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Found 65 result(s)
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
DaSCH is the trusted platform and partner for open research data in the Humanities. DaSCH develops and operates a FAIR long-term repository and a generic virtual research environment for open research data in the humanities in Switzerland. We provide long-term direct access to the data, enable their continuous editing and allow for precise citation of single objects within a dataset. We ensure interoperability with tools used by the Humanities and Cultural Sciences communities and foster the use of standards. The development of our platform happens in close cooperation with these communities. We provide training and advice in the area of research data management, promote open data and the use of standards. DaSCH is the coordinating institution and representative of Switzerland in the European Research Infrastructure Consortium ‘Digital Research Infrastructure for the Arts and Humanities’ (DARIAH ERIC). Within this mandate, we actively engage in community building within Switzerland and abroad. DaSCH cooperates with national and international organizations and initiatives in order to provide services that are fit for purpose within the broader Swiss open research data landscape and that are coordinated with other institutions such as FORS. We base our actions on the values reliability, flexibility, appreciation, curiosity, and persistence. Furthermore, DARIAH’s activities in Switzerland are coordinated by DaSCH and DaSCH is acting as DARIAH-CH Coordination Office.
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
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Lithuanian Data Archive for Social Sciences and Humanities (LiDA) is a virtual digital infrastructure for SSH data and research resources acquisition, long-term preservation and dissemination. All the data and research resources are documented in both English and Lithuanian according to international standards. Access to the resources is provided via Dataverse repository. LiDA curates different types of resources and they are published into catalogues according to the type: Survey Data, Aggregated Data (including Historical Statistics), Encoded Data (including News Media Studies), and Textual Data. Also, LiDA holds collections of social sciences and humanities data deposited by Lithuanian science and higher education institutions and Lithuanian state institutions (Data of Other Institutions). LiDA is hosted by the Centre for Data Analysis and Archiving of Kaunas University of Technology (data.ktu.edu).
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Launched in February 2020, data.sciencespo is a repository that offers visibility, sharing and preservation of data collected, curated and processed at Sciences Po. The repository is based on the Dataverse open-source software and organised into collections: CDSP Collection This collection managed by the Centre des données socio-politiques (CDSP) includes the catalogue of surveys, in the social science and humanities, processed and curated by CDSP engineers since 2005. This catalogue brings together surveys produced at Sciences Po and other French and international institutions. - Sciences Po collection (self-deposit) This collection, which is managed by the Direction des ressources et de l'information scientifique (DRIS), is intended to host data produced by researchers affiliated with Sciences Po, following the self-deposit process assisted by the Library's staff.
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Created and managed by the Library, DataSpace@HKUST is the data repository and workspace service for HKUST research community. Faculty members and research postgraduate students can use the platform to store, share, organize, preserve and publish research data. It is built on Dataverse, an open source web application developed at Harvard’s Institute for Quantitative Social Science. Using Dataverse architecture, the repository hosts multiple "dataverses". Each dataverse contains datasets; while each dataset may contain multiple data files and the corresponding descriptive metadata.
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GovData the data portal for Germany offers consistent and central access to administrative data at the federal, state, and local level. Objective is to make data more available and easier to use at a single location. As set out in the concept of "open data", we attempt to facilitate the use of open licenses and to increase the supply of machine-readable raw data.
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The information system Graffiti in Germany (INGRID) is a cooperation project between the linguistics department at the University of Paderborn and the art history department at the Karlsruhe Institute of Technology (KIT). As part of the joint project, graffiti image collections will be compiled, stored in an image database and made available for scientific use. At present, more than 100,000 graffiti from the years 1983 to 2018 from major German cities are recorded, including Cologne, Mannheim and Munich.
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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.
UCLA Library is adopting Dataverse, the open source web application designed for sharing, preserving and using research data. UCLA Dataverse will allow data, text, software, scripts, data visualizations, etc., created from research projects at UCLA to be made publicly available, widely discoverable, linkable, and ultimately, reusable
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BIBB has a strong tradition of survey-based research. It initiates and realises the collection of individual and firm-level data on crucial positions and transitions in the education and labour market system. The BIBB-FDZ covers a variety of data deploying different units of analysis and temporal designs and focusing on various thematic issues. Standard access to well prepared firm- and individual-level data on the attainment and utilization of vocational education and training Documentation of these data sets, i.e. a description of their central characteristics, main issues and variables, data collection, anonymisation, weighting and recoding etc. Advisory service on data choice, data access and handling, research potential and scope and validity of the data. Supply of a range of data tools such as standard measures and classifications in the fields of education, occupations, industries and regions (if possible also including cross-national fields), formally anonymous data for remote data access, or references to publications with the data.
A research data repository for the education and developmental sciences.
<<<!!!<<< History Data Service ressources now available in https://www.data-archive.ac.uk/find, see re3data https://www.re3data.org/repository/r3d100010215>>>!!!>>>
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
TiU Dataverse is the central online repository for research data at Tilburg University. The TiU Dataverse is managed by the Research Data Office (RDO) at Library and IT Services (LIS). TiU Dataverse takes part of the DataverseNL network. DataverseNL is a shared data service of several Dutch universities and institutions. The data management is in the hands of the member organizations, while the national organization Data Archiving and Networked Services (DANS) manages the network
The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.