The European Social Survey (ESS) is a cross-national survey based on scientific standards that has been conducted every two years since 2001. The ESS collects data on attitudes and behaviour patterns of the population in more than 30 European countries. The survey data are provided by the ESS-ERIC (ERIC = European Research Infrastructure Consortium). In cooperation with national institutions, data from interviews on attitudes, beliefs and behavioural patterns are collected throughout Europe.
Dataset of two experiments in the language pairs English-Russian, English-German. The dataset contains linguistic data (Segments translated in different methods) and human data (participants filled in questionnaires). The dataset contains translation versions across different steps of a team translation approach.
Technological development continues to offer ways of health data collection that go beyond asking survey questions. Such new types of data were collected in the SHARE survey by means of Dried Blood Spot Samples (DBSS) and accelerometer data. These data demand new data protection rules and must often be extensively processed, validated and calibrated before they can be made accessible. SHARE and CentERdata develop a strategy to provide access to such data according to FAIR principles.
Many different domains lack multilingual terminological resources. Making data and services accessible and usable in SSH is very much a matter of providing terminology across languages and multilingual vocabularies. Shortage of multilingual terminologies and vocabularies represents an obstacle to the access and reuse of information. Using the appropriate vocabularies can greatly improve both discovery and classification. Consequently, for SSHOC, it is important to address this issue with respect to the SSH domain.
Archaeological data management best practice guidance developed within E-RIHS and SSHOC will be implemented within the ARIADNEplus infrastructure and workflow, which may then be made available as a service within SSHOC.
The RESTORE Data Integration Suite is a toolbox supporting Memory, Cultural, Research institutions and citizen scientists with an interest in historical sources from archives, libraries, and museum collections in the creation of a FAIR digital ecosystem for Humanities Research, fostering semantic interoperability of cataloguing standards and research data opening and sharing.
Cultural and scientific data cannot be understood without knowledge about the provenance (the origin, context or history). Provenance provides a critical foundation for assessing authenticity, enabling trust, and allowing reproducibility. Provenance metadata are data describing objects, people, places, times which are causally related by events. They are event centric and must be described in a historical order to ensure that there are no references to non-existent (non-recorded) events or objects.
A database of survey questionnaires’ texts. The first version is compiled from questionnaires from the of European Social Survey (ESS) and the European Values Study (EVS) in the English source language and their translations into Catalan, Czech, French, German, Norwegian, Portuguese, Spanish and Russian.
The Audio Survey Experiment provides guidelines describing how to integrate the collection of digital language data into the traditional social sciences data collection process and provides audio transcript data which can be analysed with the help of natural language processing tools.
A registry of (meta)data conversion services featuring the most relevant SSH (meta)data formats and encompassing links to services, format recommendations for increasing interoperability, software recommendations, and a software library. Selected conversion tools will be created where necessary.
Based on the already functional CLARIN VCR, the VCR service will enable researchers to create integrated, coherent sets of links to digital objects. These virtual collections will provide persistent identifiers and federated login.
The collection metadata is openly available and accessible via the Virtual Language Observatory.
The repository will be built upon the community-driven open source Dataverse software platform. Its modular design facilitates integration with other data services such as DataCite or ROpenScience, allows for distributed file storage, and supports the development of additional functionality and services.