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AUSSDA - The Austrian Social Science Data Archive is a certified, national research infrastructure for the social science community. We offer sustainable and easy-to-use services in the field of digital archiving and preservation. The main beneficiaries are researchers, students, educational institutions and media professionals. We implement international standards to make research data findable, accessible, interoperable and reusable according to the FAIR principles. AUSSDA supports the open science movement to maximize the potential for data reuse. We stand for integrity in archiving and advocate for compliance with data protection and ethical principles in research data management. AUSSDA represents Austria as a national service provider in CESSDA ERIC, has locations at the universities of Vienna, Graz, Linz, Innsbruck, Krems and at the OeAW (Austrian Academy of Sciences) and works within a network of national and international partners.
The National Archives is home to millions of historical documents, known as records, which were created and collected by UK central government departments and major courts of law. Data of the fomer National Digital Archive of Datasets (NDAD) collection, which was active from 1997 to 2010 and preserves and provides online access to archived digital datasets and documents from UK central government departments, is integrated. Access to records held by The National Archives and more than 2,500 other archives.
The Comparative Political Data Set 1960-2018 (CPDS) is a collection of political and institutional data which have been assembled in the context of the research projects “Die Handlungsspielräume des Nationalstaates” and “Critical junctures. An international comparison” directed by Klaus Armingeon and funded by the Swiss National Science Foundation. This data set consists of (mostly) annual data for 36 democratic OECD and/or EU-member coun-tries for the period of 1960 to 2018. In all countries, political data were collected only for the democratic periods. The data set is suited for cross-national, longitudinal and pooled time-series analyses.