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Found 225 result(s)
Open access repository for digital research created at the University of Minnesota. U of M researchers may deposit data to the Libraries’ Data Repository for U of M (DRUM), subject to our collection policies. All data is publicly accessible. Data sets submitted to the Data Repository are reviewed by data curation staff to ensure that data is in a format and structure that best facilitates long-term access, discovery, and reuse.
The Odum Institute Archive Dataverse contains social science data curated and archived by the Odum Institute Data Archive at the University of North Carolina at Chapel Hill. Some key collections include the primary holdings of the Louis Harris Data Center, the National Network of State Polls, and other Southern-focused public opinion data. Please note that some datasets in this collection are restricted to University of North Carolina at Chapel Hill affiliates. Access to these datasets require UNC ONYEN institutional login to the Dataverse system.
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.
TERN provides open data, research and management tools, data infrastructure and site-based research equipment. The open access ecosystem data is provided by TERN Data Discovery Portal , see https://www.re3data.org/repository/r3d100012013
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mdw Repository provides researchers with a robust infrastructure for research data management and ensures accessibility of research data during and after completion of research projects, thus, providing a quality boost to contemporary and future research.
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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.
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.
LibraData is a place for UVA researchers to share data publicly. It is UVA's local instance of Dataverse. LibraData is part of the Libra Scholarly Repository suite of services which includes works of UVA scholarship such as articles, books, theses, and data.
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OpenAgrar is an open access repository which publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains amongst others theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews.
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.
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
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Data are the key to successful scientific work. A sophisticated data management will guarantee the long-term availability of observational data and metadata, and will allow for an easy data search and retrieval, to supplement the international data exchange and to provide data products for scientific, political, industrial and public stakeholders.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
Antarctic marine and terrestrial biodiversity data is widely scattered, patchy and often not readily accessible. In many cases the data is in danger of being irretrievably lost. Biodiversity.aq establishes and supports a distributed system of interoperable databases, giving easy access through a single internet portal to a set of resources relevant to research, conservation and management pertaining to Antarctic biodiversity. biodiversity.aq provides access to both marine and terrestrial Antarctic biodiversity data.
By stimulating inspiring research and producing innovative tools, Huygens ING intends to open up old and inaccessible sources, and to understand them better. Huygens ING’s focus is on Digital Humanities, History, History of Science, and Textual Scholarship. Huygens ING pursues research in the fields of History, Literary Studies, the History of Science and Digital Humanities. Huygens ING aims to publish digital sources and data responsibly and with care. Innovative tools are made as widely available as possible. We strive to share the available knowledge at the institute with both academic peers and the wider public.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
The Répertoire International des Sources Musicales (RISM) - International Inventory of Musical Sources - is an international, non-profit organization that aims to comprehensively document extant musical sources worldwide. These primary sources are music manuscripts or printed music editions, writings on music theory, and libretti. They are preserved in libraries, archives, churches, schools and private collections. RISM was founded in Paris in 1952 and is the largest and only international organization that documents written musical sources. RISM records what exists and where it can be found. As a result, by virtue of being cataloged in a comprehensive inventory, music traditions are protected while also being made available to musicologists and musicians alike. Such work is thus not an end in itself, but leads directly to practical applications.
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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.
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The AMUReD Institutional Research Data Repository of the Adam Mickiewicz University in Poznan (UAM) collects and provides access to digital versions of research data collected, processed or produced as part of the scientific research or developmental work of UAM employees.The AMUReD Repository is part of the AMU Research Portal, with University Library in Poznan as the operating unit. Depositing data is possible after logging into the AMU Research Portal, according to the attached instructions. The AMUReD repository is open, and research data are made available in three models: open (Open Access), embargo (Embargo) and closed (Restricted Access). The detailed rules of the AMUReD repository are defined in the Regulations. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The prefix for DOIs is doi:10.60629. It is possible to choose a Creative Commons license for shared datasets.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
An increasing number of Language Resources (LT) in the various fields of Human Language Technology (HLT) are distributed on behalf of ELRA via its operational body ELDA, thanks to the contribution of various players of the HLT community. Our aim is to provide Language Resources, by means of this repository, so as to prevent researchers and developers from investing efforts to rebuild resources which already exist as well as help them identify and access those resources.
The UK Polar Data Centre (UK PDC) is the focal point for Arctic and Antarctic environmental data management in the UK. Part of the Natural Environmental Research Council’s (NERC) network of environmental data centres and based at the British Antarctic Survey, it coordinates the management of polar data from UK-funded research and supports researchers in complying with national and international data legislation and policy.
IEEE DataPort™ is a universally accessible online data repository created, owned, and supported by IEEE, the world’s largest technical professional organization. It enables all researchers and data owners to upload their dataset without cost. IEEE DataPort makes data available in three ways: standard datasets, open access datasets, and data competition datasets. By default, all "standard" datasets that are uploaded are accessible to paid IEEE DataPort subscribers. Data owners have an option to pay a fee to make their dataset “open access”, so it is available to all IEEE DataPort users (no subscription required). The third option is to host a "data competition" and make a dataset accessible for free for a specific duration with instructions for the data competition and how to participate. IEEE DataPort provides workflows for uploading data, searching, and accessing data, and initiating or participating in data competitions. All datasets are stored on Amazon AWS S3, and each dataset uploaded by an individual can be up to 2TB in size. Institutional subscriptions are available to the platform to make it easy for all members of a given institution to utilize the platform and upload datasets.