15 posts found
What data governance should look like in open source AI models
Open source artificial intelligence (AI) is an opportunity to democratise innovation and avoid the concentration of power in the technology industry. However, their development is highly dependent on the availability of high quality datasets and the implementation of robust data governance framework…
Data Sandboxes: Exploring the potential of open data in a secure environment
Data sandboxes are tools that provide us with environments to test new data-related practices and technologies, making them powerful instruments for managing and using data securely and effectively. These spaces are very useful in determining whether and under what conditions it is feasibl…
Global principles of AI journalism
General ethical frameworks
The absence of a common, unified, ethical framework for the use of artificial intelligence in the world is only apparent and, in a sense, a myth. There are a multitude of supranational charters, manuals and sets of standards that set out principles of ethical use, although…
Artificial intelligence to improve interoperability in the European public sector
The European Union has placed the digital transformation of the public sector at the heart of its policy agenda. Through various initiatives under the Digital Decade policy programme, the EU aims to boost the efficiency of public services and provide a better experience for citizens.…
The implementation of the EU Data Governance Regulation in Public Administrations
Since 24 September last year, the Regulation (EU) 2022/868 of the European Parliament and of the Council of 30 May 2022, on European Data Governance (Data Governance Regulation) has been applicable throughout the European Union. Since it is a Regulation, its provisions are directly effective without…
Quantifying the value of data
There is a recurring question that has been around since the beginning of the open data movement, and as efforts and investments in data collection and publication have increased, it has resonated more and more strongly: What is the value of a dataset?
This is an extremely difficult question to answ…
When to use each programming language in data science?
Python, R, SQL, JavaScript, C++, HTML... Nowadays we can find a multitude of programming languages that allow us to develop software programmes, applications, web pages, etc. Each one has unique characteristics that differentiate it from the rest and make it more appropriate for certain tasks. But h…
10 Popular natural language processing libraries
The advance of supercomputing and data analytics in fields as diverse as social networks or customer service is encouraging a part of artificial intelligence (AI) to focus on developing algorithms capable of processing and generating natural language.
To be able to carry out this task in the current…
Open data in Spain according to the Global Data Barometer study
The Global Data Barometer is a new multi-dimensional study that assesses the potential of data use by public administration in more than 100 countries. It is a tool that thoroughly investigates data policies and practices in their governance, openness and use for the public good.
This new Barometer…
10 Popular Data Analytics and Machine Learning Libraries
Programming libraries refer to the sets of code files that have been created to develop software in a simple way . Thanks to them, developers can avoid code duplication and minimize errors with greater agility and lower cost. There are many bookstores, focused on different activities. A few weeks ag…
