A large number of different data sources with different contents and formats coexist in an open data portal. It is therefore necessary to provide each file, resource or content on the network with a context or definition that allows people, and also machines, to interpret its meaning. This is where the concept of Linked data comes in.

Linked Data allows the web to be used as a single large global database. Following this publishing paradigm, data is available in context and interconnected for reuse. Linked Data emerged from the Semantic Web project inspired by Tim Berners-Lee, the father of the Web, from the need to introduce contextual information in the form of metadata on the Web.

The document "LinkedData as an open data model" briefly explains the basic concepts to understand how the semantic web and linked data works, such as the case of URIs or unique resource identifiers, ontologies or vocabularies that allow the description of relationships between them, to focus on how Aragon has implemented these technologies to develop different services, such as:

• The Interoperable Information Structure (EI2A), an ontology that homogenises structures, vocabularies and characteristics to respond to the diversity and heterogeneity of existing data within the Administration, within the framework of Aragon Open Data. The document explains some of the ontologies and vocabularies used for the development.
• The European Legislation Identifier (ELI), which allows online access to legislation in a formalised format that facilitates its reuse.
• The semantic infrastructure in Aragon Open Data, where the use of the Virtuoso tool for the storage of linked data stands out. The document explains the characteristics of this universal server, whose architecture allows the persistence of data in RDF-XML formats, among others. In addition, it explains how the bank that stores triplets in a native way for resources relationships works and shows examples of services of Aragon Open data that exploit these triplets of data as Aragopedia and Aragon Open Data Pool.

You can then download the full document (only available in Spanish).

This document is part of the series of educational materials and technological articles that Aragón open Data is producing in order to explain how they have deployed different solutions to respond to the needs for location, access and reuse of the different sets of data. You can complete your reading with another volume in the series: "How to implement CKAN: real case of the Aragon Open Data portal".

Aragon Open Data is one of the most active open data initiatives on the Spanish scene. In addition to the implementation, management and maintenance of an interoperable data catalogue, since its inception Aragon Open Data has carried out actions to bring the culture of open data closer to citizens, companies and all types of organisations. These initiatives include the development of services to offer the data and facilitate its reuse in a simple way such as Aragopedia, Open Social Data or the recent Aragón Open Data Focus (more information available in this interview).

Given the knowledge that they hold, it is not surprising that they have begun to develop educational materials and technological articles with the aim of explaining how they have deployed different solutions to respond to the needs of localisation, access and reuse of the different sets of data.

Below is one such material, which focuses on explaining how they have implemented the CKAN software solution to improve the availability of data on the portal.

CKAN as an open data management software solution in a real case for the Aragon Open Data portal

CKAN is a free, open-source platform developed by the Open Knowledge Foundation for publishing and cataloguing data collections. Due to its free and open nature, as well as its rapid implementation, it has become a worldwide reference for the opening of data.

Since its birth in 2012, Aragon Open Data has bet on CKAN technology for the management of its open data system. The document "CKAN, cornerstone for the management of an open data system" shows us how its architecture works and serves as an example for other initiatives that want to implement a platform of this type.

The document describes the challenges they encountered when migrating the original platform to a higher version and how they solved it by building a client application. This process resulted in the current architecture of the portal, which is shown in the figure below:

The CKAN backend is developed entirely in Python, with its own Javascript front end, and allows the deployment of a layer of services that can be managed from an API, and the use of base plugins or extensions that provide additional functionalities to the platform. CKAN is supported by a PostgreSQL database, where the datasets it houses, its resources and other metadata required for the operation of the platform are stored, and makes use of Solr, a search engine that helps to speed up the location and availability of the datasets.

In addition to explaining this architecture, the document discusses the functionalities and extensions used in the customised CKAN instance, and how the set of components integrated into the platform: Angular, NodeJS, PostgreSQL and Solr coexist to provide data sets that are the basis for the development of open data services and solutions such as Presupuestos de Aragón or the already mentioned Aragón Open Data Focus.

CKAN incorporates an extension that supports RFD data serialisation which, in addition to allowing the exposure of linked data in formats such as RDF-XML or Turtle, is used to federate datasets that follow the DCAT specification of metadata, making CKAN a more versatile and appropriate platform for the publication of Linked Data, something that Aragon Open Data has also done as we can see in this other document.

You can download the document "CKAN as an open data management software solution in a real case for the Aragon Open Data portal" below (only available in Spanish). You can also complement your reading with these two additional articles:

• Automatic collection of open data: Explains how Aragon Open Data federates open data using a CKAN plugin.
• ELK architecture as an open data tool: Explains how Aragon Open Data uses an architecture based on the ELK technology stack (Elasticsearch, Logstash and Kibana).

In Spain there are a large number of local, regional and state data initiatives. In order to harmonise this ecosystem, datos.gob.es is a single access point, so that re-users can easily find the information they require in a single space. In addition, datos.gob.es links to the European Data Portal (EDP), which means that the Spanish initiatives included in the catalogue are more visible at an international level. 

A series of simple steps must be followed to appear in the datos.gob.es catalogue. The first one is to request a user account, through this form. User accounts are reserved only for open data publishing bodies or entities; they are not necessary to access or download datasets from the catalogue. The following video (in Spanish) explains what you have to do to get your user account:

Once registered, the publishing user can register his / her datasets in two different ways:

1. Manual: This involves registering each dataset individually, completing a form for each dataset where its metadata are detailed manually.
2. Automatic (federated): The data registration and update are done periodically from a RDF file that include the metadata available through a url on the publisher website. It is no longer necessary to work individually with each dataset, but the process can automatically cover several datasets.

datos.gob.es also performs a comprehensive analysis to ensure that the metadata meets quality standards. Among other actions, metadata is checked for validity, broken links are analysed and distributions are checked.

The following infographic shows the process in a simple way. Click on the lateral arrows to change the slide. You can download the complete infographic at the end of the article.

If you have any questions or comments, you can contact datos.gob.es support team.

Natural language processing is making machines (computers) understand human language: spoken or in the form of text. More formally, natural language processing is a hybrid field between computer science and linguistics, which uses different techniques, some of them based on artificial intelligence, to interpret human language.

In this report, prepared by the digital transformation expert Alejandro Alija, we will see how natural language processing is much closer to our day-to-day life than we may initially think. Applications such as automatic translation of texts; sentiment analysis in social networks; the searches we carry out on the internet; the generation of meteorological summaries or the simple requests that we make to our smart speaker, have a strong technological component of natural language processing.

The specific weight that natural language processing has (and will have) in industry and the economy is increasing, since most of the data that is produced in the world (mainly through the Internet) is data in the form of texts and voice (unstructured data). Open data plays a crucial role for this technology. The artificial intelligence algorithms that are used to analyze and understand natural language require a huge amount of quality data to be trained. Many of these data come from the open data repositories of both public and private institutions.

Throughout this report, the history of natural language processing is reviewed, from its inception to the present day. Additionally, the Inspire section describes some of the most representative use cases that harness the potential of natural language processing. The prediction of text when writing a new email, the classification of texts in categories or the generation of false news, are just some of the cases that are reviewed in this report.

Finally, for those more enthusiastic readers, in the Action section, a complete use case (using programming tools) is developed on sentiment analysis in conversations about citizen public debates.

The report ends with a list of resources and readings for those users who wish to continue expanding their knowledge of Artificial Intelligence.

You can download the full report and other additional materials at the following links:

Note: The published code is intended to be a guide for the reader, but may require external dependencies or specific configurations for each user who wants to run it.

We release a new series of reports in datos.gob.es, which under the methodology “Awareness, Inspire, Action” tries to explain how different emerging technologies work and their relationship with open data. The objective is to introduce the reader to the subject through the use of practical, simple and recognizable use cases.

The first report of the series is dedicated to Artificial Intelligence. We can define Artificial Intelligence (AI) as the ability of a machine to mimic human intelligence. This technology will have a great impact on our lives, in two ways: the automation of daily, routine and dangerous tasks and the increase of human capacities, helping to strengthen the work force of the future.

The report has been prepared by Alejandro Alija, expert in Digital Transformation and Innovation, and addresses the following contents:

• The report begins with the Awareness section where the concept of AI is explained in a simple way, briefly outlining two of its sub-fields: Machine Learning and Deep Learning. This section also includes a brief historical review, where the evolution of AI is reviewed, and the factors that make it possible are compiled and explained.
• Next, in the Inspire section, we deep on the AI use cases. For this, the author has taken as reference his two areas of impact: AI as an amplifier of human language, with tasks such as reports translation or conversion of written to spoken language (and vice versa), and AI as an extension of human vision, illustrated through examples of the use of image recognition and classification.
• Finally, in the Action section one of the use case mentioned in the Inspire section is developed: the recognition and classification of images. For them, a set of images has been selected available in the data catalogue of data.gob.es (the photographic archive of the Basque Government: images about Euskadi and the Government activity). Using AI tools, the images have been classified and their description noted. This example can be replicated by the reader since the code necessary for its development has been made available.

The report ends with a list of resources and readings for those users who wish to continue expanding their knowledge about Artificial Intelligence.

You can also download the full report and other additional materials in the following links:

Note: The published code is intended to be a guide for the reader, but may require external dependencies or specific configurations for each user who wants to run it.

Open data is one of the key elements of smart cities. The collection of information, its analysis and its use make possible to address many of the challenges facing cities today, such as the creation of public services that respond to a growing population.

Among all the open datasets that are published related to cities, real-time data provides multiple advantages. Knowing the situation of our cities in real time can serve to make decisions and improve efficiency in urban mobility, energy management or environmental conditions, among other aspects.

In this context, the report "Open data in real time: use cases for smart cities" seeks to boost the opening of this type of data showing the advantages of its use. The report analyses the relationship between open data and smart cities, and shows a series of datasets that local entities should publish in real time, according to the report “Open Data 2019 - 40 datasets to be published by Local Entities”,  elaborated by the FEMP (Spanish Federation of Municipalities and Provinces). These data sets belong to the fields of transport and mobility - public car park, public bicycles, traffic, public transport - and the environment - air quality and noise pollution.

Each dataset has been analysed highlighting some use cases and reuse examples, paying special attention to the positive impact they have on citizens. The technologies involved in its deployment, the stakeholders or future challenges, among other factors, have also been addressed.

The conclusions of the analysis are collected in each of the files that you can see below:

Datasets

 

You can also download the full report and other additional materials using the following links:

On September 25, the Secretary of State for Digital Advance organizes the Infoday about language technologies. The event is part of the XXXV International Conference of the SEPLN (Spanish Society for Natural Language Processing) and the dissemination activities of the Plan for the Advancement of Language Technologies, whose objective is to promote the development of natural language processing and automatic translation in Spanish and co-official languages.

With this event, the organizers want to show and highlight the importance of natural language processing campaigns in all areas, but especially the field of health and biomedicine, as well as raise awareness of the different elements necessary for language technology projects come to fruition, such as open data.

The event will take place in the morning from 9:00 a.m. to 2:00 p.m. at the headquarters of the University of the Basque Country, in Bilbao (Avenida Abandoibarra, 3), and it is divided into two parts:

• Part I: Developments in the Plan for the Advacement Language Technologies (TL Plan). In the first part of the event, the main initiatives that are being carried out within the TL Plan will be addressed. The focus will be on some highlights, such as linguistic infrastructures and European machine translation projects. In addition, the results of some of the latest studies will be shown. One of these studies is “Reusable data as linguistic resources”, whose presentation will be defended by Leonardo Campillos, of the Autonomous University of Madrid (UAM), and which has been carried out with funding from the Secretary of State for Digital Advancement and Red.es within of the scope of the TL Plan.
• Part II: Health assessment campaigns. In the second part, the situation of the different campaigns carried out in the field of health and biomedicine will be analysed, paying special attention to anonymization tasks. For this, two round tables will be held, under the title of  “Evaluation campaigns, experiences, needs, impact and vision of participants” and “Protection of health data, legal aspects, knowledge transfer, clinical PLN solutions and opportunities for the TL academy and industry”.

Through this agenda, the organizers seek to generate a space to sharing experiences, which allow us to avoid duplication and take advantage of synergies between the different actors involved in the universe of language technologies: public entities, private companies, academic sector, researchers, etc.

The attendance to the event is free, but it is necessary to register previously through this link.

The European Data Portal (EDP) offers users an online training program, designed to disseminate what open data is and how they are changing the lives of all the inhabitants of our planet. This program consists of 16 modules, which introduce different aspects of the open data ecosystem: basic concepts, present and future trends, success stories and good practices in data publication, access and use.

Until now, these contents were available in languages ​​such as English and French, but, thanks to the collaboration with the Aporta Initiative, the EDP has just published all the modules in Spanish.

The training materials are aimed at all types of users interested in the open data world, from basic users who want to get a general idea to experts in the field. Each module can take between 15-30 minutes, although each provides two hours of additional content for advanced users who want to deepen certain aspects.

The EDP recommend completing the sixteen modules in order to obtain a solid knowledge base on the different aspects of open data. However, if you prefer to focus on a particular topic, you can go directly to the corresponding module.

The 16 modules already available in Spanish are:

Didactic units

Esta obra está bajo una licencia de Creative Commons Reconocimiento-CompartirIgual 4.0 Internacional.

In the digital world, data becomes a fundamental asset for companies. Thanks to them, they can better understand their environment, business and competition, and make convenient decisions at the right time.

In this context, it is not surprising that an increasing number of companies are looking for professional profiles with advanced digital capabilities. Workers who are able to search, find, process and communicate exciting stories based on data.

The report "How to generate value from data: formats, techniques and tools to analyse open data" aims to guide those professionals who wish to improve the digital skills highlighted above. It explores different techniques for the extraction and descriptive analysis of the data contained in the open data repositories.

The document is structured as follows:

• Data formats. Explanation of the most common data formats that can be found in an open data repository, paying special attention to csv and json.
• Mechanisms for data sharing through the Web. Collection of practical examples that illustrate how to extract data of interest from some of the most popular Internet repositories.
• Main licenses. The factors to be considered when working with different types of licenses are explained, guiding the reader towards their identification and recognition.
• Tools and technologies for data analysis. This section becomes slightly more technical. It shows different examples of extracting useful information from open data repositories, making use of some short code fragments in different programming languages.
• Conclusions. A technological vision of the future is offered, with an eye on the youngest professionals, who will be the workforce of the future.

The report is aimed at a general non-specialist public, although those readers familiar with data treatment and sharing o in the web world will find a familiar and recognizable reading.

Next, you can then download the full text, as well as the executive summary and a presentation.

Note: The published code is intended as a guide for the reader, but may require external dependencies or specific settings for each user who wishes to run it.