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Found 55 result(s)
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
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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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The Community Data Program (CDP) is a membership-based community development initiative open to any Canadian public, non-profit or community sector organization with a local service delivery or public policy mandate. The program facilitates access to the evidence needed to tell our stories and inform effective and responsive policy and program design and implementation. The CDP makes data accessible and useful for all members with training and capacity building resources. Through its vibrant network, the CDP facilitates and supports dialogue and the sharing of best practices in the use of community data. The CDP has emerged as a unique Canada-wide platform for generating information, convening and collaborating.
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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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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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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).
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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<<<!!!<<< The digital archive of the Historical Data Center Saxony-Anhalt was transferred to the share-it repositor https://www.re3data.org/repository/r3d100013014 >>>!!!>>> The Historical Data Centre Saxony-Anhalt was founded in 2008. Its main tasks are the computer-aided provision, processing and evaluation of historical research data, the development of theoretically consolidated normative data and vocabularies as well as the further development of methods in the context of digital humanities, research data management and quality assurance. The "Historical Data Centre Saxony-Anhalt" sees itself as a central institution for the data service of historical data in the federal state of Saxony-Anhalt and is thus part of a nationally and internationally linked infrastructure for long-term data storage and use. The Centre primarily acquires individual-specific microdata for the analysis of life courses, employment biographies and biographies (primarily quantitative, but also qualitative data), which offer a broad interdisciplinary and international analytical framework and meet clearly defined methodological and technical requirements. The studies are processed, archived and - in compliance with data protection and copyright conditions - made available to the scientifically interested public in accordance with internationally recognized standards. The degree of preparation depends on the type and quality of the study and on demand. Reference studies and studies in high demand are comprehensively documented - often in cooperation with primary researchers or experts - and summarized in data collections. The Historical Data Centre supports researchers in meeting the high demands of research data management. This includes the advisory support of the entire life cycle of data, starting with data production, documentation, analysis, evaluation, publication, long-term archiving and finally the subsequent use of data. In cooperation with other infrastructure facilities of the state of Saxony-Anhalt as well as national and international, interdisciplinary data repositories, the Data Centre provides tools and infrastructures for the publication and long-term archiving of research data. Together with the University and State Library of Saxony-Anhalt, the Data Centre operates its own data repository as well as special workstations for the digitisation and analysis of data. The Historical Data Centre aims to be a contact point for very different users of historical sources. We collect data relating to historical persons, events and historical territorial units.
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Public access to open data from the Regional Municipality of Waterloo (the cities of Kitchener, Cambridge, and Waterloo, and the townships of Wellesley, Woolwich, Wilmot, and North Dumfries).
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The B.C. Data Catalogue provides the easiest access to government's data holdings, as well as applications and web services. Thousands of the datasets discoverable in the Catalogue are available under the Open Government License - British Columbia.
It is a platform for supporting Open Data initiative of Government of Odisha, intends to publish datasets collected by them for public use. It also supports widely used file formats that are suitable for machine processing, thus gives avenues for many more innovative uses of Government Data in different perspective. This portal has been created under Software as A Service (SaaS) model of Open Government Data (OGD) Platform India of NIC. The data available in the portal are owned by various Departments/Organization of Government of Odisha. It follows principles on which data sharing and accessibility need to be based include: Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
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Open Government Data Portal of Tamil Nadu is a platform (designed by the National Informatics Centre), for Open Data initiative of the Government of Tamil Nadu. The portal is intended to publish datasets collected by the Tamil Nadu Government for public uses in different perspective. It has been created under Software as A Service (SaaS) model of Open Government Data (OGD) and publishes dataset in open formats like CSV, XLS, ODS/OTS, XML, RDF, KML, GML, etc. This data portal has following modules, namely (a) Data Management System (DMS) for contributing data catalogs by various state government agencies for making those available on the front end website after a due approval process through a defined workflow; (b) Content Management System (CMS) for managing and updating various functionalities and content types; (c) Visitor Relationship Management (VRM) for collating and disseminating viewer feedback on various data catalogs; and (d) Communities module for community users to interact and share their views and common interests with others. It includes different types of datasets generated both in geospatial and non-spatial data classified as shareable data and non-shareable data. Geospatial data consists primarily of satellite data, maps, etc.; and non-spatial data derived from national accounts statistics, price index, census and surveys produced by a statistical mechanism. It follows the principle of data sharing and accessibility via Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
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It is a platform (designed and developed by the National Informatics Centre (NIC), Government of India) for supporting Open Data initiative of Surat Municipal Corporation, intended to publish government datasets for public use. The portal has been created under Software as A Service (SaaS) model of Open Government Data (OGD) Platform, thus gives avenues for resuing datasets of the City in different perspective. This Portal has numerious modules; (a) Data Management System (DMS) for contributing data catalogs by various departments for making those available on the front end website after a due approval process through a defined workflow; (b) Content Management System (CMS) for managing and updating various functionalities and content types of Open Government Data Portal of Surat City; (c) Visitor Relationship Management (VRM) for collating and disseminating viewer feedback on various data catalogs; and (d) Communities module for community users to interact and share their zeal and views with others, who share common interests as that of theirs.
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.
Ag-Analytics is an online open source database of various economic and environmental data. It automates the collection, formatting, and processing of several different commonly used datasets, such as the National Agricultural Statistics Service (NASS), the Agricultural Marketing Service (AMS), Risk Management agency (RMA), the PRISM weather database, and the U.S. Commodity Futures Trading Commission (CFTC). All the data have been cleaned and well-documented to save users the inconvenience of scraping and cleaning the data themselves.
The figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.