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Found 47 result(s)
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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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QSAR DataBank (QsarDB) is repository for (Quantitative) Structure-Activity Relationships ((Q)SAR) data and models. It also provides open domain-specific digital data exchange standards and associated tools that enable research groups, project teams and institutions to share and represent predictive in silico models.
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DAIS - Digital Archive of the Serbian Academy of Sciences and Arts is a joint digital repository of the Serbian Academy of Sciences and Arts (SASA) and the research institutes under the auspices of SASA. The aim of the repository is to provide open access to publications and other research outputs resulting from the projects implemented by the SASA and its institutes. The repository uses a DSpace-based software platform developed and maintained by the Belgrade University Computer Centre (RCUB).
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Geoscientific Data & Discovery Publishing Center (GDD) is based on the geological scientific data generated globally, establishing policies and systems for the scientific data publishing, absorbing the concepts and methods of international open data, and joint Digital Object Unique Identifier-DOI registration agencies to provide standard data reference formats and permanent access address for data references, doing publishing through the Internet platform, which combines innovation and advance. GDD mainly includes data descriptor and entity data publishing. The data papers describe entity data and corresponding metadata information. The entity data includes common shared data such as geographic information, geologic maps, and databases, and also includes multiple data types, such as documents, archive records, data forms and other multimedia formed during geological work, various data-centric applications, database interface services, and typical data services.
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The nature of the ‘Bridge of Data’ project is to design and build a platform that allows collecting, searching, analyzing and sharing open research data and to provide it with unique data collected from the three most important Pomeranian universities: Gdańsk University of Technology, Medical University of Gdańsk and the University of Gdańsk. These data will be made available free of charge to the scientific community, entrepreneurs and the public. A bridge will be built to allow reuse of Open Research Data. The available research data will be described by standards developed by dedicated, experienced scientific teams. The metadata will allow other external computer systems to interpret the collected data. ORD descriptions will also include data reuse or reduction scenarios to facilitate further processing.
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The sources of the data sets include data sets donated by researchers, surveys carried out by SRDA, as well as by government department and other academic organizations. Prior to the release of data sets, the confidentiality and sensitivity of every survey data set are evaluated. Standard data management and cleaning procedures are applied to ensure data accuracy and completeness. In addition, metadata and relevant supplement files are also edited and attached.
The Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system was developed to share data across the entire TBI research field and to facilitate collaboration between laboratories, as well as interconnectivity with other informatics platforms. Sharing data, methodologies, and associated tools, rather than summaries or interpretations of this information, can accelerate research progress by allowing re-analysis of data, as well as re-aggregation, integration, and rigorous comparison with other data, tools, and methods. This community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches.
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.
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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.
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GESIS preserves (mainly quantitative) social research data to make it available to the scientific research community. The data is described in a standardized way, secured for the long term, provided with a permanent identifier (DOI), and can be easily found and reused through browser-optimized catalogs (https://search.gesis.org/).
e-cienciaDatos is a multidisciplinary data repository that houses the scientific datasets of researchers from the public universities of the Community of Madrid and the UNED, members of the Consorcio Madroño, in order to give visibility to these data, to ensure its preservation And facilitate their access and reuse. e-cienciaDatos is structured as a system constituted by different communities that collects datasets of each of the individual universities. e-cienciaDatos offers the deposit and publication of datasets, assigning a digital object identifier DOI to each of them. The association of a dataset with a DOI will facilitate data verification, dissemination, reuse, impact and long-term access. In addition, the repository provides a standardized citation for each dataset, which contains sufficient information so that it can be identified and located, including the DOI.
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
The goal of the Center of Estonian Language Resources (CELR) is to create and manage an infrastructure to make the Estonian language digital resources (dictionaries, corpora – both text and speech –, various language databases) and language technology tools (software) available to everyone working with digital language materials. CELR coordinates and organises the documentation and archiving of the resources as well as develops language technology standards and draws up necessary legal contracts and licences for different types of users (public, academic, commercial, etc.). In addition to collecting language resources, a system will be launched for introducing the resources to, informing and educating the potential users. The main users of CELR are researchers from Estonian R&D institutions and Social Sciences and Humanities researchers all over the world via the CLARIN ERIC network of similar centers in Europe. Access to data is provided through different sites: Public Repository https://entu.keeleressursid.ee/public-document, Language resources https://keeleressursid.ee/en/resources/corpora, and MetaShare CELR https://metashare.ut.ee/.
The Linguistic Data Consortium (LDC) is an open consortium of universities, libraries, corporations and government research laboratories. It was formed in 1992 to address the critical data shortage then facing language technology research and development. Initially, LDC's primary role was as a repository and distribution point for language resources. Since that time, and with the help of its members, LDC has grown into an organization that creates and distributes a wide array of language resources. LDC also supports sponsored research programs and language-based technology evaluations by providing resources and contributing organizational expertise. LDC is hosted by the University of Pennsylvania and is a center within the University’s School of Arts and Sciences.
Polish CLARIN node – CLARIN-PL Language Technology Centre – is being built at Wrocław University of Technology. The LTC is addressed to scholars in the humanities and social sciences. Registered users are granted free access to digital language resources and advanced tools to explore them. They can also archive and share their own language data (in written, spoken, video or multimodal form).
Currently, the IMS repository focuses on resources provided by the Institute for Natural Language Processing in Stuttgart (IMS) and other CLARIN-D related institutions such as the local Collaborative Research Centre 732 (SFB 732) as well as institutions and/or organizations that belong to the CLARIN-D extended scientific community. Comprehensive guidelines and workflows for submission by external contributors are being compiled based on the experiences in archiving such in-house resources.
eLaborate is an online work environment in which scholars can upload scans, transcribe and annotate text, and publish the results as on online text edition which is freely available to all users. Short information about and a link to already published editions is presented on the page Editions under Published. Information about editions currently being prepared is posted on the page Ongoing projects. The eLaborate work environment for the creation and publication of online digital editions is developed by the Huygens Institute for the History of the Netherlands of the Royal Netherlands Academy of Arts and Sciences. Although the institute considers itself primarily a research facility and does not maintain a public collection profile, Huygens ING actively maintains almost 200 digitally available resource collections.
The DNB Household Survey (DHS) supplies longitudinal data to the international academic community, with a focus on the psychological and economic aspects of financial behavior. The study comprises information on work, pensions, housing, mortgages, income, assets, loans, health, economic and psychological concepts, and personal characteristics. The DHS data are collected from 2,000 households participating in the CentERpanel. The CentERpanel is an Internet panel that reflects the composition of the Dutch-speaking population in the Netherlands. Both the DHS as well as the CentERpanel, in which the study in conducted, are run by CentERdata
The focus of CLARIN INT Portal is on resources that are relevant to the lexicological study of the Dutch language and on resources relevant for research in and development of language and speech technology. For Example: lexicons, lexical databases, text corpora, speech corpora, language and speech technology tools, etc. The resources are: Cornetto-LMF (Lexicon Markup Framework), Corpus of Contemporary Dutch (Corpus Hedendaags Nederlands), Corpus Gysseling, Corpus VU-DNC (VU University Diachronic News text Corpus), Dictionary of the Frisian Language (Woordenboek der Friese Taal), DuELME-LMF (Lexicon Markup Framework), Language Portal (Taalportaal), Namescape, NERD (Named Entity Recognition and Disambiguation) and TICCLops (Text-Induced Corpus Clean-up online processing system).
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.