24 posts found
How to ensure the authenticity of satellite imagery
Synthetic images are visual representations artificially generated by algorithms and computational techniques, rather than being captured directly from reality with cameras or sensors. They are produced from different methods, among which the antagonistic generative networks (Generative Adversarial…
DCAT-AP-ES: A step forward in open data interoperability
Context and need for an update
Data is a key resource in the digital transformation of public administrations. Ensuring its access, interoperability and reuse is fundamental to improve transparency, foster innovation and enable the development of efficient public services centered on citizens.
In th…
How to build a citizen science initiative considering open data from the start
Citizen participation in the collection of scientific data promotes a more democratic science, by involving society in R+D+i processes and reinforcing accountability. In this sense, there are a variety of citizen science initiatives launched by entities such as CSIC, CENEAM or CREAF, among oth…
HealthDCAT-AP: The Standard That Connects Health Data to People
Data is the engine of innovation, and its transformative potential is reflected in all areas, especially in health. From faster diagnoses to personalized treatments to more effective public policies, the intelligent use of health information has the power to change lives in profound and meaningful w…
Open data on femicide: a fundamental step in the fight against violence against women
Femicide, defined as the gender-based murder of women, remains one of the most extreme forms of violence. In 2023, it is estimated that approximately 85,000 women and girls were murdered in the world and of these, 60% died at the hands of intimate partners or family members, which is equivalent to 1…
Federated machine learning: generating value from shared data while maintaining privacy
Data is a fundamental resource for improving our quality of life because it enables better decision-making processes to create personalised products and services, both in the public and private sectors. In contexts such as health, mobility, energy or education, the use of data facilitates more effic…
How do you build an artificial intelligence model?
Artificial Intelligence (AI) is no longer a futuristic concept and has become a key tool in our daily lives. From movie or series recommendations on streaming platforms to virtual assistants like Alexa or Google Assistant on our devices, AI is everywhere. But how do you build an AI model? Despite wh…
Open source auto machine learning tools
The increasing complexity of machine learning models and the need to optimise their performance has been driving the development of AutoML (Automated Machine Learning) for years. This discipline seeks to automate key tasks in the model development lifecycle, such as algorithm selection, data process…
New Year's resolution: Apply the UNE data specifications in your organisation
As tradition dictates, the end of the year is a good time to reflect on our goals and objectives for the new phase that begins after the chimes. In data, the start of a new year also provides opportunities to chart an interoperable and digital future that will enable the development of a robust data…
Application of the UNE 0081:2023 Specification for data quality evaluation
The new UNE 0081 Data Quality Assessment specification, focused on data as a product (datasets or databases), complements the UNE 0079 Data Quality Management specification, which we analyse in this article, and focuses on data quality management processes. Both standards 0079 and 008…
