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Found 147 result(s)
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The Weizenbaum Library is the open access repository of the Weizenbaum Institute. It makes the open research results (publications and research data) of the Institute permanently accessible worldwide.
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The purpose of the Canadian Urban Data Repository (CUDR) is to provide a “home” for urban datasets. While primarily focused on datasets created by academe, it will also contain datasets created by NGOs, governments, citizens, and industry. Datasets stored in the repository will be open-access and will not contain personally identifiable information. The purpose of the Canadian Urban Data Catalogue (CUDC) is to enhance the awareness of urban datasets that exist across Canada by providing a catalogue of Canadian and Canadian-created urban datasets. It will catalogue datasets available in CUDR and external datasets available on other platforms and as web services. These external datasets may be open or closed. CUDC uses a rich metadata model that supports the documentation and search for datasets relevant to a user’s needs. Catalogue entry metadata may be exported and imported from/to CUDC.
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The Research Data Repository of FID move is a digital long-term repository for open data from the field of transport and mobility research. All datasets are provided with an open licence and are assigned a persistent DataCite DOI (Digital Object Identifier). Both data search and archiving are free. The Specialised Information Service for Mobility and Transport Research (FID move) has been set up by the Saxon State and University Library Dresden (SLUB) and the German TIB – Leibniz Information Centre for Science and Technology as part of the DFG funding programme "Specialised Information Services".
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Discuss Data is an open repository for storing, sharing and discussing research data on Eastern Europe, the South Caucasus and Central Asia. The platform, launched in September 2020, is funded by the German Research Foundation (DFG) and operated by the Research Centre for East European Studies at the University of Bremen (FSO) and the Göttingen State and University Library (SUB). Discuss Data goes beyond ordinary repositories and offers an interactive online platform for the discussion and quality assessment of research data. Our aim is to create a space for academic communication and for the community-specific publication, curation, annotation and discussion of research data.
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This platform aims to realize data storage, data management, data analysis, data sharing and data citation traceability of various data sets in the field of Humanities and Social Sciences of East China Normal University.
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Koszalin University of Technology is the only technical university in Central Pomerania. It is located in a town of 100 thousand inhabitants, about 10 km from the Baltic Sea. Central Pomerania is a region with well-developed tourism, agriculture, food-processing and electronics industries. Koszalin University of Technology conducts teaching and scientific-research activities in disciplines related primarily to the directions of development of the region. Koszalin University of Technology is authorized to confer doctoral degrees. The doctoral degree is conferred by the Doctoral School operating at Koszalin University of Technology. It educates students on I st and II nd degree studies, in stationary and non-stationary mode. The Repository is to be used for collecting, storing (archiving), presenting (making available) and retrieving information on the scientific and popular scientific achievement of employees, doctoral students and students, as well as on their professional achievements and activities that create the university's output and shaping its image among other scientific institutions in the country and in the world.
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The objective of the PDRC is to construct and collect a well-designed and large-scale panel data set and provide rigorous empirical studies based on these data sets. The data will enable us (i) to provide international comparisons and fact-findings on the household income changes, social mobility, changes in employment status and the investment activities; (ii) to verify the hypotheses related to the dynamics of economic behavior derived from economic theory; and (iii) to evaluate important policy changes in the tax system and social security program, which might have lagged effects.
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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.
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SMU Research Data Repository (SMU RDR) is a tool and service for researchers from Singapore Management University (SMU) to store, share and publish their research data. SMU RDR accepts a wide range of research data and outputs generated from research projects.
DASS-BiH (Data Archive for Social Sciences in Bosnia and Herzegovina) is the national service whose role is to ensure long-term preservation and dissemination of social science research data. The purpose of the data archive is to provide a vital research data resource for researchers, teachers, students, and all other interested users.
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DATICE was established in late 2018 and is funded by the University of Iceland's (UI) School of Social Sciences, with a contribution from the university's Centennial Fund. DATICE is the appointed service provider for the Consortium of European Social Science Data Archives (CESSDA ERIC) in Iceland and is located within the UI Social Science Research Institute (SSRI). The main goal of the data service is to ensure open and free access to high quality research data for the research community as well as the general public.
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Welcome to the transparency portal of the city of Karlsruhe, your central contact point for open data and documents of the city of Karlsruhe. On this portal you will find documents and reports as well as machine-readable data sets ("open data"). You may - under a few conditions - distribute, edit and also commercially use this information free of charge. We are happy if interesting projects arise from this - and if you tell us about your project. The information offered is constantly being expanded.
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DAIS - Digital Archive of the Serbian Academy of Sciences and Arts is a joint digital repository of the Serbian Academy of Sciences and Arts (SASA) and the research institutes under the auspices of SASA. The aim of the repository is to provide open access to publications and other research outputs resulting from the projects implemented by the SASA and its institutes. The repository uses a DSpace-based software platform developed and maintained by the Belgrade University Computer Centre (RCUB).
WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.
To help flattening the COVID-19 curve public health systems need better information on whether preventive measures are working and how the virus may spread. Facebook Data for Good offer maps on population movement that researchers and nonprofits are already using to understand the coronavirus crisis, using aggregated data to protect people’s privacy.
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Risklayer Explorer is a collaboration between Risklayer GmbH and the Karlsruhe Institute of Technology's Center for Disaster Risk Management and Risk Reduction Technology (CEDIM). This website is still under development, but we are going live with it already, because we want to present data on the Novel Coronavirus (COVID-19) to help inform the public of the current situation. You will be able to track disaster events and read about our analysis here. Our work is a continuation of a new style of disaster research started by CEDIM in 2011 to analyze disasters immediately after their occurrence, assess the impacts, and retrace the temporal development of disaster events. We are already analyzing damaging earthquakes globally, providing you with event characteristics, earthquake's intensity footprints, as well as the population affected by earthquakes. In addition to earthquake events, we expect to be tracking and analyzing tropical cyclone, volcano and extreme weather events in 2020.
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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.