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Found 46 result(s)
DataBank is a repository that will keep data safe in the long term. It can automatically obtain a Digital Object Indicator (DOI) for each data package, and make the metadata and/or the underlying data searchable and accessible by the wider world.
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The Universitat de Barcelona Digital Repository is an institutional resource containing open-access digital versions of publications related to the teaching, research and institutional activities of the UB's teaching staff and other members of the university community, including research data.
The Texas Data Repository is a platform for publishing and archiving datasets (and other data products) created by faculty, staff, and students at Texas higher education institutions. The repository is built in an open-source application called Dataverse, developed and used by Harvard University. The repository is hosted by the Texas Digital Library, a consortium of academic libraries in Texas with a proven history of providing shared technology services that support secure, reliable access to digital collections of research and scholarship. For a list of TDL participating institutions, please visit: http://tdl.org/members.
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In the digital collections, you can take a look at the digitized prints from the holdings of the ULB Düsseldorf free of cost. In special collections, the ULB unites rare, valuable and unique parts of holdings that are installed as an ensemble. Deposita, unpublished works, donations, acquisition of rare books etc. were and are an important source for the constant growth of the library. These treasures and specialties - beyond their academic value - also contribute substantially to the profile of the ULB.
The UC San Diego Library Digital Collections website gathers two categories of content managed by the Library: library collections (including digitized versions of selected collections covering topics such as art, film, music, history and anthropology) and research data collections (including research data generated by UC San Diego researchers).
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GBIF is an international organisation that is working to make the world's biodiversity data accessible everywhere in the world. GBIF and its many partners work to mobilize the data, and to improve search mechanisms, data and metadata standards, web services, and the other components of an Internet-based information infrastructure for biodiversity. GBIF makes available data that are shared by hundreds of data publishers from around the world. These data are shared according to the GBIF Data Use Agreement, which includes the provision that users of any data accessed through or retrieved via the GBIF Portal will always give credit to the original data publishers.
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
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.
Open access to macromolecular X-ray diffraction and MicroED datasets. The repository complements the Worldwide Protein Data Bank. SBDG also hosts reference collection of biomedical datasets contributed by members of SBGrid, Harvard and pilot communities.
The Illinois Data Bank is an institutional data repository that collects, disseminates, and provides persistent and reliable access to the research data of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students can deposit their research data directly into the Illinois Data Bank and receive a DOI for citation purposes.
This Web resource provides data and information relevant to SARS coronavirus. It includes links to the most recent sequence data and publications, to other SARS related resources, and a pre-computed alignment of genome sequences from various isolates. The genome of SARS-CoV consists of a single, positive-strand RNA that is approximately 29,700 nucleotides long. The overall genome organization of SARS-CoV is similar to that of other coronaviruses. The reference genome includes 13 genes, which encode at least 14 proteins. Two large overlapping reading frames (ORFs) encompass 71% of the genome. The remainder has 12 potential ORFs, including genes for structural proteins S (spike), E (small envelope), M (membrane), and N (nucleocapsid). Other potential ORFs code for unique putative SARS-CoV-specific polypeptides that lack obvious sequence similarity to known proteins.
The Museum is committed to open access and open science, and has launched the Data Portal to make its research and collections datasets available online. It allows anyone to explore, download and reuse the data for their own research. Our natural history collection is one of the most important in the world, documenting 4.5 billion years of life, the Earth and the solar system. Almost all animal, plant, mineral and fossil groups are represented. These datasets will increase exponentially. Under the Museum's ambitious digital collections programme we aim to have 20 million specimens digitised in the next five years.
The Purdue University Research Repository (PURR) provides a virtual research environment and data publication and archiving platform for its campuses. Also supports the publication and online execution of software tools with DataCite DOIs.
EASY is the online archiving system of Data Archiving and Networked Services (DANS). EASY offers you access to thousands of datasets in the humanities, the social sciences and other disciplines. EASY can also be used for the online depositing of research data.
The Environmental Data Initiative Repository concentrates on studies of ecological processes that play out at time scales spanning decades to centuries including those of the NSF Long Term Ecological Research (LTER) program, the NSF Macrosystems Biology Program, the NSF Long Term Research in Environmental Biology (LTREB) program, the Organization of Biological Field Stations, and others. The repository hosts data that provide a context to evaluate the nature and pace of ecological change, to interpret its effects, and to forecast the range of future biological responses to change.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. A unique feature of Edmond is the dedicated metadata management, which supports a non-restrictive metadata schema definition, as simple as you like or as complex as your parameters require. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
CaltechDATA is an institutional data repository for Caltech. Caltech library runs the repository to preserve the accomplishments of Caltech researchers and share their results with the world. Caltech-associated researchers can upload data, link data with their publications, and assign a permanent DOI so that others can reference the data set. The repository also preserves software and has automatic Github integration. All files present in the repository are open access or embargoed, and all metadata is always available to the public.
BioModels Database is a repository of peer-reviewed, published, computational models that allows biologists to store, search and retrieve published mathematical models from the field of systems biology, but also more generally those of biological interest. Models in the database can be used to generate sub-models, can be simulated online, and can be converted between different representational formats.
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This DOI repository provides permanent identifiers to data sets generated by Life Science researchers active in Sweden, and for which no other suitable public repository is available. BILS is a distributed national research infrastructure supported by the Swedish Research Council (Vetenskapsrådet) providing bioinformatics support to life science researchers in Sweden.
The Arctic Data Center is the primary data and software repository for the Arctic section of NSF Polar Programs. The Center helps the research community to reproducibly preserve and discover all products of NSF-funded research in the Arctic, including data, metadata, software, documents, and provenance that links these together. The repository is open to contributions from NSF Arctic investigators, and data are released under an open license (CC-BY, CC0, depending on the choice of the contributor). All science, engineering, and education research supported by the NSF Arctic research program are included, such as Natural Sciences (Geoscience, Earth Science, Oceanography, Ecology, Atmospheric Science, Biology, etc.) and Social Sciences (Archeology, Anthropology, Social Science, etc.). Key to the initiative is the partnership between NCEAS at UC Santa Barbara, DataONE, and NOAA’s NCEI, each of which bring critical capabilities to the Center. Infrastructure from the successful NSF-sponsored DataONE federation of data repositories enables data replication to NCEI, providing both offsite and institutional diversity that are critical to long term preservation.
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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.