datos abiertos

This application designed for iOS devices offers a wide range of tourist activities in the Autonomous Community of Castilla y León. It acts as a travel assistant, allowing you to create an itinerary according to the interests of each user.

TUrMISMO allows you to discover activities to do in the area, save your favourite places or plans, and trace your own route. To do this, it offers geolocated information on places as diverse as tourist offices, restaurants and wineries, organised excursions and ski schools, among many others.

The app was presented this year 2024 to the VII Open Data Competition of Castilla y León and uses open data provided by the Junta de Castilla y León.

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.

The Provincial Council of Bizkaia the University of the Basque Country (UPV/EHU) and the Bilbao City Council collaborate in the Bilbao Bizkaia Open Data Classroom an initiative that aims to develop the use of open data from the two Biscayan institutions (Provincial Council and City Council) for use in university projects. The ultimate goal is that, thanks to this re-use, public services can be improved and new knowledge can be generated to contribute to the resolution of social problems.

The initiative, aimed at university students as well as teaching and research staff, was born as a way to research staff, was born as a a collaboration agreement between the three administrations (Provincial Council of Bizkaia, Bilbao City Council and UPV/EHU). For this purpose, other agreements made with the Bilbao School of Engineering for the creation of Business Classrooms were taken as a reference, but in this case it will be an open data classroom, which will promote the opening of data generated and the reuse of public information.

The Bilbao Bizkaia Open Data Classroom has been in operation since 2022 and its operation is similar to that of the twelve Business Classrooms that were already in operation at the Bilbao School of Engineering. These company classrooms are laboratory-classrooms within the school, created and financed by companies and institutions to promote their innovation activities. In this sense, as the organisers of the Aula state, "they are an effective instrument of collaboration between the Departments of the Bilbao School of Engineering and the business world, both in activities related to research, technological development and innovation and in everything related to training".

Open data for innovation in the classroom

 In addition to developing projects based on the reuse of open data that improve the services provided by the regional and municipal authorities, the Aula also creates data visualisations based on open information processing initiatives proposed by the university community with the aim of improving the welfare of citizens. Another of its areas of work is the implementation of training activities that contribute to the improvement of the digital skills of the university community.

During the first edition of the Bilbao-Bizkaia Open Data Classroom, in the 2022-2023 academic year, the students developed projects on the reuse of data on recycling or outdoor activities, among others. All of them were created using regional data. You can consult the projects here: https://sites.google.com/view/opendatabilbaobizkaia/home?authuser=0.

How can I join Aula Open Data Bilbao-Bizkaia?

The Aula Open data Bilbao Bizkaia has its own space in the headquarters of the Bilbao School of Engineering, in San Mamés. This space has been fitted out thanks to a grant awarded by the Provincial Council of Bizkaia and the City Council of Bilbao, which also collaborate by financing the management costs of the classroom.

The programme is aimed at engineering bachelor's and master's degree students carrying out their bachelor's and master's degree final projects, respectively. However, it is not necessary to be in the final year of a Bachelor's or Master's degree to participate in the Aula. The initiative is open to anyone with an interest in data.

Training in Power BI and data analysis toolsis provided at the beginning of the course.

The programme is free of charge, and students working under the agreement are paid. The selection process is by CV.

In the following link you can find all the information about the Classroom.

https://www.aulaopendatabilbaobizkaia.eus/aula_es.html

After months of new developments, the pace of advances in artificial intelligence does not seem to be slowing down - quite the contrary. A few weeks ago, when reviewing the latest developments in this field on the occasion of the 2023 deadline, video generation from text instructions was considered to be still in its infancy. However, just a few weeks later, we have seen the announcement of SORA. With this tool, it seems that the possibility to generate realistic videos, up to one minute long, from textual descriptions is here.

Every day, the tools we have access to become more sophisticated and we are constantly amazed by their ability to perform tasks that once seemed exclusive to the human mind. We have quickly become accustomed to generating text and images from written instructions and have incorporated these tools into our daily lives to enhance and improve the way we do our jobs. With each new development, pushing the boundaries a little further than we imagined, the possibilities seem endless.

Advances in Artificial Intelligence, powered by open data and other technologies such as those associated with the Web3, are helping to rethink the future of virtually every field of our activity: from solutions to address the challenges of climate change, to artistic creation, be it music, literature or painting[6], to medical diagnosis, agriculture or the generation of trust to drive the creation of social and economic value.

In this article we will review the developments that impact on a field where, in the coming years, interesting advances are likely to be made thanks to the combination of artificial intelligence and open data. We are talking about the design and planning of smarter, more sustainable and liveable cities for all their inhabitants.

Urban Planning and Management

Urban planning and management is complicated because countless complex interactions need to be anticipated, analysed and resolved. Therefore, it is reasonable to expect major breakthroughs from the analysis of the data that cities increasingly open up on mobility, energy consumption, climatology and pollution, planning and land use, etc. New techniques and tools provided by generative artificial intelligence combined, for example, with intelligent agents will allow a deeper interpretation and simulation of urban dynamics.

In this sense, this new combination of technologies could be used for example to design more efficient, sustainable and liveable cities, anticipating the future needs of the population and dynamically adapting to changes in real time. Thus, new smart urban models would be used to optimise everything from traffic flow to resource allocation by simulating behaviour through intelligent agents.

Figure 1: Images generated by Urbanistai.com

 

Urbanist.ai is one of the first examples of an advanced urban analytics platform, based on generative artificial intelligence, that aims to transform the way urban planning tasks are currently conceived.  The services it currently provides already allow the participatory transformation of urban spaces from images, but its ambition goes further and it plans to incorporate new techniques that redefine the way cities are planned. There is even a version of UrbanistAI designed to introduce children to the world of urban planning.

Going one step further, the generation of 3D city models is something that tools such as InfiniCity have already made available to users. Although there are still many challenges to be overcome, the results are promising. These technologies could make it substantially cheaper to generate digital twins on which to run simulations that anticipate problems before they are built.

Available data

However, as with other developments based on Generative AI, these issues would not be possible without data, and especially not without open data.  All new developments in AI use a combination of private and public data in their training, but in few cases is the training dataset known with certainty, as it is not made public. Data can come from a wide variety of sources, such as IoT sensors, government records or public transport systems, and is the basis for providing a holistic view of how cities function holistic view of how cities function and how and how their inhabitants interact with the urban environment.

The growing importance of open data in training these models is reflected in initiatives such as the Task Force on AI Data Assets and Open Government, launched by the US Department of Commerce, which will be tasked with preparing open public data for Artificial Intelligence. This means not only machine-readable formats, but also machine-understandable metadata. With open data enriched by metadata and organised in interpretable formats, artificial intelligence models could yield much more accurate results.

A long-established and basic data source is OpenStreetmap (OSM), a collaborative project that makes a free and editable map of open global geographic dataavailable to the community. It includes detailed information on streets, squares, parks, buildings, etc. which is crucial as a basis for urban mobility analysis, transport planning or infrastructure management. The immense cost of developing such a resource is only within the reach of large technology companies, making it invaluable to all initiatives that use it as a basis.

 

Figure 2: OpenStreetmap Images (OSM)

 

More specific datasets such as HoliCity, a 3D data asset with rich structural information, including 6,300 real-world views, are proving valuable. For example, recent scientific work based on this dataset has shown that it is possible for a model fed with millions of street images to predict neighbourhood characteristics, such as home values or crime rates.

Along these lines, Microsoft has released an extensive collection of building contours automatically generated from satellite imagery, covering a large number of countries and regions.

 

Figure 3: Urban Atlas Images (OSM)

Microsoft Building Footprints provide a detailed basis for 3D city modelling, urban density analysis, infrastructure planning and natural hazard management, giving an accurate picture of the physical structure of cities.

We also have Urban Atlas, an initiative that provides free and open access to detailed land use and land cover information for more than 788 Functional Urban Areas in Europe. It is part of the Copernicus Land Monitoring Serviceprogramme, and provides valuable insights into the spatial distribution of urban features, including residential, commercial, industrial, green areas and water bodies, street tree maps, building block height measurements, and even population estimates.

Risks and ethical considerations

However, we must not lose sight of the risks posed, as in other domains, by the incorporation of artificial intelligence into the planning and management of cities, as discussed in the UN report on "Risks, Applications and Governance of AI for Cities". For example, concerns about privacy and security of personal information raised by mass data collection, or the risk of algorithmic biases that may deepen existing inequalities. It is therefore essential to ensure that data collection and use is conducted in an ethical and transparent manner, with a focus on equity and inclusion.

This is why, as city design moves towards the adoption of artificial intelligence, dialogue and collaboration between technologists, urban planners, policy makers and society at large will be key to ensuring that smart city development aligns with the values of sustainability, equity and inclusion. Only in this way can we ensure that the cities of the future

are not only more efficient and technologically advanced, but also more humane and welcoming for all their inhabitants.

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Content prepared by Jose Luis Marín, Senior Consultant in Data, Strategy, Innovation & Digitalization. The contents and views reflected in this publication are the sole responsibility of the author.

The Sustainable Development Goals (SDGs) are a set of targets adopted by the international community aimed at addressing the most pressing challenges of our time. These goals were born simultaneously with the Global Partnership for Sustainable Development Data and the International Open Data Charter, which provided a coalition of experts willing to harness the benefits of open data for the new development agenda.

In this regard, open data plays a very relevant role within the development agenda as indicators of progress towards the SDGs, as they allow measuring and evaluating their progress, as well as improving accountability through sharing that data with the rest of the community, providing great value in multiple ways:

• Facilitating decision-making when designing policies and strategies to help meet the objectives;
• Identifying inequalities and specific challenges among different regions or population groups;
• Improving efficiency in policy and program implementation;
• As an engine of innovation through research and development.

Today, there are large global databases, both generalist and thematic, that we can use for these purposes, in addition to all the national data sources available in our own country. However, there is still a long way to go in this regard: the proportion of SDG indicators that are conceptually clear and have good national coverage is still 66%, according to the latest SDG progress report published in 2023. This leads us to continue facing data gaps in vital areas such as poverty, hunger, education, equality, sustainability, climate, seas, and justice, among others. Additionally, there is also a fairly general and significant lack of data disaggregated by age and/or sex, making it very difficult to properly monitor the potential progress of the objectives regarding the most vulnerable population groups.

This report takes a journey through the dual role that open data plays in supporting national and global progress in achieving the SDGs. The first part of the report focuses on the better-known role of open data as mere indicators when measuring progress towards the objectives, while the second part addresses its role as a key tool and fundamental raw material for the development of society in general and for the achievement of the objectives themselves in particular. To this end, it explores which datasets could have the greatest potential in each case, showing some practical examples, both national and at the European level, in various specific development objectives.

If you want to learn more about the content of this report, you can watch the interview with its author.

The awards ceremony for the seventh edition of the Castilla y León open data competition was held on Monday 12 February seventh edition of the Castilla y León open data competition, which aims to recognise and value the good use of open dataas well as promoting and encouraging its use and exploitation.

The competition, which has been running since 2016, aims to to raise interest in open data and the and the multiple economic possibilities associated with it. In this way, the initiative, organised by the Regional Ministry of the Presidency of the Junta de Castilla y Leónthe initiative, organised by the Regional Ministry of the Presidency of Castile and Leon, recognises projects that generate ideas, studies, services, websites or mobile applications. As has been the case in previous editions, the common denominator of the entries in this competition is the use of datasets from the Open Data Portal of the Junta de Castilla y León.

Thirty-two entries were submitted in this call, of which eight were awarded in one of the four categories eight of them have been awarded in one of the four categories: Ideas, Products and Services, Didactic Resource and Data Journalism.

Eight award-winning projects in this edition of the competition

The winners in the different categories, chosen from the 32 entries submitted, were:

Category Ideas:

• First prize of 1500 €: Health supply in Castilla y León / Dashboard - Author: Almudena María Moreno Maderuelo.
  
  • Scorecard related to public health in Castilla y León, based on open data.
• Second prize of 500 €: "Geographical names and their oral transmission" - Author: Guillermo Herrero Gacimartín.
  
  • An idea to take advantage of open data to promote the conservation and dissemination of the wealth of geographical names and histories of the peoples of our autonomous community.

Category Products and Services:

• First prize of 2500 €: EnergyCyl. Boosting energy efficiency through energy analysis in Castilla y León  - Author: David Aparicio Sanz.
  
  • Web application that compiles, analyses and provides detailed information on the energy sector in the autonomous community of Castilla y León.
• Second prize 1500 €: Active Territories Project.Webmapping for the characterisation and sustainable promotion of innovative initiatives in the rural environment of Castilla y León - Authors: Víctor Pérez Eguíluz, María A. Castrillo Romón, Elvira Khairulina, José Luis Lalana Soto and Enrique Rodrigo González.
  
  • Website of the "Territorios Activos" project to study innovation in the context of rural environments in the autonomous community of Castilla y León.
• Third prize 500 €: Anomalous pattern monitoring for operational optimisation of logistics infrastructures - Author: Unai Beristain.
  
  • Open data and IoT solution for logistics management and early detection of anomalous patterns in logistics infrastructures. 3D web map based on open data.
• Student prizes of €1500: Offers for young people in Castilla y León - Authors: Ismael Martín Moakil, Alberto Herrero Jiménez, Oscar Antona Gutierrez, Daniel Herranz Herranz, Alberto Aguilar García, Joel Garrido Hernández, Rafael Martín Domínguez and Alonso Gallego. IES Alonso de Madrigal (Ávila).
  
  • App for Android that allows you to find out about discounts and promotions for young people with the Carnet Joven de Castilla y León (Youth Card of Castilla y León)

Didactic Resource Category:

• First prize: 1500 €: CHEST: an application to support the creation and reuse of ubiquitous educational experiences related to cultural heritage around the world - Authors: Pablo García Zarza, Guillermo Vega Gorgojo, Miguel L. Bote Lorenzo, Juan I. Asensio Pérez, Eduardo Gómez Sánchez and Yannis Dimitriadis.
  
  • Application to support teachers in the design and implementation of ubiquitous learning when teaching subjects related to cultural heritage.

Data Journalism Category:

• First prize of 1500 €: what is life like without a bar? How the villages manage to play the game - Authors: Ana Isabel Ruíz Espinar, Marta Ley and Guillermo Cid.
  
  • Journalistic article that analyses how the existence of hotel and catering establishments affects the municipalities of Castilla y León.

The Junta de Castilla y León has published a list of all the projects that entered the competition, available on its website: https://datosabiertos.jcyl.es/web/es/concurso-datos-abiertos/proyectos-presentados.html

During the awards ceremony, the Minister of the Presidency of the Junta de Castilla y León, Luis Miguel González Gago, insisted on the premise of continuing to improve the presentation and accessibility of open data accessibility of open data. In this sense, the aim is to improve the visualisation of the data presented by all the departments of the Junta de Castilla y León, which in a homogeneous and coordinated way will use the same presentation schemes so that they can be easily located, understood and interpreted easily located, understood and interpreted by citizens by citizens. A commitment to interoperability.

This mobile application developed by the City Council of Ourense allows you to consult updated information about the city: news, notices or upcoming events on different topics such as: 

• Arts and festivities: Cultural events organized by the city council.
• Tourism: Information about thermal facilities, tourist attractions, heritage, routes and gastronomy.
• Notifications: Real time notifications about possible traffic cuts, opening of monuments or other specific issues.  
• Information: Data of general interest such as emergency telephone numbers or citizen services of the city council. 

The mOUbil app, developed through local open data sets, unifies all the information of interest to the neighbors of Ourense, as well as tourists who want to know the city. In addition, anyone can make suggestions for improvement on the application through this form: Queries and Suggestions (ourense.gal).  

Your download is available for both Android mOUbil - Ourense no peto! - Apps in Google Play and iOS: moubil - Ourense no peto! in App Store (apple.com)

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

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

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

What is data governance?

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

How was the FEMP Data Governance Ordinance developed?

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

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

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

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

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

New features and structure of the Data Governance Ordinance

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

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

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

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

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

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

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

The Centre de documentació i biblioteca del Institut Català d'Arqueologia Clàssica (ICAC) has the repository Open Science ICAC. This website is a space where science is shared in an accessible and inclusive way. The space introduces recommendations and advises on the process of publishing content. Also, on how to make the data generated during the research process available for future research work.

The website, in addition to being a repository of scientific research texts, is also a place to find tools and tips on how to approach the research data management process in each of its phases: before, during and at the time of publication.

• Before you begin: create a data management plan to ensure that your research proposal is as robust as possible. The Data Management Plan (DMP) is a methodological document that describes the life cycle of the data collected, generated and processed during a research project, a doctoral thesis, etc.
• During the research process: at this point it points out the need to unify the nomenclature of the documents to be generated before starting to collect files or data, in order to avoid an accumulation of disorganised content that will lead to lost or misplaced data. In addition, this section provides information on directory structure, folder names and file names, the creation of a txt file (README) describing the nomenclatures or the use of short, descriptive names such as project name/acronym, file creation date, sample number or version number. Recommendations on how to structure each of these fields so that they are reusable and easily searchable can also be found on the website.
• Publication of research data: in addition to the results of the research itself in the form of a thesis, dissertation, paper, etc., it recommends the publication of the data generated by the research process itself. The ICAC itself points out that research data remains valuable after the research project for which it was generated has ended, and that sharing data can open up new avenues of research without future researchers having to recreate and collect identical data. Finally, it outlines how, when and what to consider when publishing research data.

Graphical content for improving the quality of open data

Recently, the ICAC has taken a further step to encourage good practice in the use of open data. To this end, it has developed a series of graphic contents based on the "Practical guide for the improvement of the quality of open data"produced by datos.gob.es. Specifically, the cultural body has produced four easy-to-understand infographics, in Catalan and English, on good practices with open data in working with databases and spreadsheets, texts and docs and CSV format.

All the infographics resulting from the adaptation of the guide are available to the general public and also to the centre's research staff at Recercat, Catalonia's research repository. Soon it will also be available on the Open Science website of the Institut Català d'Arqueologia Clàssica (ICAC)open Science ICAC.

The infographics produced by the ICAC review various aspects. The first ones contain general recommendations to ensure the quality of open data, such as the use of standardised character encoding, such as UTF-8, or naming columns correctly, using only lowercase letters and avoiding spaces, which are replaced by hyphens. Among the recommendations for generating quality data, they also include how to show the presence of null or missing data or how to manage data duplication, so that data collection and processing is centralised in a single system so that, in case of duplication, it can be easily detected and eliminated.

The latter deal with how to set the format of thenumerical figures and other data such as dates, so that they follow the ISO standardised system, as well as how to use dots as decimals. In the case of geographic information, as recommended by the Guide, its materials also include the need to reserve two columns for inserting the longitude and latitude of the geographic points used.

The third theme of these infographics focuses on the development of good databases or spreadsheets databases or spreadsheetsso that they are easily reusable and do not generate problems when working with them. Among the recommendations that stand out are consistency in generating names or codes for each item included in the data collection, as well as developing a help guide for the cells that are coded, so that they are intelligible to those who need to reuse them.

In the section on texts and documents within these databases, the infographics produced by the Institut Català d'Arqueologia Clàssica include some of the most important recommendations for creating texts and ensuring that they are preserved in the best possible way. Among them, it points to the need to save attachments to text documents such as images or spreadsheets separately from the text document. This ensures that the document retains its original quality, such as the resolution of an image, for example.

Finally, the fourth infographic that has been made available contains the most important recommendations for working with CSV format working with CSV format (comma separated value) format, such as creating a CSV document for each table and, in the case of working with a document with several spreadsheets, making them available independently. It also notes in this case that each row in the CSV document has the same number of columns so that they are easily workable and reusable, without the need for further clean-up.

As mentioned above, all infographics follow the recommendations already included in the Practical guide for improving the quality of open data.

The guide to improving open data quality

The "Practical guide for improving the quality of open data" is a document produced by datos.gob.es as part of the Aporta Initiative and published in September 2022. The document provides a compendium of guidelines for action on each of the defining characteristics of quality, driving quality improvement. In turn, this guide takes the data.europe.eu data quality guide, published in 2021 by the Publications Office of the European Union, as a reference and complements it so that both publishers and re-users of data can follow guidelines to ensure the quality of open data.

In summary, the guide aims to be a reference framework for all those involved in both the generation and use of open data so that they have a starting point to ensure the suitability of data both in making it available and in assessing whether a dataset is of sufficient quality to be reused in studies, applications, services or other.

The Open Government Guide for Public Employees is a manual to guide the staff of public administrations at all levels (local, regional and state) on the concept and conditions necessary to achieve an "inclusive open government in a digital environment". Specifically, the document seeks for the administration to assume open government as a cross-cutting element of society, fostering its connection with the Sustainable Development Goals. 

 It is a comprehensive, practical and well-structured guide that facilitates the understanding and implementation of the principles of open government, providing examples and best practices that foster the development of the necessary skills to facilitate the long-term sustainability of open government.

What is open government?

The guide adopts the most widely accepted definition of open government, based on three axes: 

• Transparency and access to information (vision axis): Refers to open access to public information to facilitate greater accountability.
• Citizen participation (voice axis): It offers the possibility for citizens to be heard and intervene to improve decision-making and co-creation processes in public policies.
• Collaboration (value axis): Focuses on cooperation within the administration or externally, with citizens or civil society organizations, through innovation to generate greater co-production in the design and implementation of public services.

This manual defines these axes and breaks them down into their most relevant elements for better understanding and application. According to the guide, the basic elements of open administration are:

• An integrity that cuts across all public action.
• Data are "the raw material of governments and public administrations" and, for this reason, must be made available to "any actor", respecting the limits established by law.  The use of information and communication technologies (digital) is conceived as a "space for the expansion of public action", without neglecting the digital divide.
• The citizenry is placed at the center of open administration, because it is not only the object of public action, but also "must enjoy a leading role in all the dynamics of transparency, participation and collaboration".
• Sustainability of government initiatives.

Adapted from a visual of the Open Government Guide for Public Employees. Source: https://funcionpublica.hacienda.gob.es/Secretaria-de-Estado-de-Funcion-Publica/Actualidad/ultimas-noticias/Noticias/2023/04/2023_04_11.html

Benefits of Open Government

With all this, a number of benefits are achieved:

• Increased institutional quality and legitimacy

• Increased trust in institutions

• More targeted policies to serve citizens

• More equitable access to policy formulation

How can I use the guide?

The guide is very useful because, in order to explain some concepts, it poses challenges so that civil servants themselves can reflect on them and even put them into practice. The authors also propose cases that provide an overview of open government in the world and its evolution, both in terms of the concepts related to it and the laws, regulations, relevant plans and areas of application (including Law 19/2023 on transparency, the Digital Spain 2025 agenda, the Digital Rights Charter and the General Data Protection Regulation, known as RGPD). As an example, the cases he mentions include the Elkar-EKIN Social Inclusion Plan of the Provincial Council of Gipuzkoa and Frena La Curva, an initiative launched by members of the Directorate General of Citizen Participation and the LAAAB of the Government of Aragon during COVID-19.

The guide also includes a self-diagnostic test on accountability, fostering collaboration, bibliographical references and proposals for improvement.

 In addition, it offers diagrams and summaries to explain and schematize each concept, as well as specific guidelines to put them into practice. For example, it includes the question "Where are the limits on access to public information? To answer this question, the guide cites the cases in which access can be given to information that refers to a person's ideology, beliefs, religious or union affiliation (p. 26). With adaptation to specific contexts, the manual could very well serve as a basis for organizing training workshops for civil servants because of the number of relevant issues it addresses and its organization.

The authors are right to also include warnings and constructive criticisms of the situation of open government in institutions. Although they do not point out directly, they talk about:

• Black boxes: they are criticized for being closed systems. It is stated that black boxes should be opened and made transparent and that "the representation of sectors traditionally excluded from public decisions should be increased".
• Administrative language: This is a challenge for real transparency, since, according to a study mentioned in the guide, out of 760 official texts, 78% of them were not clear. Among the most difficult to understand are applications for scholarships, grants and subsidies, and employment-related procedures.
• The existence of a lack of transparency in some municipalities, according to another study mentioned in the guide. The global open government index, elaborated by the World Justice Project, places Spain in 24th place, behind countries such as Estonia (14th), Chile (18th), Costa Rica (19th) or Uruguay (21st) and ahead of Italy (28th), Greece (36th) or Romania (51st), among 102 countries. Open Knowledge Foundation has stopped updating its Global Open Data Index, specifically on open data.

In short, public administration is conceived as a step towards an open state, with the incorporation of the values of openness in all branches of government, including the legislative and judicial branches, in addition to government.

Additional issues to consider

For those who want to follow the path to open government, there are a number of issues to consider: 

• The guide can be adapted to different spheres and scales of public. But public administration is not homogeneous, nor do the people in it have the same responsibilities, motivations, knowledge or attitudes to open government. A review of citizen use of open data in the Basque administration concluded that one obstacle to transparency is the lack of acceptance or collaboration in some sectors of the administration itself. A step forward, therefore, could be to conduct internal campaigns to disseminate the advantages for the administration of integrating citizen perspectives and to generate those spaces to integrate their contributions.

• Although the black box model is disappearing from the public administration, which is subject to great scrutiny, it has returned in the form of closed and opaque algorithmic systems applied to public administration. There are many studies in the scientific literature -for example, this one- that warn that erroneous opaque box systems may be operating in public administration without anyone noticing until harmful results are generated. This is an issue that needs to be reviewed.
•  In order to adapt it to specific contexts, it should be possible to define more concretely what participation, collaboration and co-creation are. As the guide indicates, they imply not only transparency, but also the implementation of collaborative or innovative initiatives. But it is also necessary to ask a series of additional questions: what is a collaborative or innovation initiative, what methodologies exist, how is it organized and how is its success measured?
• The guide highlights the need to include citizens in open government. When talking about inclusion and participation, organized civil society and academia are mentioned above all, for example, in the Open Government Forum. But there is room for improvement to encourage individual participation and collaboration, especially for people with little access to technology. The guide mentions gender, territorial, age and disability digital divides, but does not explore them. However, when access to many public services, aid and assistance has been platformized (especially after the COVID-19 pandemic), such digital divides affect many people, especially the elderly, low-income and women. Since a generalist guide cannot address all relevant issues in detail, this would merit a separate guide.

Public institutions are increasingly turning to algorithmic decision-making for effective, fast and inclusive decision making. Therefore, it is also increasingly relevant to train the administration itself in open government in a digitized, digitized and platformized environment. This guide is a great first step for those who want to approach the subject.

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.