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Found 63 result(s)
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idUS is the digital archive that gives access to full text of the scientific production of the University of Seville and their datasets. Its objective is to gather, preserve and disseminate the documents and data resulting from the scientific activity of the University, making the documents visible, accessible, recoverable, usable and preservable for any user.
DaSCH is the trusted platform and partner for open research data in the Humanities. DaSCH develops and operates a FAIR long-term repository and a generic virtual research environment for open research data in the humanities in Switzerland. We provide long-term direct access to the data, enable their continuous editing and allow for precise citation of single objects within a dataset. We ensure interoperability with tools used by the Humanities and Cultural Sciences communities and foster the use of standards. The development of our platform happens in close cooperation with these communities. We provide training and advice in the area of research data management, promote open data and the use of standards. DaSCH is the coordinating institution and representative of Switzerland in the European Research Infrastructure Consortium ‘Digital Research Infrastructure for the Arts and Humanities’ (DARIAH ERIC). Within this mandate, we actively engage in community building within Switzerland and abroad. DaSCH cooperates with national and international organizations and initiatives in order to provide services that are fit for purpose within the broader Swiss open research data landscape and that are coordinated with other institutions such as FORS. We base our actions on the values reliability, flexibility, appreciation, curiosity, and persistence. Furthermore, DARIAH’s activities in Switzerland are coordinated by DaSCH and DaSCH is acting as DARIAH-CH Coordination Office.
With the Program EnviDat we develop a unified and managed access portal for WSL's rich reservoir of environmental monitoring and research data. EnviDat is designed as a portal to publish, connect and search across existing data but is not intended to become a large data centre hosting original data. While sharing of data is centrally facilitated, data management remains decentralised and the know-how and responsibility to curate research data remains with the original data providers.
The Plant Metabolic Network (PMN) provides a broad network of plant metabolic pathway databases that contain curated information from the literature and computational analyses about the genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism in plants. The PMN currently houses one multi-species reference database called PlantCyc and 22 species/taxon-specific databases.
nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.
Open Research Exeter (ORE) is the University of Exeter's repository for all types of research, including research papers, research data and theses. Research in ORE can be viewed and downloaded freely by anyone, anywhere: researchers, students, industry, business and the wider public. ORE's content includes journal articles, conference papers, working papers, reports, book chapters, videos, audio, images, multimedia research project outputs, raw data and analysed data. ORE's content is securely stored, managed and preserved to ensure free, permanent access.
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.
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FDAT is a research data repository hosted by the University of Tübingen, designed to facilitate long-term archiving and publication of research data. Managed by the Information, Communication and Media Center (IKM), it primarily caters to the humanities and social sciences, while welcoming researchers from all scientific disciplines at the university. Committed to high-quality data management, FDAT emphasizes the importance of adhering to the FAIR Data Principles, promoting findability, accessibility, interoperability, and reusability of the research data it contains.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
<<<!!!<<< This MultiDark application is now integrated into CosmoSim (https://www.cosmosim.org/ , all data and much more is available there. The old MultiDark server is no longer available. >>>!!!>>> The MultiDark database provides results from cosmological simulations performed within the MultiDark project. This database can be queried by entering SQL statements directly into the Query Form. The access to that form and thus access to the public & private databases is password protected.
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Science Data Bank is an open generalist data repository developed and maintained by the Chinese Academy of Sciences Computing and Network Information Center (CNIC). It promotes the publication and reuse of scientific data. Researchers and journal publishers can use it to store, manage and share science data.
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Discuss Data is an open repository for storing, sharing and discussing research data on Eastern Europe, the South Caucasus and Central Asia. The platform, launched in September 2020, is funded by the German Research Foundation (DFG) and operated by the Research Centre for East European Studies at the University of Bremen (FSO) and the Göttingen State and University Library (SUB). Discuss Data goes beyond ordinary repositories and offers an interactive online platform for the discussion and quality assessment of research data. Our aim is to create a space for academic communication and for the community-specific publication, curation, annotation and discussion of research data.
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.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
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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.
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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The National High Energy Physics Science Data Center (NHEPSDC) is a repository for high-energy physics. In 2019, it was designated as a scientific data center at the national level by the Ministry of Science and Technology of China (MOST). NHEPSDC is constructed and operated by the Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences (CAS). NHEPSDC consists of a main data center in Beijing, a branch center in Guangdong-Hong Kong-Macao Greater Bay Area, and a branch center in Huairou District of Beijing. The mission of NHEPSDC is to provide the services of data collection, archiving, long-term preservation, access and sharing, software tools, and data analysis. The services of NHEPSDC are mainly for high-energy physics and related scientific research activities. The data collected can be roughly divided into the following two categories: one is the raw data from large scientific facilities, and the other is data generated from general scientific and technological projects (usually supported by government funding), hereafter referred to as generic data. More than 70 people work in NHEPSDC now, with 18 in high-energy physics, 17 in computer science, 15 in software engineering, 20 in data management and some other operation engineers. NHEPSDC is equipped with a hierarchical storage system, high-performance computing power, high bandwidth domestic and international network links, and a professional service support system. In the past three years, the average data increment is about 10 PB per year. By integrating data resources with the IT environment, a state-of-art data process platform is provided to users for scientific research, the volume of data accessed every year is more than 400 PB with more than 10 million visits.
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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.
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This site provides access to over 210,000 digitized or born-digital images in the Koç University collections featuring prints, photographs, slides, maps, newspapers, posters, postcards, manuscripts, streaming video, and more. The collections consist of the materials of the Koç University Libraries and Archives (AKMED, ANAMED, SKL, and VEKAM), Koç University Faculty and Departments, and projects carried out in partnership with the Koç University Libraries. It includes the Koç University Institutional Repository (KU-IR).
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.