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Found 60 result(s)
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.
Research Data Australia is the data discovery service of the Australian National Data Service (ANDS). We do not store the data itself here but provide descriptions of, and links to, the data from our data publishing partners. ANDS is funded by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS).
<<< 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.
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
The edoc-Server, start 1998, is the Institutional Repository of the Humboldt-Universität zu Berlin and offers the posibility of text- and data-publications. Every item is published for Open-Access with an optional embargo period of up to five years. Data publications since 01.01.2018.
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
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.
Monash.figshare is Monash University’s institutional data repository. It allows researchers to store, manage and showcase their data while retaining control over access rights and re-use conditions. Monash.figshare offers the latest in cloud-based technology, ensures valuable research data is stored securely, and supports long-term citations with Digital Object Identifiers (DOIs).
The Spiral Digital Repository is the Imperial College London institutional open access repository. This system allows you, as an author, to make your research documents open access without incurring additional publication costs. When you self-archive a research document in Spiral it becomes free for anyone to read. You can upload copies of your publications to Spiral using Symplectic Elements. All deposited content becomes searchable online.
BExIS is the online data repository and information system of the Biodiversity Exploratories Project (BE). The BE is a German network of biodiversity related working groups from areas such as vegetation and soil science, zoology and forestry. Up to three years after data acquisition, the data use is restricted to members of the BE. Thereafter, the data is usually public available (
The Detection of Archaeological Residues using Remote-sensing Techniques (DART) project was initiated in 2010 in order to investigate the ability of various sensors to detect archaeological features in ‘difficult’ circumstances. Concluding in September 2013, DART had the overall aim of developing analytical methods for identifying and quantifying gradual changes and dynamics in sensor responses associated with surface and near-surface archaeological features under different environmental and land-management conditions.
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).
"Deposit Once" is the repository for research data and publications of TU Berlin. It is an institutional repository for deposition and storage of research data from many different disciplines. "Deposit Once" is also a service platform that provides value-added services - including the reusability of existing data, automated workflows for the detection of research results and other added values ​​for the scientists / inside.
Research Data Finder is QUT’s discovery service for research data created or collected by QUT researchers. Designed to promote the visibility of QUT research datasets, Research Data Finder provides descriptions about shareable, reusable datasets available via open or mediated access.
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.
Figshare has been chosen as the University of Adelaide's official data and digital object repository with unlimited local storage. All current staff and HDR students can access and publish research data and digital objects on the University of Adelaide's Figshare site. Because Figshare is cloud-based, you can access it anywhere and at any time.
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.
LINDAT/CLARIN is designed as a Czech “node” of Clarin ERIC (Common Language Resources and Technology Infrastructure). It also supports the goals of the META-NET language technology network. Both networks aim at collection, annotation, development and free sharing of language data and basic technologies between institutions and individuals both in science and in all types of research. The Clarin ERIC infrastructural project is more focused on humanities, while META-NET aims at the development of language technologies and applications. The data stored in the repository are already being used in scientific publications in the Czech Republic.
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.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.