From today, September 15, registration is open for one of the most important events in the geospatial sector in the Iberian Peninsula. The XVI Iberian Conference on Spatial Data Infrastructures (JIIDE 2025) will be held in Oviedo from 12 to 14 November 2025. This annual meeting represents a unique opportunity to explore the latest trends in spatial data reuse, especially in the context of the application of artificial intelligence to territorial knowledge.

Since its first edition in 2011, the JIIDEs have evolved as a result of collaboration between the Direção-Geral do Território de Portugal, the National Geographic Institute of Spain through the National Center for Geographic Information, and the Government of Andorra. In this sixteenth edition, the Ministry of Territorial Planning, Urban Planning, Housing and Citizens' Rights of  the Principality of Asturias and the University of Oviedo also join, thus consolidating an initiative that brings together hundreds of professionals from the Public Administration, the private sector and the academic field every year.

For three days, experts with proven experience and technical knowledge in geographic information will share their most innovative developments, work methodologies and success stories in the management and reuse of spatial data.

Two axes: artificial intelligence and the INSPIRE and HVDS regulatory framework

The central theme of this edition, "AI and territory: exploring the new frontiers of spatial knowledge", reflects the natural evolution of the sector towards the incorporation of emerging technologies. Artificial intelligence, machine learning, and advanced analytics algorithms are radically transforming the way we process, analyze, and extract value from geospatial data.

This orientation towards AI is not accidental. The publication and use of geospatial data makes it possible to harness one of the most valuable digital assets for economic development, environmental monitoring, competitiveness, innovation and job creation. When this data is combined with artificial intelligence techniques, its potential multiplies exponentially.

The conference takes place at a particularly relevant time for the open data ecosystem. The INSPIRE Directive, together with Directive (EU) 2019/1024 on open data and re-use of public sector information, has established a regulatory framework that explicitly recognises the economic and social value of digital geospatial data.

The evolution in the publication of high-value datasets marks an important milestone in this process. These sets, characterized by their great potential for reuse, should be available free of charge, in machine-readable formats and through application programming interfaces (APIs). Geospatial data occupies a central position in this categorisation, underlining its strategic importance for the European open data ecosystem.

JIIDE 2025 will devote particular attention to presenting practical examples of re-use of these high-value datasets , both through the new OGC APIs and through traditional download services and established interoperable formats. This practical approach will allow attendees to learn about real cases of implementation and their tangible results.

Miscellaneous Program: Use Cases, AI, and Geospatial Data Reuse

You can also check the program here. Among the planned activities, there are sessions ranging from fundamental technical aspects to innovative applications that demonstrate the transformative potential of this data. The activities are organized into five main themes:

1. Spatial data structure and metadata.

2. Data management and publication.

3. Development of spatial  software.

4. Artificial intelligence.

5. Cooperation between agents.

Some of the highlighted topics are project management and coordination, where corporate systems such as the SIG of the Junta de Andalucía or the SITNA of the Government of Navarra will be presented. Earth observation will also feature prominently, with presentations on the evolution of the National Plan for Aerial Orthophotography (APNOA) programme  and advanced deep learning image processing techniques.

On the other hand, thematic visualisers also represent another fundamental axis, showing how spatial data can be transformed into accessible tools for citizens. From eclipse visualizers to tools for calculating the solar potential of rooftops, developments will be presented that demonstrate how the creative reuse of data can generate services of high social value.

Following the annual theme, the application of AI to geospatial data will be approached from multiple perspectives. Use cases will be presented in areas as diverse as the automatic detection of sports facilities, the classification of LiDAR point clouds, the identification of hazardous materials such as asbestos, or the optimization of urban mobility.

One of the most relevant sessions for the open data community will focus specifically on "Reuse and Open Government". This session will address the integration of spatial data infrastructures into open data portals, spatial data metadata according to the GeoDCAT-AP standard, and the application of data quality regulations.

Local governments play a key role in the generation and publication of spatial data. For this reason, the JIIDE 2025 will dedicate a specific session to the publication of local data, where municipalities such as Barcelona, Madrid, Bilbao or Cáceres will share their experiences and developments.

In addition to the theoretical sessions, the conferences include practical workshops on specific tools, methodologies and technologies. These workshops, lasting 45 minutes to an hour, allow attendees to experiment directly with the solutions presented. Some of them address the creation of custom web geoportals and others, for example, the implementation of OGC APIs, through advanced visualization techniques and metadata management tools.

Participate in person or online

The JIIDEs maintain their commitment to open participation, inviting both researchers and professionals to present their tools, technical solutions, work methodologies and success stories. In addition, the JIIDE 2025 will be held in hybrid mode, allowing both face-to-face participation in Oviedo and virtual monitoring.

This flexibility, maintained from the experiences of recent years, ensures that professionals throughout the Iberian territory and beyond can benefit from shared knowledge. Participation remains free, although prior registration is required for each session, roundtable or workshop.

Starting today, you can sign up and take advantage of this opportunity to learn and exchange experiences on geospatial data. Registration is available on the official website of the event: https://www.jiide.org/web/portal/inicio

Imagine you want to know how many terraces there are in your neighbourhood, how the pollen levels in the air you breathe every day are evolving or whether recycling in your city is working well. All this information exists in your municipality's databases, but it sits in spreadsheets and technical documents that only experts know how to interpret.

This is where open data visualisation initiativescome in: they transform those seemingly cold numbers into stories that anyone can understand at a glance.  A colourful graph showing the evolution of traffic on your street, an interactive map showing the green areas of your city, or an infographic explaining how the municipal budget is spent. These tools make public information accessible, useful and, moreover, comprehensible to all citizens.

Moreover, the advantages of this type of solution are not only for the citizens, but also benefit the Administration that carries out the exercise, because it allows:

• Detect and correct data errors.
• Add new sets to the portal.
• Reduce the number of questions from citizens.
• Generate more trust on the part of society.

Therefore, visualising open data brings government closer to citizens, facilitates informed decision-making, helps public administrations to improve their open data offer and creates a more participatory society where we can all better understand how the public sector works. In this post, we present some examples of open data visualisation initiatives in regional and municipal open data portals.

Visualiza Madrid: bringing data closer to the public

Madrid City Council's open data portal has developed the initiative "Visualiza Madrid", a project born with the specific objective of making open data and its potential reach the general public , transcending specialised technical profiles. As Ascensión Hidalgo Bellota, Deputy Director General for Transparency of Madrid City Council, explained during the IV National Meeting on Open Data, "this initiative responds to the need to democratise access to public information".

Visualiza Madrid currently has 29 visualisations that cover different topics of interest to citizens, from information on hotel and restaurant terraces to waste management and urban traffic analysis. This thematic diversity demonstrates the versatility of visualisations as a tool for communicating information from very diverse sectors of public administration.

 In addition, the initiative has received external recognition this year through the Audaz 2,025 Awards, an initiative of the Spanish chapter of the Open Government Academic Network (RAGA Spain).The initiative has also received external recognition through the Audaz 2,025 Awards.

Castilla y León: comprehensive analysis of regional data

 The Junta de Castilla y León has also developed a portal specialised in analysis and visualisations that stands out for its comprehensive approach to the presentation of regional data. Its visualisation platform offers a systematic approach to the analysis of regional information, allowing users to explore different dimensions of the reality of Castilla y Leónthrough interactive and dynamic tools.

This initiative allows complex information to be presented in a structured and understandable way, facilitating both academic analysis and citizen use of the data. The platform integrates different sources of regional information, creating a coherent ecosystem of visualisations that provides a panoramic view of different aspects of regional management. Among the topics it offers are data on tourism, the labour market and budget execution. All the visualisations are made with open data sets from the regional portal of Castilla y León .

The Castilla y León approach demonstrates how visualisations can serve as a tool for territorial analysis, providing valuable insights on economic, social and demographic dynamics that are fundamental for the planning and evaluation of regional public policies.

Canary Islands: technological integration with interactive widgets .

On the other hand, the Government of the Canary Islands has opted for an innovative strategy through the implementation of widgets that allow the integration of open data visualisations of the Instituto Canario de Estadística (ISTAC) in different platforms and contexts. This technological approach represents a qualitative leap in the distribution and reuse of public data visualisations.

The widgets developed by the Canary Islands make it easier for third parties to embed official visualisations in their own applications, websites or analyses, exponentially expanding the scope and usefulness of Canary Islands open data. This strategy not only multiplies the points of access to public information, but also fosters the creation of a collaborative ecosystem where different actors can benefit from and contribute to the value of open data.

The Canarian initiative illustrates how technology can be used to create scalable and flexible solutions that maximise the impact of investments in open data visualisation, establishing a replicable model for other administrations seeking to amplify the reach of their transparency initiatives.

Lessons learned and best practices

By way of example, the cases analysed reveal common patterns that can serve as a guide for future initiatives. The orientation towards the general public, beyond specialised technical users, emerges as an opportunity factor for the success of these platforms. To maintain the interest and relevance of the visualisations, it is important to offer thematic diversity and to update the data regularly.

Technological integration and interoperability, as demonstrated in the case of the Canary Islands, open up new possibilities to maximise the impact of public investments in data visualisation. Likewise, external recognition and participation in professional networks, as evidenced in the case of Madrid, contribute to continuous improvement and the exchange of best practices between administrations.

In general terms, open data visualisation initiatives represent a very valuable opportunity in the transparency and open government strategy of Spanish public administrations. The cases of Madrid, Castilla y León, as well as the Canary Islands, are examples of the enormous potential for transforming public data into tools for citizen empowerment and improved public management.

The success of these initiatives lies in their ability to connect government information with the real needs of citizens, creating bridges of understanding that strengthen the relationship between administration and society. As these experiences mature and consolidate, it will be crucial to keep the focus on the usability, accessibility and relevance of visualisations, ensuring that open data truly delivers on its promise to contribute to a more informed, participatory and democratic society.

Open data visualisation is not just a technical issue, but a strategic opportunity to redefine public communication and strengthen the foundations of a truly open and transparent administration.

How can public administrations harness the value of data? This question is not a simple one to address; its answer is conditioned by several factors that have to do with the context of each administration, the data available to it and the specific objectives set.

However, there are reference guides that can help define a path to action. One of them is published by the European Commission through the EU Publications Office, Data Innovation Toolkit, which emerges as a strategic compass to navigate this complex data innovation ecosystem.

This tool is not a simple manual as it includes templates to make the implementation of the process easier. Aimed at a variety of profiles, from novice analysts to experienced policy makers and technology innovators, Data Innovation Toolkit is a useful resource that accompanies you through the process, step by step.

It aims to democratise data-driven innovation by providing a structured framework that goes beyond the mere collection of information. In this post, we will analyse the contents of the European guide, as well as the references it provides for good innovative use of data.

Structure covering the data lifecycle

The guide is organised in four main steps, which address the entire data lifecycle.

1. Planning

The first part of the guide focuses on establishing a strong foundation for any data-driven innovation project. Before embarking on any process, it is important to define objectives. To do so, the Data Innovation Toolkit suggests a deep reflection that requires aligning the specific needs of the project with the strategic objectives of the organisation. In this step, stakeholder mapping is also key. This implies a thorough understanding of the interests, expectations and possible contributions of each actor involved. This understanding enables the design of engagement strategies that maximise collaboration and minimise potential conflicts.

To create a proper data innovation team, we can use the RACI matrix (Responsible, Accountable, Consulted, Informed) to define precise roles and responsibilities. It is not just about bringing professionals together, but about building multidisciplinary teams where each member understands their exact role and contribution to the project. To assist in this task the guide provides:

• Challenge definition tool: to identify and articulate the key issues they seek to address, summarising them in a single statement.
• Stakeholder mapping tool: to visualise the network of individuals and organisations involved, assessing their influence and interests.
• Team definition tool: to make it easier to identify people in your organisation who can help you.
• Tool to define roles: to, once the necessary profiles have been defined, determine their responsibilities and role in the data project in more detail, using a RACI matrix.
• Tool to define People:  People is a concept used to define specific types of users, called behavioural archetypes. This guide helps to create these detailed profiles, which represent the users or clients who will be involved in the project.
• Tool for mapping Data Journey: to make a synthetic representation describing step by step how a user can interact with his data. The process is represented from the user's perspective, describing what happens at each stage of the interaction and the touch points.

2. Collection and processing

Once the team has been set up and the objectives have been identified, a classification of the data is made that goes beyond the traditional division between quantitative and qualitative data.

Quantitative scope:

• Discrete data, such as the number of complaints in a public service, represents not only a number, but an opportunity to systematically identify areas for improvement. They allow administrations to map recurrent problems and design targeted interventions. Ongoing data, such as response times for administrative procedures, provide a snapshot of operational efficiency. It is not just a matter of measuring, but of understanding the factors that influence the variability of these times and designing more agile and efficient processes.

Qualitative:

• Nominal (name) data enables the categorisation of public services, allowing for a more structured understanding of the diversity of administrative interventions.

• Ordinal (number) data, such as satisfaction ratings, become a prioritisation tool for continuous improvement.

A series of checklists are available in the document to review this aspect:

• Checklist of data gaps: to identify if there are any gaps in the data to be used and, if so, how to fill them.
• Template for data collection: to align the dataset to the objective of the innovative analysis.
• Checklist of data collection: to ensure access to the data sources needed to run the project.
• Checklist of data quality: to review the quality level of the dataset.
• Data processing letters: to check that data is being processed securely, efficiently and in compliance with regulations.

3. Sharing and analysis

At this point, the Data Innovation Toolkit proposes four analysis strategies that transform data into actionable knowledge.

1. Descriptive analysis: goes beyond the simple visualisation of historical data, allowing the construction of narratives that explain the evolution of the phenomena studied.
2. Diagnostic analysis: delves deeper into the investigation of causes, unravelling the hidden patterns that explain the observed behaviours.
3. Predictive analytics: becomes a strategic planning tool, allowing administrations to prepare for future scenarios.
4. Prescriptive analysis: goes a step further, not only projecting trends, but recommending concrete actions based on data modelling.

In addition to analysis, the ethical dimension is fundamental. The guide therefore sets out strict protocols to ensure secure data transfers, regulatory compliance, transparency and informed consent. In this section, the following checklistis provided:

• Data sharing template: to ensure secure, legal and transparent sharing.
• Checklist for data sharing: to perform all the necessary steps to share data securely, ethically and achieving all the defined objectives.
• Data analysis template: to conduct a proper analysis to obtain insights useful and meaningful for the project.

4. Use and evaluation

The last stage focuses on converting the insights into real actions. The communication of results, the definition of key performance indicators (KPIs), impact measurement and scalability strategies become tools for continuous improvement.

A collaborative resource in continuous improvement

In short, the toolkit offers a comprehensive transformation: from evidence-based decision making to personalising public services, increasing transparency and optimising resources. You can also check the checklist available in this section which are:

• Checklist for data use: to review that the data and the conclusions drawn are used in an effective, accountable and goal-oriented manner.
• Data innovation through KPI tool: to define the KPIs that will measure the success of the process.
• Impact measurement and success evaluation tools: to assess the success and impact of the innovation in the data project.
• Data innovation scalability plan: to identify strategies to scale the project effectively.

In addition, this repository of innovation resources and data is a dynamic catalogue of knowledge including expertise articles, implementation guides, case studies and learning materials.

You can access here the list of materials provided by the Data Innovation Toolkit.

• Web: https://is.gd/datainnovationrepository

You can even contact the development team if you have any questions or would like to contribute to the repository:

• Email: DIGIT-DIGITAL-INNOVATION@ec.europa.eu

To conclude, harnessing the value of data with an innovative perspective is not a magic leap, but a gradual and complex process. On this path, the Data Innovation Toolkit can be useful as it offers a structured framework. Effective implementation will require investment in training, cultural adaptation and long-term commitment.

On 28 November, the 2nd Forum for the Government and the Autonomous Communities to meet around data was held in Seville, organised by the State Secretariat for Digitalisation and Artificial Intelligence (SEDIA), in collaboration with the Andalusian Institute of Statistics and Cartography (IECA) and the Digital Agency of Andalusia (ADA). Almost all the autonomous communities participated, reflecting their commitment to data as a strategic driver of digital transformation.

The programme addressed key issues, such as the lessons learned in the implementation of data governance, the impact of its ethical use, and the potential of public-private collaboration in the deployment of sectoral data spaces, with emphasis on the Plan for the Promotion of Sectoral Data Spaces recently presented by the Ministry for Digital Transformation on 21 November.

Here is a summary of the key points of the meeting.

A space to exchange experiences, success stories and lessons learned.

The event brought together more than 70 experts from units of the General State Administration and 15 autonomous communities and the Autonomous City of Melilla, which are active in the use and management of data in their organisations. El objetivo era poner en común las experiencias en este ámbito y compartir los casos de éxito y los aprendizajes derivados de la implantación de iniciativas de gobierno del dato, promoviendo la colaboración entre administraciones para mejorar la competitividad y la eficiencia digital futura.

The forum was opened by the Regional Minister of Presidency, Interior, Social Dialogue and Administrative Simplification of the Andalusian Regional Government, and the Director General of Data of the Ministry for Digital Transformation and Public Administration, and was closed by the Director of IECA.

The day was structured around three round tables with 15 speakers. The attendees were also able to answer various questions related to the subject matter of each of these roundtables, in order to ascertain their perceptions in this regard. This format facilitated a fruitful and enriching exchange of ideas that allowed attendees to explore key issues.

• Table 1 "Experiences of implementing Data Governance: Lessons learnt. The first round table focused on different experiences in data governance. The speakers shared the challenges faced and the practical lessons learned, with the aim of serving as an example and point of reflection for similar initiatives that participants might undertake in the future. The importance of support at the highest level and the use of existing frameworks, such as UNE specifications or the DAMA methodology, was stressed. The need to focus not only on technology, but also to respond to cultural and organisational changes, and to establish processes and structures that will last over time was also emphasised.
• Table 2 "Data with purpose: Success stories of ethical and reliable use of data". The second roundtable focused on presenting concrete results obtained through the ethical and reliable use of data. The speakers shared their backgrounds and achievements, illustrating the wide possibilities that a well governed and managed data can generate in terms of citizen service and improvement of public administration. The work to be done on the quantity and quality of datawas highlighted, without losing focus on the future goal, which is to solve today's problems through sustainable projects.
• Table 3 "Data spaces from the perspective of public-private collaboration and the enhancement of public data". The third and final roundtable explored the paradigm of data spaces. Special emphasis was placed on public-private partnerships and how to enhance the value of public data. A highlight of this session was the presentation by the Directorate General for Data of the Plan for the Promotion of Sectoral Data Spaces. This plan seeks to deploy data spaces across the different productive sectors, underlining the fundamental value that quality public data can have in their effective implementation.

Overall, these roundtables not only provided a platform for the exchange of knowledge and experiences, but also laid the groundwork for future collaborations and innovative projects in the field of data management and governance in the Spanish public administration.

Attendees were very appreciative of the wide variety of roles involved, giving different views on something as complex as data governance, which includes many different approaches and competencies. The general perception is that shared experiences help others to try to circumvent the barriers that others have previously had to overcome and to reach the final goal faster, which is to provide better service and implement better public policies for citizens through a data-driven government.

Conclusions of the Forum

Some of the conclusions reached were:

• It is necessary to focus on data quality. Without quality data, well governed and managed, it will be difficult to achieve valuable solutions, for example in the field of artificial intelligence.
• Invest in data governance by ensuring sustainable projects. Data governance is not just about technology, but about business and services. It requires considerable effort on the part of organisations to create data that reflect reality and are truly useful for decision-making, breaking down silos and implementing citizen-oriented services. To this end, it is recommended to build on existing conceptual frameworks, oriented towards processes and organisational structures that are sustainable over time.
• The Autonomous Communities can help the deployment of the Plan for the Promotion of Data Spaces from a public-private partnership perspective and benefit from its actions.
• We need to influence the data culture in organisations. The objective is to incorporate data governance into the different business areas, supporting organisational objectives, ensuring that the data culture permeates the organisation and is perceived as something transversal that contributes value to the different sectors as well as to the administration and society as a whole.

Upcoming performances

After the success of the first edition, held in Navarre in 2023, the forum has been consolidated as a reference space for the exchange of experiences and good practices in data management, essential for those seeking to lead the future of data management in public administrations.

Theday concluded with a proposal for continuity, highlighting the need to create a community of knowledge exchange between editions. Furthermore, the Principality of Asturias has applied to host the third edition of the forum, to be held in 2025, which demonstrates the growing interest in further consolidating this space for inter-institutional cooperation on data.

The   Big Data Test Infrastructure (BDTI) is a tool funded by the European Digital Agenda, which enables public administrations to perform analysis with open data and open source tools in order to drive innovation.

This free-to-use, cloud-based tool was created in 2019 to accelerate digital and social transformation. With this approach and also following the European Open Data Directive, the European Commission concluded that in order to achieve a digital and economic boost, the power of public administrations' data should be harnessed, i.e. its availability, quality and usability should be increased. This is how BDTI was born, with the purpose of encouraging the reuse of this information by providing a free analysis test environment that allows public administrations to prototype solutions in the cloud before implementing them in the production environment of their own facilities.

What tools does BDTI offer?

Big Data Test Infrastructure offers European public administrations a set of standard open source tools for storing, processing and analysing their data. The platform consists of virtual machines, analysis clusters, storage and network facilities. The tools it offers are:

• Databases: to store data and perform queries on the stored data. The BDTI currently includes a relational database(PostgreSQL), a document-oriented database(MongoDB) and a graph database(Virtuoso).
• Data lake: for storing large amounts of structured and unstructured data (MinIO). Unstructured raw data can be processed with deployed configurations of other building blocks (BDTI components) and stored in a more structured format within the data lake solution.
• Development environments: provide the computing capabilities and tools necessary to perform standard data analysis activities on data from external sources, such as data lakes and databases.
  
  • JupyterLab, an interactive, online development environment for creating Jupyter notebooks, code and data.
  • Rstudio, an integrated development environment for R, a programming language for statistical computing and graphics.
  • KNIME, an open source data integration, reporting and analytics platform with machine learning and data mining components, can be used for the entire data science lifecycle.
  • H2O.ai, an open sourcemachine learning ( ML) and artificial intelligence (AI) platform designed to simplify and accelerate the creation, operation and innovation with ML and AI in any environment.
• Advanced processing: clusters and tools can also be created to process large volumes of data and perform real-time search operations(Apache Spark, Elasticsearch and Kibana)
• Display: BDTI also offers data visualisation applications such as Apache Superset, capable of handling petabyte-scale data, or Metabase.
• Orchestration: for the automation of data-driven processes throughout their lifecycle, from preparing data to making data-driven decisions and taking actions based on those decisions, is offered:
  
  • Apache Airflow, an open source workflow management platform that allows complex data pipelines to be easily scheduled and executed.

Through these cloud-based tools, public workers in EU countries can create their own pilot projects to demonstrate the value that data can bring to innovation. Once the project is completed, users have the possibility to download the source code and data to continue the work themselves, using environments of their choice. In addition, civil society, academia and the private sector can participate in these pilot projects, as long as there is a public entity involved in the use case.

Success stories

These resources have enabled the creation of various projects in different EU countries. Some examples of use cases can be found on the BDTI website. For example, Eurostat carried out a pilot project using open data from internet job advertisements to map the situation of European labour markets. Other success stories included the optimisation of public procurement by the Norwegian Agency for Digitisation, data sharing efforts by the European Blood Alliance and work to facilitate understanding of the impact of COVID-19 on the city of Florence .

In Spain, BDTI enabled a data mining project atthe  Conselleria de Sanitat de la Comunidad Valenciana. Thanks to BDTI, knowledge could be extracted from the enormous amount of scientific clinical articles, a task that supported clinicians and managers in their clinical practices and daily work.

Courses, newsletter and other resources

 In addition to publishing use cases, theBig Data Test Infrastructure website offers an free online course to learn how to get the most out of BDTI. This course focuses on a highly practical use case: analysing the financing of green projects and initiatives in polluted regions of the EU, using open data from data.europa.eu and other open sources.

In addition, a monthly  newsletter on the latest BDTI news, best practices and data analytics opportunities for the public sector has recently been launched .

In short, the re-use of public sector data (RISP) is a priority for the European Commission and BDTI(Big Data Test Infrastructure) is one of the tools contributing to its development. If you work in the public administration and you are interested in using BDTI register here.

Open data is a source of information for the development of smart services, as well as for decision-making and policy-making. It is therefore not surprising that an increasing number of public bodies, in addition to opening data - for reuse by others and for reasons of accountability and transparency - are also reusing their own data for different purposes.

In this sense, the rise of smart city management platforms is encouraging many city councils and autonomous communities to develop smart applications and tools that take advantage of the use of data and analytical techniques to innovate and improve the public services they offer to citizens. Below, we show you several examples.

Resource optimisation

Open data can be used by public bodies to understand how public resources are being managed, as well as to promote actions that enable more efficient management and economic savings, e.g. in terms of energy consumption or by promoting more efficient resource management.

Energy consumption scorecard. Junta de Castilla y León.

This energy datahub, developed by the open data initiative of the Junta de Castilla y León, offers detailed and visual information on energy consumption in the centres managed by the Junta, such as educational centres, health centres, administrative offices or hospitals, among others.

It is a scorecard that gathers information from more than 1,500 consumption centres, offering different types of graphical representations that make it easier for the reader to understand the data. The data source used for the development of this platform can be consulted via this link.

The tool facilitates disaggregated analysis by type of energy and geographical location. This information may be of interest to citizens, but also to the Board's own managers. Thanks to this platform, between 2015 and the beginning of 2020, the Board saved more than 12 million euros in electricity.

In addition, the regional government has an electricity table that focuses exclusively on the electricity consumption of hospitals in Castilla y León on an hourly basis. The data is linked to meteorological information, so that future costs can be estimated and the use of heating can be optimised. The data used to develop this table can be consulted here.

Organic solid waste management. City Council of Santiago de Compostela.

The City Council of Santiago de Compostela has launched, within the Smartiago initiative, a project that aims to achieve a sustainable and intelligent management of municipal solid waste (MSW). The main objective of this tool is to design, develop and build smart surface containers for the characterisation of organic solid waste, based on the use of open IoT technologies, the application of machine learning algorithms and the use of open data as sources for the enrichment of community composting prediction models. This aims to achieve the 50% readiness for reuse and recycling target, up from the current 13%. The project, currently under development, will also include a gamification app to encourage good practices in sustainability.

Improving service delivery

Thanks to open data it is also possible to create tools for social service professionals to provide a better response and attention to the needs of citizens. Let's look at a couple of examples:

Civil protection map. Generalitat de Catalunya.

This interactive map shows the main resources of the civil protection system in Catalonia. The civil protection map allows you to see where the different risks are located (technological, environmental...) and the situation of the teams in order to better plan responses. Here you can consult the main source of data used by this tool.

Pharmacological Guide. Andalusian Regional Government.

This application has been designed by the Andalusian Regional Government to offer healthcare professionals a faster and more efficient consultation of the main drugs used in emergency care in Andalusia. It is a useful working tool for those healthcare professionals who aid in critical situations as it includes constantly updated and contrasted information on the main indications, doses, contraindications and interactions of the most commonly used drugs.

Decision-making and policy formulation

Open data provides greater knowledge about what is happening around us, enabling us to make better decisions. It is a very useful tool for public bodies to develop policies that respond to the real needs of citizens. Over the last year, we have seen how measures to prevent the spread of COVID-19 have been taken on the basis of data on the evolution of the disease. Other examples are:

The Noise Map. Valladolid City Council.

Valladolid City Council has a Noise Map that organises information on noise pollution. This map has been developed to be used in a compulsory way in the execution of the calculations foreseen in the different regulatory standards, as well as in the technical building code and which will apply to residential, institutional and industrial buildings, as well as in the technical building code and which will apply to residential, institutional and industrial buildings.

Intelligent tourism management platform. Conil Town Council.

Within the framework of Red.es' Smart Cities, Territories and Islands calls for proposals, we are finding more and more proposals that include the development of data management platforms that promote efficient decision-making. One example is the City Council of Conil de la Frontera, which is working with a smart tourism management platform to increase the knowledge of tourists, through the aggregation and centralisation of data related to the origin of the tourist, mobility and most visited areas, preferred places to visit and stay overnight or satisfaction surveys, among other parameters. In this way, the local administration can identify patterns and carry out actions to adapt and improve management, detect irregularities, promote economic and business development or favour the generation of employment in the priority areas identified. These data have also been used to estimate the real population during the pandemic and to make a better estimate of incidence rates. Although these data do not appear to be public for the moment, the aim is to open them to companies through an open data platform.

CitizenLab. Madrid City Council.

The regional government of Madrid, together with Grant Thornton, has launched a datalab to better understand citizen behaviour. The project seeks to analyse predictive models of citizen behaviour using Big Data and Artificial Intelligence (AI), with the aim of improving public services in the Madrid region in areas such as mobility, healthcare, tourism and infrastructure. In the last year, for example, it has been used to predict the demand for vaccines.

Undoubtedly, there are numerous applications and digital tools used by public administrations - and it seems that there will be more - that base their operation on open data to offer more and better services to citizens. In this article we have compiled some examples, but if you know of any related ones that may be of interest, do not hesitate to leave a comment or write to us at our email address dinamizacion@datos.gob.es.

Content prepared by the datos.gob.es team.