Hoy, poco más de dos años después de su entrada en vigor, la Comisión Europea ha publicado un informe de evaluación sobre el Reglamento general de protección de datos (RGPD). El informe muestra que el RGPD ha cumplido la mayoría de sus objetivos, fundamentalmente porque ofrece a los ciudadanos un conjunto sólido de derechos exigibles y ha creado un nuevo sistema europeo de gobernanza y control del cumplimiento. El RGPD ha demostrado su flexibilidad para apoyar soluciones digitales en circunstancias imprevistas, como la crisis de la COVID-19. El informe concluye asimismo que aumenta la armonización en todos los Estados miembros, aunque existe cierto nivel de fragmentación que debe ser supervisado de forma continua. También señala que las empresas están desarrollando una cultura del cumplimiento y recurren cada vez más a una sólida protección de datos como ventaja competitiva. El informe incluye una lista de medidas destinadas a facilitar aún más la aplicación del RGPD a todas las partes interesadas, especialmente a las pequeñas y medianas empresas, así como a promover y desarrollar una cultura de protección de datos verdaderamente europea y un control riguroso de su aplicación. | RAPID, IP/20/1163, 24.6.2020

La Comisión ha desvelado hoy sus ideas y medidas para una transformación digital que redunde en beneficio de todos, y refleje lo mejor de Europa: abierta, justa, diversa, democrática y con confianza en sí misma. La estrategia presenta una sociedad europea impulsada por soluciones digitales que sitúan en el lugar preferente a las personas, abre nuevas oportunidades para las empresas y da impulso al desarrollo de una tecnología fiable que fomente una sociedad abierta y democrática y una economía dinámica y sostenible. La digitalización es un factor clave en la lucha contra el cambio climático y en la consecución de la transición ecológica. La estrategia europea de datos y las opciones estratégicas destinadas a garantizar un desarrollo de la inteligencia artificial centrado en el ser humano, que se han presentado hoy, constituyen los primeros pasos en pos de esos objetivos. | RAPID, IP/20/273, 19.2.2020

La Comisión ha desvelado hoy sus ideas y medidas para una transformación digital que redunde en beneficio de todos, y refleje lo mejor de Europa: abierta, justa, diversa, democrática y con confianza en sí misma. La estrategia presenta una sociedad europea impulsada por soluciones digitales que sitúan en el lugar preferente a las personas, abre nuevas oportunidades para las empresas y da impulso al desarrollo de una tecnología fiable que fomente una sociedad abierta y democrática y una economía dinámica y sostenible. La digitalización es un factor clave en la lucha contra el cambio climático y en la consecución de la transición ecológica. La estrategia europea de datos y las opciones estratégicas destinadas a garantizar un desarrollo de la inteligencia artificial centrado en el ser humano, que se han presentado hoy, constituyen los primeros pasos en pos de esos objetivos. | RAPID, IP-20-273, 19.2.2020

Lunes, 16 Diciembre 2019 10:05

Enlace de microdatos. Edición 2019

CoverMicro data linking — 2019 edition

Microdata linking (MDL) provides an opportunity to discover new information and to develop new statistics and indicators both when using existing data sets but also when combining with new data collections. The guidelines for MDL gather past experiences and best practices of the microdata linking, focusing on the most recent exercise of linking Business demography (BD) and Trade by enterprise characteristics (TEC) data. The key concepts and sources are described in broad terms. The central role of the Business register is emphasized when carrying out microdata linking exercises.

This publication introduces the rationale and key elements of microdata linking and suggests new angles for economic analysis and support for policy making. It also deals with the benefits and limitations of microdata linking and the main lessons learned so far. [+]

CoverFinancial big data and policy work: opportunities and challenges — 2019 edition

Public authorities working in the financial sphere have shown an increasing interest for big data. On the supply side, the amount of information at hand has boomed, reflecting not only the internet revolution, but also all the various initiatives launched after the financial crisis of 2007-09 to make a better use of existing sources of information – including, but not only, digital sources – and start new data collections, often on a very large scale.

As a result, “Financial Big Data” are quite specific. They primarily consist of the very large though relatively well-structured data sets derived from administrative and financial activities, for which new private data sources can play a major role.

Accessing these data can provide many opportunities for public authorities like central banks. But specific challenges also arise when handling these data and using them to support policy. In practice, this calls for being both pragmatic – ie starting with small pilot projects when exploring the financial big data universe – and ambitious – ie taking this opportunity to revisit existing information systems in a holistic way.

These various dilemma can be illustrated by two data collections of particular importance for central banks, one on derivatives transactions and one on the issuance of debt securities. [+]

CoverCitizen to government data partnerships: What can we learn from and recommend to civil society groups working in the official statistics domain?

The Cape Town Global Action Plan for Sustainable Development Data subscribed in 2017 at the first World Data Forum highlights the need of National Statistical Offices (NSOs) to adapt to evolving demands. This need is triggered by all kinds of decision-makers, specially from governments under constant pressures to deliver focused, tailored and timely solutions. Based on a classification framework adapted from the e-governance concept, this document takes stock of various international, regional and local initiatives thought to aid or monitor government actions and that are granting access to and use of non-traditional data sources. These are citizens to government data partnerships, that use technologies like open geospatial information platforms and can complement surveys and traditional censuses in the official statistics data stream, with special focus in demographic and social statistics. Recommendations will address the question of how civil society NGOs can strengthen their general capacities inside the statistical production processes to effectively support NSOs through collaboration projects at national and international levels. [+]

CoverPower from statistics: data, information and knowledge — Guidance report

The ‘Power from Statistics’ initiative, jointly organised by Eurostat and the European Political Strategy Centre, aims to determine which topics will be relevant to decision-makers and citizens in the future and how official statistics could best deliver information about them.

This Guidance Report is inspired by the ‘Power from Statistics Outlook Report’ (in which experts from various stakeholder groups set out their personal reflections and ideas on the future of European statistics) as well as by the high-level conference ‘Power from Statistics: delivering the evidence of tomorrow’, at which policymakers, journalists, business leaders, academics and official statisticians from all over Europe discussed the needs and challenges facing evidence-based policymaking. [+]

CoverAn overview of methods for treating selectivity in big data sources
The official statistics community is now seriously considering big data as a significant data source for producing statistics. It holds the potential for providing faster, cheaper, more detailed and completely new types of statistics. However, the use of big data also brings several challenges. One of them is the non-probabilistic character of most sources of big data, as very often, they were not designed to produce statistics. The resulting selectivity bias is therefore a major concern when using big data. This paper presents a statistical approach to big data, searching for a definition meaningful from the statistical point of view and identifying their main statistical characteristics. It then argues that big data sources share many characteristics with Internet opt-in panel surveys and proposes this as a reference to address selectivity and coverage problems in big data. Coverage and the self-selection process are briefly discussed in mobile network data, Twitter, Google Trends and Wikipedia page views data. An overview of methods which can be used to address selectivity and eliminate, or mitigate, bias is then presented, covering both methods applied at individual level, i.e. at the level of the statistical unit, and at domain level, i.e. at the level of the produced statistics. Finally, the applicability of the methods to the several big data sources is briefly discussed and a framework for adjusting selectivity in big data is proposed. [+]

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