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Found 23 result(s)
GroupLens is a research lab in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities specializing in recommender systems, online communities, mobile and ubiquitous technologies, digital libraries, and local geographic information systems.
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).
<<< has been discontinued !!! >>> (ORD@CH) has been developed as a publication platform for open research data in Switzerland. It currently offers a metadata catalogue of the data available at the participating institutions (ETH Zurich Scientific IT Services, FORS Lausanne, Digital Humanities Lab at the University of Basel). In addition, metadata from other institutions is continuously added, with the goal to develop a comprehensive metadata infrastructure for open research data in Switzerland. The ORD@CH project is part of the program „Scientific information: access, processing and safeguarding“, initiated by the Rectors’ Conference of Swiss Universities (Program SUC 2013-2016 P-2). The portal is currently hosted and developed by ETH Zurich Scientific IT Services.
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.
Welcome to the largest bibliographic database dedicated to Economics and available freely on the Internet. This site is part of a large volunteer effort to enhance the free dissemination of research in Economics, RePEc, which includes bibliographic metadata from over 1,800 participating archives, including all the major publishers and research outlets. IDEAS is just one of several services that use RePEc data. Authors are invited to register with RePEc to create an online profile. Then, anyone finding some of your research here can find your latest contact details and a listing of your other research. You will also receive a monthly mailing about the popularity of your works, your ranking and newly found citations. Besides that IDEAS provides software and public accessible data from Federal Reserve Bank.
The JAE Data Archive, which is hosted by a server belonging to the Economics Department of Queen's University, contains data for all papers accepted after January, 1994, unless the data are confidential. There are also data for a few papers accepted earlier. Volume 10, No. 1 (1995) is the first issue in which all papers were accepted subject to the proviso that data be provided. For some papers, especially more recent ones, the Data Archive also contains programs and supplementary material, such as technical appendices and additional graphs.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, documents or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. In the following cases, a direct data upload into the ETH Data Archive though, has to be considered: - Upload and registration of software code according to ETH transfer’s requirements for Software Disclosure. - A substantial number of files, have to be regularly submitted for long-term archiving and/or publishing and browser-based upload is not an option: the ETH Data Archive may offer automated data and metadata transfers from source applications (e.g. from a LIMS) via API. - Files for a project on a local computer have to be collected and metadata has to be added before uploading the data to the ETH Data Archive: -- we provide you with the local file editor docuteam packer. Docuteam packer allows to structure, describe, and organise data for an upload into the ETH Data Archive and the depositor decides when submission is due.
KONECT (the Koblenz Network Collection) is a project to collect large network datasets of all types in order to perform research in network science and related fields, collected by the Institute of Web Science and Technologies at the University of Koblenz–Landau. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.
It is a statistical system developed for collection, computerization, analysis and use of educational and allied data for planning, management, monitoring and feedback. So, DISE is an initiative of the Department of Educational Management Information System (EMIS) of NUEPA for developing and strengthening the educational management information system in India. The initiative is coordinated from district level to state and extended up to national level are being constantly collected and disseminated. It provides information on vital parameters relating to students, teachers and infrastructure at all levels of education in India. Presently DISE has three modules U-DISE, DISE, and SEMIS. DISE also provides several other derivative statistical products, such as, District Report Cards, State Report Cards, School Report Cards, Flash Statistics, Analytical Reports, Rural/Urban Statistics, etc.
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.
We are developing an open, online platform to provide a seamless access to cloud computing infrastructure and brain data and data derivatives. This platform is meant to reach out beyond neuroscience, allowing also computer scientists, statisticians and engineers interested in brain data to use the data to develop and publish their methods. Brain Life is a project under active development. We currently offer several cloud computing services – also called Brain Life Applications. Sixty-six collaborators from global scientific communities contribute to the project by providing data, applications, technology and products to advance understanding the human brain.
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.
Academic Commons is a freely accessible digital collection of research and scholarship produced at Columbia University or one of its affiliate institutions (Barnard College, Teachers College, Union Theological Seminary, and Jewish Theological Seminary). The mission of Academic Commons is to collect and preserve the digital outputs of research and scholarship produced at Columbia and its affiliate institutions and present them to a global audience. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
The focus of PolMine is on texts published by public institutions in Germany. Corpora of parliamentary protocols are at the heart of the project: Parliamentary proceedings are available for long stretches of time, cover a broad set of public policies and are in the public domain, making them a valuable text resource for political science. The project develops repositories of textual data in a sustainable fashion to suit the research needs of political science. Concerning data, the focus is on converting text issued by public institutions into a sustainable digital format (TEI/XML).
The Odum Institute Dataverse Network provides access to data collections curated by the Odum Institute as well as collections owned by other institutions and individual scholars. You can search across or browse any of these dataverses listed below. You may also create your own branded dataverse to manage and provide access to your data.