of 8% compared to the previous year.
• The subscribed capital of the sector amounts to EUR 252 million. This represents an increase of 6%, which breaks the negative trend of recent years.
• 74% of the companies have reported profits. The aggregate net profit of the 539 companies for which data is available exceeded 145 million euros.

The following visual summarises some of this data:

Figure 1. Source: Asedie Infomediary Sector Report. "Data Economy in its infomediary scope" (2025).

Significant advances in the ASEDIE Top 10

The Asedie Top 10 aims to identify and promote the openness of selected datasets for reuse. This initiative seeks to foster collaboration between the public and private sectors, facilitating access to information that can generate significant economic and social benefits. Its development has taken place in three phases, each focusing on different datasets, the evolution of which has been analysed in this report:.

• Phase 1 (2019), which promoted the opening of databases of associations, cooperatives and foundations. Currently, 16 Autonomous Communities allow access to the three databases and 11 already offer NIF data.  There is a lack of access to cooperatives in a community.
• Phase 2 (2020), focusing on datasets related to energy efficiency certificates, SAT registers and industrial estates. All communities have made energy efficiency data available to citizens, but one is missing in industrial parks and three in SAT registers.
• Phase 3 (2023), focusing on datasets of economic agents, education centres, health centres and ERES-ERTES (Expediente de Regulación de Empleo y Expediente de Regulación Temporal de Empleo). Progress has been made compared to last year, but work is ongoing to achieve greater uniformity of information.

New success stories and best practices

The report concludes with a section compiling several success stories of products and services developed with public information and contributing to the growth of our economy, for example:

• Energy Efficiency Improvement Calculator: allows to identify the necessary interventions and estimate the associated costs and the impact on the energy efficiency certification (EEC).
• GEOPUBLIC: is a tool designed to help Public Administrations better understand their territory. It allows for an analysis of strengths, opportunities and challenges in comparison with other similar regions, provinces or municipalities. Thanks to its ability to segment business and socio-demographic data at different scales, it facilitates the monitoring of the life cycle of enterprises and their influence on the local economy.
• New website of the DBK sectoral observatory: improves the search for sectoral information, thanks to the continuous monitoring of some 600 Spanish and Portuguese sectors. Every year it publishes more than 300 in-depth reports and 1,000 sectoral information sheets.
• Data assignment and repair service: facilitates the updating of information on the customers of electricity retailers by allowing this information to be enriched with the cadastral reference associated with the supply point. This complies with a requirement of the State Tax Administration Agency (AEAT).

The report also includes good practices of public administrations such as:

• The Callejero Digital de Andalucía Unificado (CDAU), which centralises, standardises and keeps the region's geographical and postal data up to date.
• The Geoportal of the Madrid City Council, which integrates metadata, OGC map services, a map viewer and a geolocator that respect the INSPIRE and LISIGE directives. It is easy to use for both professionals and citizens thanks to its intuitive and accessible interface.
• The Canary Statistics Institute (ISTAC), which has made an innovative technological ecosystem available to society. It features eDatos, an open source infrastructure for statistical data management ensuring transparency and interoperability.
• The Spanish National Forest Inventory (IFN) and its web application Download IFN, a basic resource for forest management, research and education. Allows easy filtering of plots for downloading.
• The Statistical Interoperability Node, which provides legal, organisational, semantic and technical coverage for the integration of the different information systems of the different levels of administrative management.
• The Open Cohesion School, an innovative educational programme of the Generalitat de Catalunya aimed at secondary school students. Students investigate publicly funded projects to analyse their impact, while developing digital skills, critical thinking and civic engagement.
• The National Publicity System for Public Subsidies and Grants, which has unveiled a completely redesigned website. It has improved its functionality with API-REST queries and downloads. More information here.

In conclusion, the infomediary sector in Spain consolidifies itself as a key driver for the economy, showing a solid evolution and steady growth. With a record number of companies and a turnover exceeding 2.6 billion euros in 2023, the sector not only generates employment, but also positions itself as a benchmark for innovation. Information as a strategic resource drives a more efficient and connected economic future. Its proper use, always from an ethical perspective, promises to continue to be a source of progress both nationally and internationally.

The 2024 Best Cases Awards of the Public Sector Tech Watch observatory now have finalists. These awards seek to highlight solutions that use emerging technologies, such as artificial intelligence or blockchain, in public administrations, through two categories:

• Solutions to improve the public services offered to citizens (Government-to-Citizen or G2C).
• Solutions to improve the internal processes of the administrations themselves (Government-to-Government or G2G).

The awards are intended to create a mechanism for sharing the best experiences on the use of emerging technologies in the public sector and thus give visibility to the most innovative administrations in Europe.

Almost 60% of the finalist solutions are Spanish.

In total, 32 proposals have been received, 14 of which have been pre-selected in a preliminary evaluation. Of these, more than half are solutions from Spanish organisations. Specifically, nine finalists have been shortlisted for the G2G category -five of them Spanish- and five for G2C -three of them linked to our country-.The following is a summary of what these Spanish solutions consist of.

Solutions to improve the internal processes of the administrations themselves.

• Innovation in local government: digital transformation and GeoAI for data management (Alicante Provincial Council).

Suma Gestión Tributaria, of the Diputación de Alicante, is the agency in charge of managing and collecting the municipal taxes of the city councils of its province. To optimise this task, they have developed a solution that combines geographic information systems and artificial intelligence (machine learning and deep learning) to improve training in detection of properties that do not pay taxes. This solution collects data from multiple administrations and entities in order to avoid delays in the collection of municipalities.

• Regional inspector of public infrastructures: monitoring of construction sites (Provincial Council of Bizkaia and Interbiak).

The autonomous road inspector and autonomous urban inspector help public administrations to automatically monitor roads. These solutions, which can be installed in any vehicle, use artificial or computer vision techniques along with information from sensors to automatically check the condition of traffic signs, road markings, protective barriers, etc. They also perform early forecasting of pavement degradation, monitor construction sites and generate alerts for hazards such as possible landslides.

• Application of drones for the transport of biological samples (Centre for Telecommunications and Information Technologies -CTTI-, Generalitat de Catalunya).

This pilot project implements and evaluates a health transport route in the Girona health region. Its aim is to transport biological samples (blood and urine) between a primary health centre and a hospital using drones. As a result, the journey time has been reduced from 20 minutes with ground transport to seven minutes with the use of drones. This has improved the quality of the samples transported, increased flexibility in scheduling transport times and reduced environmental impact.

• Robotic automation of processes in the administration of justice (Ministry of the Presidency, Justice and Relations with the Courts).

Ministry of the Presidency, Justice and Relations with the Courts has implemented a solution for the robotisation of administrative processes in order to streamline routine, repetitive and low-risk work. To date, more than 25 process automation lines have been implemented, including the automatic cancellation of criminal records, nationality applications, automatic issuance of life insurance certificates, etc. As a result, it is estimated that more than 500,000 working hourshave been saved.

• Artificial intelligence in the processing of official publications (Official Gazette of the Province of Barcelona and Official Documentation and Publications Service, Barcelona Provincial Council).

CIDO (Official Information and Documentation Search Engine) has implemented an AI system that automatically generates summaries of official publications of the public administrations of Barcelona. Using supervised machine learning and neural networkstechniques, the system generates summaries of up to 100 words for publications in Catalan or Spanish. The tool allows the recording of manual modifications to improve accuracy.

Solutions to improve the public services offered to citizens

• Virtual Desk of Digital Immediacy: bringing Justice closer to citizens through digitalisation (Ministry of the Presidency, Justice and Relations with the Courts).

The Virtual Digital Immediacy Desktop (EVID) allows remote hearings with full guarantees of legal certainty using blockchain technologies. The solution integrates the convening of the hearing, the provision of documentation, the identification of the participants, the acceptance of consents, the generation of the document justifying the action carried out, the signing of the document and the recording of the session. In this way, legal acts can be carried out from anywhere, without the need to travel and in a simple way, making justice more inclusive, accessible and environmentally friendly. By the end of June 2024, more than 370,000 virtual sessions had been held through EVID.

• Application of Generative AI to make it easier for citizens to understand legal texts (Entitat Autònoma del Diari Oficial i Publicacions -EADOP-, Generalitat de Catalunya).

Legal language is often a barrier that prevents citizens from easily understanding legal texts. To remove this obstacle, the Government is making available to users of the Legal Portal of Catalonia and to the general public the summaries of Catalan law in simple language obtained from generative artificial intelligence. The aim is to have summaries of the more than 14,000 14,000 existing regulatory provisions adapted to clear communication available by the end of the year. The abstracts will be published in Catalan and Spanish, with the prospect of also offering a version in Aranesein the future.

• Emi - Intelligent Employment (Consellería de Emprego, Comercio e Emigración de la Xunta de Galicia).

Emi, Intelligent Employment is an artificial intelligence and big data tool that helps the offices of the Public Employment Service of Galicia to orient unemployed people towards the skills required by the labour market, according to their abilities. AI models make six-month projections of contracts for a particular occupation for a chosen geographical area. In addition, they allow estimating the probability of finding employment for individuals in the coming months.

You can see all the solutions presented here. The winners will be announced at the final event on 28 November. The ceremony takes place in Brussels, but can also be followed online. To do so, you need to register here.

Public Sector Tech Watch: an observatory to inspire new projects

Public Sector Tech Watch (PSTW), managed by the European Commission, is positioned as a "one-stop shop" for all those interested - public sector, policy makers, private companies, academia, etc. - in the latest technological developments to improve public sector performance and service delivery. For this purpose, it has several sections where the following information of interest is displayed:

• Cases: contains examples of how innovative technologies and their associated data are used by public sector organisations in Europe.
• Stories: presents testimonials to show the challenges faced by European administrations in implementing technological solutions.

If you know of a case of interest that is not currently monitored by PSTW, you can register it here. Successful cases are reviewed and evaluated before being included in the database.

Almost half of European adults lack basic digital skills. According to the latest State of the Digital Decade report, in 2023, only 55.6% of citizens reported having such skills. This percentage rises to 66.2% in the case of Spain, ahead of the European average.

Having basic digital skills is essential in today's society because it enables access to a wider range of information and services, as well as effective communication in onlineenvironments, facilitating greater participation in civic and social activities. It is also a great competitive advantage in the world of work.

In Europe, more than 90% of professional roles require a basic level of digital skills. Technological knowledge has long since ceased to be required only for technical professions, but is spreading to all sectors, from business to transport and even agriculture. In this respect, more than 70% of companies said that the lack of staff with the right digital skills is a barrier to investment.

A key objective of the Digital Decade is therefore to ensure that at least 80% of people aged 16-74 have at least basic digital skills by 2030.

Basic technology skills that everyone should have

When we talk about basic technological capabilities, we refer, according to the DigComp framework , to a number of areas, including:

• Information and data literacy: includes locating, retrieving, managing and organising data, judging the relevance of the source and its content.
• Communication and collaboration: involves interacting, communicating and collaborating through digital technologies taking into account cultural and generational diversity. It also includes managing one's own digital presence, identity and reputation.
• Digital content creation: this would be defined as the enhancement and integration of information and content to generate new messages, respecting copyrights and licences. It also involves knowing how to give understandable instructions to a computer system.
• Security: this is limited to the protection of devices, content, personal data and privacy in digital environments, to protect physical and mental health.
• Problem solving: it allows to identify and solve needs and problems in digital environments. It also focuses on the use of digital tools to innovate processes and products, keeping up with digital evolution.

Which data-related jobs are most in demand?

Now that the core competences are clear, it is worth noting that in a world where digitalisation is becoming increasingly important , it is not surprising that the demand for advanced technological and data-related skills is also growing.

According to data from the LinkedIn employment platform, among the 25 fastest growing professions in Spain in 2024 are security analysts (position 1), software development analysts (2), data engineers (11) and artificial intelligence engineers (25). Similar data is offered by Fundación Telefónica's Employment Map, which also highlights four of the most in-demand profiles related to data:

• Data analyst: responsible for the management and exploitation of information, they are dedicated to the collection, analysis and exploitation of data, often through the creation of dashboards and reports.
• Database designer or database administrator: focused on designing, implementing and managing databases. As well as maintaining its security by implementing backup and recovery procedures in case of failures.
• Data engineer: responsible for the design and implementation of data architectures and infrastructures to capture, store, process and access data, optimising its performance and guaranteeing its security.
• Data scientist: focused on data analysis and predictive modelling, optimisation of algorithms and communication of results.

These are all jobs with good salaries and future prospects, but where there is still a large gap between men and women. According to European data, only 1 in 6 ICT specialists and 1 in 3 science, technology, engineering and mathematics (STEM) graduates are women.

To develop data-related professions, you need, among others, knowledge of popular programming languages such as Python, R or SQL, and multiple data processing and visualisation tools, such as those detailed in these articles:

• Debugging and data conversion tools
• Data analysis tools
• Data visualisation tools
• Data visualisation libraries and APIs
• Geospatial visualisation tools
• Network analysis tools

The range of training courses on all these skills is growing all the time.

Future prospects

Nearly a quarter of all jobs (23%) will change in the next five years, according to the World Economic Forum's Future of Jobs 2023 Report.  Technological advances will create new jobs, transform existing jobs and destroy those that become obsolete. Technical knowledge, related to areas such as artificial intelligence or Big Data, and the development of cognitive skills, such as analytical thinking, will provide great competitive advantages in the labour market of the future. In this context, policy initiatives to boost society's re-skilling , such as the European Digital Education Action Plan (2021-2027), will help to generate common frameworks and certificates in a constantly evolving world.

The technological revolution is here to stay and will continue to change our world. Therefore, those who start acquiring new skills earlier will be better positioned in the future employment landscape.

Data literacy has become a crucial issue in the digital age. This concept refers to the ability of people to understand how data is used, how it is accessed, created, analysed, used or reused, and communicated.

We live in a world where data and algorithms influence everyday decisions and the opportunities people have to live well. Its effect can be felt in areas ranging from advertising and employment provision to criminal justice and social welfare. It is therefore essential to understand how data is generated and used.

Data literacy can involve many areas, but we will focus on its relationship with digital rights on the one hand and Artificial Intelligence (AI) on the other. This article proposes to explore the importance of data literacy for citizenship, addressing its implications for the protection of individual and collective rights and the promotion of a more informed and critical society in a technological context where artificial intelligence is becoming increasingly important.

The context of digital rights

More and more studies studies increasingly indicate that effective participation in today's data-driven, algorithm-driven society requires data literacy indicating that effective participation in today's data-driven, algorithm-driven society requires data literacy. Civil rights are increasingly translating into digital rights as our society becomes more dependent on digital technologies and environments digital rights as our society becomes more dependent on digital technologies and environments. This transformation manifests itself in various ways:

• On the one hand, rights recognised in constitutions and human rights declarations are being explicitly adapted to the digital context. For example, freedom of expression now includes freedom of expression online, and the right to privacy extends to the protection of personal data in digital environments. Moreover, some traditional civil rights are being reinterpreted in the digital context. One example of this is the right to equality and non-discrimination, which now includes protection against algorithmic discrimination and against bias in artificial intelligence systems. Another example is the right to education, which now also extends to the right to digital education. The importance of digital skills in society is recognised in several legal frameworks and documents, both at national and international level, such as the Organic Law 3/2018 on Personal Data Protection and Guarantee of Digital Rights (LOPDGDD) in Spain. Finally, the right of access to the internet is increasingly seen as a fundamental right, similar to access to other basic services.
• On the other hand, rights are emerging that address challenges unique to the digital world, such as the right to be forgotten (in force in the European Union and some other countries that have adopted similar legislation¹), which allows individuals to request the removal of personal information available online, under certain conditions. Another example is the right to digital disconnection (in force in several countries, mainly in Europe²), which ensures that workers can disconnect from work devices and communications outside working hours. Similarly, there is a right to net neutrality to ensure equal access to online content without discrimination by service providers, a right that is also established in several countries and regions, although its implementation and scope may vary. The EU has regulations that protect net neutrality, including Regulation 2015/2120, which establishes rules to safeguard open internet access. The Spanish Data Protection Act provides for the obligation of Internet providers to provide a transparent offer of services without discrimination on technical or economic grounds. Furthermore, the right of access to the internet - related to net neutrality - is recognised as a human right by the United Nations (UN).

This transformation of rights reflects the growing importance of digital technologies in all aspects of our lives.

The context of artificial intelligence

The relationship between AI development and data is fundamental and symbiotic, as data serves as the basis for AI development in a number of ways:

1. Data is used to train AI algorithms, enabling them to learn, detect patterns, make predictions and improve their performance over time.
2. The quality and quantity of data directly affect the accuracy and reliability of AI systems. In general, more diverse and complete datasets lead to better performing AI models.
3. The availability of data in various domains can enable the development of AI systems for different use cases.

Data literacy has therefore become increasingly crucial in the AI era, as it forms the basis for effectively harnessing and understanding AI technologies.

In addition, the rise of big data and algorithms has transformed the mechanisms of participation, presenting both challenges and opportunities. Algorithms, while they may be designed to be fair, often reflect the biases of their creators or the data they are trained on. This can lead to decisions that negatively affect vulnerable groups.

In this regard, legislative and academic efforts are being made to prevent this from happening. For example, the EuropeanArtificial Intelligence Act (AI Act) includes safeguards to avoid harmful biases in algorithmic decision-making. For example, it classifies AI systems according to their level of potential risk and imposes stricter requirements on high-risk systems. In addition, it requires the use of high quality data to train the algorithms, minimising bias, and provides for detailed documentation of the development and operation of the systems, allowing for audits and evaluations with human oversight. It also strengthens the rights of persons affected by AI decisions, including the right to challenge decisions made and their explainability, allowing affected persons to understand how a decision was reached.

The importance of digital literacy in both contexts

Data literacy helps citizens make informed decisions and understand the full implications of their digital rights, which are also considered, in many respects, as mentioned above, to be universal civil rights. In this context, data literacy serves as a critical filter for full civic participation that enables citizens to influence political and social decisions full civic participation that enables citizens to influence political and social decisions. That is,those who have access to data and the skills and tools to navigate the data infrastructure effectively can intervene and influencepolitical and social processes in a meaningful way , something which promotes the Open Government Partnership.

On the other hand, data literacy enables citizens to question and understand these processes, fostering a culture of accountability and transparency in the use of AI.  There arealso barriers to participation in data-driven environments. One of these barriers is the digital divide (i.e. deprivation of access to infrastructure, connectivity and training, among others) and, indeed, lack of data literacy. The latter is therefore a crucial concept for overcoming the challenges posed by datification datification of human relations and the platformisation of content and services.

Recommendations for implementing a preparedness partnership

Part of the solution to addressing the challenges posed by the development of digital technology is to include data literacy in educational curricula from an early age.

This should cover:

• Data basics: understanding what data is, how it is collected and used.
• Critical analysis: acquisition of the skills to evaluate the quality and source of data and to identify biases in the information presented. It seeks to recognise the potential biases that data may contain and that may occur in the processing of such data, and to build capacity to act in favour of open data and its use for the common good.
• Rights and regulations: information on data protection rights and how European laws affect the use of AI. This area would cover all current and future regulation affecting the use of data and its implication for technology such as AI.
• Practical applications: the possibility of creating, using and reusing open data available on portals provided by governments and public administrations, thus generating projects and opportunities that allow people to work with real data, promoting active, contextualised and continuous learning.

By educating about the use and interpretation of data, it fosters a more critical society that is able to demand accountability in the use of AI. New data protection laws in Europe provide a framework that, together with education, can help mitigate the risks associated with algorithmic abuse and promote ethical use of technology. In a data-driven society, where data plays a central role, there is a need to foster data literacy in citizens from an early age.

¹The right to be forgotten was first established in May 2014 following a ruling by the Court of Justice of the European Union. Subsequently, in 2018, it was reinforced with the General Data Protection Regulation (GDPR)which explicitly includes it in its Article 17 as a "right of erasure". In July 2015, Russia passed a law allowing citizens to request the removal of links on Russian search engines if the information"violates Russian law or if it is false or outdated". Turkey has established its own version of the right to be forgotten, following a similar model to that of the EU. Serbia has also implemented a version of the right to be forgotten in its legislation. In Spain, the Ley Orgánica de Protección de Datos Personales (LOPD) regulates the right to be forgotten, especially with regard to debt collection files. In the United Statesthe right to be forgotten is considered incompatible with the Constitution, mainly because of the strong protection of freedom of expression. However, there are some related regulations, such as the Fair Credit Reporting Act of 1970, which allows in certain situations the deletion of old or outdated information in credit reports.

Content prepared by Miren Gutiérrez, PhD and researcher at the University of Deusto, expert in data activism, data justice, data literacy and gender disinformation. The contents and views reflected in this publication are the sole responsibility of the author.

Data equity is a concept that emphasises the importance of considering issues of power, bias and discrimination in data collection, analysis and interpretation. It involves ensuring that data is collected, analysed and used in a way that is fair, inclusive and equitable to all stakeholders, particularly those who have historically been marginalised or excluded. Although there is no consensus on its definition, data equity aims to address systemic inequalities and power imbalances by promoting transparency, accountability and community ownership of data. It also involves recognising and redressing legacies of discrimination through data and ensuring that data is used to support the well-being and empowerment of all individuals and communities. Data equity is therefore a key principle in data governance, related to impacts on individuals, groups and ecosystems

To shed more light on this issue, the World Economic Forum - an organisation that brings together business leaders and experts to organisation that brings together leaders of major companies and experts to discuss global issues - published a short report entitled published a few months ago a short report entitled Data Equity: Foundational Concepts for Generative AI, aimed at industry, civil society, academia and decision-makers.

The aim of the World Economic Forum paper is, first, to define data equity and demonstrate its importance in the development and implementation of Generative AI (known as genAI). In this report, the World Economic Forum identifies some challenges and risks associated with data inequity in AI development, such as bias, discrimination and unfair outcomes. It also aims to provide practical guidance and recommendations for achieving data equity, including strategies for data collection, analysis and use. On the other hand, the World Economic Forum says it wants, on the one hand, to foster collaboration between stakeholders from industry, governments, academia and civil society to address data equity issues and promote the development of fair and inclusive AI, and on the other hand, to influence the future of AI development.

Some of the key findings of the report are discussed below.

Types of data equity

The paper identifies four main classes of data equity: 

•  Fairness of representation refers to the fair and proportional inclusion of different groups in the datasets used to train genAI models.
•  Resource equity refers to the equitable distribution of resources (data, infrastructure and knowledge) necessary for the development and use of genAI.
•  Equity of access means ensuring fair and non-discriminatory access to the capabilities and benefits of genAI by different groups.
•  Equity of results seeks to ensure that genAI results and applications do not generate disproportionate or detrimental impacts on vulnerable groups.

Equity challenges in the genAI

The paper highlights that foundation models, which are the basis of many genAI tools, present specific data fairness challenges, as they encode biases and prejudices present in training datasets and can amplify them in their results. In AI, a function model refers to a program or algorithm that relies on training data to recognise patterns and make predictions or decisions, allowing it to make predictions or decisions based on new input data.

The main challenges in terms of social justice with artificial intelligence (AI) include thefact thattraining data may be biased. Generative AI models are trained on large datasets that often contain bias and discriminatory content, which can lead to the perpetuation of hate speech, misogyny and racism.  Algorithmic biasescan then occur, which not only reproduce these initial biases, but can amplify them, increasing existing social inequalities and resulting in discrimination and unfair treatment of stereotyped groups. There are also privacy concerns, as generative AI relies on some sensitive personal data, which can be exploited and exposed.

The increasing use of generative AI in various fields is already causing job changes, as it is easier, quicker or cheaper to ask an artificial intelligence to create an image or text - in fact, based on human creations that exist on the internet - than to commission an expert to do so. This can exacerbate economic inequalities.

Finally, generative AI has the potential to intensify disinformation. Generative AI can be used to create high-quality deepfakes, which are already being used to spread hoaxes and misinformation, potentially undermining democratic processes and institutions.

Gaps and possible solutions

These challenges highlight the need for careful consideration and regulation of generative AI to ensure that it is developed and used in a way that respects human rights and promotes social justice. However, the document does not address misinformation and only mentions gender when talking about "feature equity", a component of data equity. Equity of characteristics seeks to "ensure accurate representation of the individuals, groups and communities represented by the data, which requires the inclusion of attributes such as race, gender, location and income along with other data" (p.4). Without these attributes, the paper says, "it is often difficult to identify and address latent biases and inequalities". However, the same characteristics can be used to discriminate against women, for example.

Addressing these challenges requires the engagement and collaboration of various stakeholders, such as industry, government, academia and civil society, to develop methods and processes that integrate data equity considerations into all phases of genAIdevelopment. This document lays the theoretical foundations of what can be understood as data equity; however, there is still a long way to go to see how to move from theory to practice in regulation, habits and knowledge.

This document links up with the steps already being taken in Europe and Spain with the European Union's AI Law y the IA Strategy of the Spanish Government respectively. Precisely, one of the axes of the latter (Axis 3) is to promote transparent, ethical and humanistic AI.

The Spanish AI strategy is a more comprehensive document than that of the World Economic Forum, outlining the government's plans for the development and adoption of general artificial intelligence technologies. The strategy focuses on areas such as talent development, research and innovation, regulatory frameworks and the adoption of AI in the public and private sectors, and targets primarily national stakeholders such as government agencies, businesses and research institutions. While the Spanish AI strategy does not explicitly mention data equity, it does emphasise the importance of responsible and ethical AI development, which could include data equity considerations.

The World Economic Forum report can be found here: Data Equity: Foundational Concepts for Generative AI | World Economic Forum (weforum.org)

Content prepared by Miren Gutiérrez, PhD and researcher at the University of Deusto, expert in data activism, data justice, data literacy and gender disinformation. The contents and views reflected in this publication are the sole responsibility of its author.

Artificial intelligence (AI) has revolutionised various aspects of society and our environment. With ever faster technological advances, AI is transforming the way daily tasks are performed in different sectors of the economy.   

As such, employment is one of the sectors where it is having the greatest impact. Among the main developments, this technology is introducing new professional profiles and modifying or transforming existing jobs. Against this backdrop, questions are being asked about the future of employment and how it will affect workers in the labour market.   

What are the key figures for AI in employment?  

The International Monetary Fund has recently pointed out: Artificial Intelligence will affect 40% of jobs worldwide, both replacing some and complementing and creating new ones.   

The irruption of AI in the world of work has made it easier for some tasks that previously required human intervention to be carried out more automatically. Moreover, as the same international organisation warns, compared to other automation processes experienced in past decades, the AI era is also transforming highly skilled jobs.  

The document also states that the impact of AI on the workplace will differ according to the country's level of development. It will be greater in the case of advanced economies, where up to 6 out of 10 jobs are expected to be conditioned by this technology. In the case of emerging economies, it will reach up to 40% and, in low-income countries, it will be reflected in 26% of jobs. For its part, the International Labour Organisation (ILO) also warns in its report ‘Generative AI and Jobs: A global analysis of potential effects on job quantity and quality’ that the effects of the arrival of AI in administrative positions will particularly affect women, due to the high rate of female employment in this labour sector.  

In the Spanish case, according to figures from last year, not only is the influence of AI on jobs observed, but also the difficulty of finding people with specialised training. According to the report on talent in artificial intelligence prepared by Indesia, last year 20% of job offers related to data and Artificial Intelligence were not filled due to a lack of professionals with specialisation. 

Future projections  

Although there are no reliable figures yet to see what the next few years will look like, some organisations, such as the OECD, say that we are still at an early stage in the development of AI in the labour market, but on the verge of a large-scale breakthrough. According to its ‘Employment Outlook 2023’ report, ‘business adoption of AI remains relatively low’, although it warns that ‘rapid advances, including in generative AI (e.g. ChatGPT), falling costs and the growing availability of AI-skilled workers suggest that OECD countries may be on the verge of an AI revolution’. It is worth noting that generative AI is one of the fields where open data is having a major impact. 

And what will happen in Spain? Perhaps it is still too early to point to very precise figures, but the report produced last year by Indesia already warned that Spanish industry will require more than 90,000 data and AI professionals by 2025. This same document also points out the challenges that Spanish companies will have to face, as globalisation and the intensification of remote work means that national companies are competing with international companies that also offer 100% remote employment, ‘with better salary conditions, more attractive and innovative projects and more challenging career plans’, says the report.   

What jobs is AI changing?  

Although one of the greatest fears of the arrival of this technology in the world of work is the destruction of jobs, the latest figures published by the International Labour Organisation (ILO) point to a much more promising scenario. Specifically, the ILO predicts that AI will complement jobs rather than destroy them.   

There is not much unanimity on which sectors will be most affected. In its report ‘The impact of AI on the workplace: Main findings from the OECD AI surveys of employers and workers', the OECD points out that manufacturing and finance are two of the areas most affected by the irruption of Artificial Intelligence.   

On the other hand, Randstad has recently published a report on the evolution of the last two years with a vision of the future until 2033. The document points out that the most affected sectors will be jobs linked to commerce, hospitality and transport. Among those jobs that will remain largely unaffected are agriculture, livestock and fishing, associative activities, extractive industries and construction. Finally, there is a third group, which includes employment sectors in which new profiles will be created. In this case, we find programming and consultancy companies, scientific and technical companies, telecommunications and the media and publications. 

Beyond software developers, the new jobs that artificial intelligence is bringing will include everything from natural language processing experts or AI Prompt engineers (experts in asking the questions needed to get generative AI applications to deliver a specific result) to algorithm auditors or even artists.  

Ultimately, while it is too early to say exactly which types of jobs are most affected, organisations point to one thing: the greater the likelihood of automation of job-related processes, the greater the impact of AI in transforming or modifying that job profile.   

The challenges of AI in the labour market  

One of the bodies that has done most research on the challenges and impacts of AI on employment is the ILO. At the level of needs, the ILO points to the need to design policies that support an orderly, just and consultative transition. To this end, it notes that workers' voice, training and adequate social protection will be key to managing the transition. ‘Otherwise, there is a risk that only a few countries and well-prepared market participants will benefit from the new technology,’ it warns.  

For its part, the OECD outlines a series of recommendations for governments to accommodate this new employment reality, including the need to: 

• Establish concrete policies to ensure the implementation of key principles for the reliable use of AI. Through the implementation of these mechanisms, the OECD believes that the benefits that AI can bring to the workplace are harnessed, while at the same time addressing potential risks to fundamental rights and workers' well-being.   

• Create new skills, while others will change or become obsolete. To this end, he points to training, which is needed ‘both for the low-skilled and older workers, but also for the high-skilled’. Therefore, ‘governments should encourage business to provide more training, integrate AI skills into education and support diversity in the AI workforce’.   

In summary, although the figures do not yet allow us to see the full picture, several international organisations do agree that the AI revolution is coming. They also point to the need to adapt to this new scenario through internal training in companies to be able to cope with the needs posed by the technology. Finally, in governmental matters, organisations such as the ILO point out that it is necessary to ensure that the transition in the technological revolution is fair and within the margins of reliable uses of Artificial Intelligence. 

The Multisectoral Information Partnership (ASEDIE) has published the twelfth edition of its "Report on the Infomediary Sector", that reviews the initiatives to boost the data economy in the country. In addition, this edition commemorates the 25th anniversary of the association in the sector.

In the 12th Report on the Data Economy in the infomediary sphere, ASEDIE provides accurate figures on the sector in Spain to continue its annual work of highlighting and conveying its size and importance. The presentation of this edition took place at Madrid International Lab's auditorium on 20 March.

The main findings of the study are summarised below.