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Found 159 result(s)
The EUR Data Repository [EDR] is the institutional data repository from the Erasmus University Rotterdam. The EUR Data Repository is an online platform where you showcase your research and make it findable, citable, and reusable for others.
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The Common Research Data Repository (Deposita Dados) is a database for archiving, publishing, disseminating, preserving and sharing digital research data and its mission is to promote, support and facilitate the adoption of open access to the datasets of Brazilian researchers linked to scientific institutions that do not yet have their own research data repositories and/or of Brazilian researchers who have executed their datasets through scientific collaboration in foreign teaching and research institutions.
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Kinsources is an open and interactive platform to archive, share, analyze and compare kinship data used in scientific research. Kinsources is not just another genealogy website, but a peer-reviewed repository designed for comparative and collaborative research. The aim of Kinsources is to provide kinship studies with a large and solid empirical base. Kinsources combines the functionality of communal data repository with a toolbox providing researchers with advanced software for analyzing kinship data. The software Puck (Program for the Use and Computation of Kinship data) is integrated in the statistical package and the search engine of the Kinsources website. Kinsources is part of a research perspective that seeks to understand the interaction between genealogy, terminology and space in the emergence of kinship structures. Hosted by the TGIR HumaNum, the platform ensures both security and free access to the scientific data is validated by the research community.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
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The Scientific Database of the Federal University of ParanĆ” aims to gather the scientific data used in the researches that were published by the UFPR community in theses, dissertations, journal articles, and other bibliographic materials. BDC joins RDI / UFPR as an innovative service that tracks the worldwide trend in research planning, management, production, organization, storage, dissemination and reuse. The availability of research data contributes to the transparency and optimization of scientific production through the reuse of data sets and the possibility of new analyzes and approaches
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.
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 ā€œOpen Services.ā€
The German Text Archive (Deutsches Textarchiv, DTA) presents online a selection of key German-language works in various disciplines from the 17th to 19th centuries. The electronic full-texts are indexed linguistically and the search facilities tolerate a range of spelling variants. The DTA presents German-language printed works from around 1650 to 1900 as full text and as digital facsimile. The selection of texts was made on the basis of lexicographical criteria and includes scientific or scholarly texts, texts from everyday life, and literary works. The digitalisation was made from the first edition of each work. Using the digital images of these editions, the text was first typed up manually twice (ā€˜double keyingā€™). To represent the structure of the text, the electronic full-text was encoded in conformity with the XML standard TEI P5. The next stages complete the linguistic analysis, i.e. the text is tokenised, lemmatised, and the parts of speech are annotated. The DTA thus presents a linguistically analysed, historical full-text corpus, available for a range of questions in corpus linguistics. Thanks to the interdisciplinary nature of the DTA Corpus, it also offers valuable source-texts for neighbouring disciplines in the humanities, and for scientists, legal scholars and economists.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
FLOSSmole is a collaborative collection of free, libre, and open source software (FLOSS) data. FLOSSmole contains nearly 1 TB of data covering the period 2004 until now, about more than 500,000 different open source projects.
A premier source for United States cancer statistics, SEER gathers information related to incidence, prevalence, and survival from specific geographic areas that represent 28 percent of the population, as well as compiles related reports and reports on the national cancer mortality rates. Their aim is to provide information related to cancer statistics and decrease the burden of cancer in the national population. SEER has been collecting data from cancer cases since 1973.
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The Australian Data Archive (ADA) provides a national service for the collection and preservation of digital research data and to make these data available for secondary analysis by academic researchers and other users. Data are stored in seven sub-archives: Social Science, Historical, Indigenous, Longitudinal, Qualitative, Crime & Justice and International. Along with Australian data, ADA International is also a repository for studies by Australian researchers conducted in other countries, particularly throughout the Asia-Pacific region. The ADA International data catalogue includes links to studies from countries including New Zealand, Bangladesh, Cambodia, China, Indonesia, and several other countries. In 2017 the archive systems moved from the existing Nesstar platform to the new ADA Dataverse platform https://dataverse.ada.edu.au/
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
CLARIN-LV is a national node of Clarin ERIC (Common Language Resources and Technology Infrastructure). The mission of the repository is to ensure the availability and longĀ­ term preservation of language resources. The data stored in the repository are being actively used and cited in scientific publications.
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Multidisciplinary research data repository, hosted by DTU, the Danish Technical University.