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Found 17 result(s)
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
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DABAR (Digital Academic Archives and Repositories) is the key component of the Croatian e-infrastructure’s data layer. It provides technological solutions that facilitate maintenance of higher education and science institutions' digital assets, i.e., various digital objects produced by the institutions and their employees.
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).
The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.
The Archaeological Map of the Czech Republic (AMCR) is a repository designed for information on archaeological investigations, sites and finds, operated by the Archaeological Institutes of the CAS in Prague and Brno. The archives of these institutions contain documentation of archaeological fieldwork on the territory of the Czech Republic from 1919 to the present day, and they continue to enrich their collections. The AMCR database and related documents form the largest collection of archaeological data concerning the Czech Republic and are therefore an important part of our cultural heritage. The AMCR digital archive contains various types of records - individual archaeological documents (texts, field photographs, aerial photographs, maps and plans, digital data), projects, fieldwork events, archaeological sites, records of individual finds and a library of 3D models. Data and descriptive information are continuously taken from the AMCR and presented in the the AMCR Digital Archive interface.
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The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
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OCTOPUS is an Open Geospatial Consortium (OGC) compliant web-enabled database that allows users to visualise, query, and download cosmogenic 10Be and 26Al, luminescence, and radiocarbon ages and denudation rates associated with erosional landscapes, Quaternary depositional landforms and archaeological records, along with associated geospatial (vector and raster) data layers.
The Humanitarian Data Exchange (HDX) is an open platform for sharing data across crises and organisations. Launched in July 2014, the goal of HDX is to make humanitarian data easy to find and use for analysis. HDX is managed by OCHA's Centre for Humanitarian Data, which is located in The Hague. OCHA is part of the United Nations Secretariat and is responsible for bringing together humanitarian actors to ensure a coherent response to emergencies. The HDX team includes OCHA staff and a number of consultants who are based in North America, Europe and Africa.
The Million Song Dataset is a freely-available collection of audio features and metadata for a million contemporary popular music tracks. The core of the dataset is the feature analysis and metadata for one million songs, provided by The Echo Nest. The dataset does not include any audio, only the derived features. Note, however, that sample audio can be fetched from services like 7digital, using code we provide.
DataON is Korea's National Research Data Platform. It provides integrated search of metadata for KISTI's research data and domestic and international research data and links to raw data. DataON allows users (researchers, policy makers, etc.) to perform the following tasks: Easily search for various types of research data in all scientific fields. By registering research results, research data can be posted and cited. Build a community among researchers and enable collaborative research. It provides a data analysis environment that allows one-stop analysis of discovered research data.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
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Research Data Australia is the data discovery service of the Australian Research Data Commons (ARDC). The ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program. Research Data Australia helps you find, access, and reuse data for research from over one hundred Australian research organisations, government agencies, and cultural institutions. We do not store the data itself here but provide descriptions of, and links to, the data from our data publishing partners.
Europeana is the trusted source of cultural heritage brought to you by the Europeana Foundation and a large number of European cultural institutions, projects and partners. It’s a real piece of team work. Ideas and inspiration can be found within the millions of items on Europeana. These objects include: Images - paintings, drawings, maps, photos and pictures of museum objects Texts - books, newspapers, letters, diaries and archival papers Sounds - music and spoken word from cylinders, tapes, discs and radio broadcasts Videos - films, newsreels and TV broadcasts All texts are CC BY-SA, images and media licensed individually.
The ADS is an accredited digital repository for heritage data that supports research, learning and teaching with freely available, high quality and dependable digital resources by preserving and disseminating digital data in the long term. The ADS also promotes good practice in the use of digital data, provides technical advice to the heritage community, and supports the deployment of digital technologies.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
Sound and Vision has one of the largest audiovisual archives in Europe. The institute manages over 70 percent of the Dutch audiovisual heritage. The collection contains more than a million hours of television, radio, music and film from the beginning in 1898 until today. All programs of the Dutch public broadcasters come in digitally every day. Individuals and institutions entrust their collection to Sound and Vision as well. The institute ensures that the material is optimally preserved for (re)use. Broadcasters, producers and editors use the archive for the creation of new programs. The collection is also used to develop products and services for a wide audience, such as exhibitions, iPhone applications, DVD boxes and various websites. The collection of Sound and Vision contains the complete radio and television archives of the Dutch public broadcasters; films of virtually every leading Dutch documentary maker; newsreels; the national music depot; various audiovisual corporate collections; advertising, radio and video material of cultural and social organizations, of scientific institutes and of all kinds of educational institutions. There are also collections of images and articles from the history of Dutch broadcasting itself, like the elaborate collection of historical television sets.
The platform hosts the critical edition of the letters written to Jacob Burckhardt, reconstructing in open access one of the most important European correspondences of the 19th century. Save a few exceptions, these letters are all unpublished. On a later stage, the project aims to publish also Jacob Burckhardt’s letters. The editing process has been carried out using Muruca semantic digital library framework. The Muruca framework has been modified over the project, as the requirements of the philological researchers emerged more clearly. The results are stored in and accessible from the front-end of the platform.