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Found 41 result(s)
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The Leibniz Data Manager (LDM) is a scientific repository for research data from the fields of science and technology. The service supports a better re-usability of research data for scientific projects. The LDM fosters the management and access to heterogeneous research data publications and assists researchers in the selection of relevant data sets for their respective disciplines. The LDM currently offers the following functions for the visualization of research data: · Supports data collections and publications with different formats. · Different views on the same data set (2D and 3D support). · Visualization of Auto CAD files. · Jupyter Notes for demonstrating live code. · RDF Description of data collections.
The Energy Data eXchange (EDX) is an online collection of capabilities and resources that advance research and customize energy-related needs. EDX is developed and maintained by NETL-RIC researchers and technical computing teams to support private collaboration for ongoing research efforts, and tech transfer of finalized DOE NETL research products. EDX supports NETL-affiliated research by: Coordinating historical and current data and information from a wide variety of sources to facilitate access to research that crosscuts multiple NETL projects/programs; Providing external access to technical products and data published by NETL-affiliated research teams; Collaborating with a variety of organizations and institutions in a secure environment through EDX’s ;Collaborative Workspaces
IoT Lab is a research platform exploring the potential of crowdsourcing and Internet of Things for multidisciplinary research with more end-user interactions. IoT Lab is a European Research project which aims at researching the potential of crowdsourcing to extend IoT testbed infrastructure for multidisciplinary experiments with more end-user interactions. It addresses topics such as: - Crowdsourcing mechanisms and tools; - “Crowdsourcing-driven research”; - Virtualization of crowdsourcing and testbeds; - Ubiquitous Interconnection and Cloudification of testbeds; - Testbed as a Service platform; - Multidisciplinary experiments; - End-user and societal value creation; - Privacy and personal data protection.
The IRI/LDEO Climate Data Library is a collection of climate data sets with the focus of climate change monitoring and mitigation. Browse data by category and source, navigate and analyze datasets using maps, and the Ingrid Data Analysis Language. The IRI/LDEO also includes web tutorials.
The JRC Data Catalogue gives access to the multidisciplinary data produced and maintained by the Joint Research Centre, the European Commission's in-house science service providing independent scientific advice and support to policies of the European Union.
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<<<!!!<<< The repository is no longer available 2020-02-21: no more access to "Environment Climate Data Sweden" >>>!!!<<< The transfer of records from the Environment Climate Data Sweden (ECDS) database to the Swedish National Dataservice (SND) https://www.re3data.org/repository/r3d100010146 was completed in 2019. SND is a national research infrastructure with a primary function to support the accessibility, preservation, and re-use of research data and related materials. You can search the SND research data portal specifically for Natural Science or Agricultural and Veterinary Sciences datasets. Data descriptions with associated datasets, or a direct reference/URL to data, have been migrated from the ECDS portal to the SND research data portal. Previous links to these data are now automatically directed to an SND catalogue entry. Records in the ECDS catalogue that only contained metadata (ie information that data could be accessed through another portal, e.g. Pangea), now link directly to the portal in question. If you want to make one of those data descriptions searchable in SND’s catalogue, please contact SND on snd@snd.gu.se. A small number of records were neither migrated to SND nor redirected to external providers, and they redirect. Contact SND on snd@snd.gu.se if you want more information about the closing of the ECDS portal and the migration of data descriptions to SND’s research data catalogue.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.
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Arquivo.pt is a research infrastructure that preserves millions of files collected from the web since 1996 and provides a public search service over this information. It contains information in several languages. Periodically it collects and stores information published on the web. Then, it processes the collect data to make it searchable, providing a “Google-like” service that enables searching the past web (English user interface available at https://arquivo.pt/?l=en). This preservation workflow is performed through a large-scale distributed information system and can also accessed through API (https://arquivo.pt/api).
MetabolomeXchange.org delivers the mechanisms needed for disseminating the data to the metabolomics community at large (both metabolomics researchers and databases). The main objective is to make it easier for metabolomics researchers to become aware of newly released, publicly available, metabolomics datasets that may be useful for their research. MetabolomeXchange contains datasets from different data providers: MetaboLights, Metabolomic Repository Bordeaux, Metabolomics Workbench, and Metabolonote
IATI is a voluntary, multi-stakeholder initiative that seeks to improve the transparency of aid, development, and humanitarian resources in order to increase their effectiveness in tackling poverty. IATI brings together donor and recipient countries, civil society organisations, and other experts in aid information who are committed to working together to increase the transparency and openness of aid. - See more at: https://iatistandard.org/en/about/#sthash.BYPZ6NPt.dpuf
Pandora is an open data platform devoted to the study of the human story. Data may be deposited from various disciplines and research topics that investigate humans from their early beginnings until present in addition to their environmental context (e.g. archeology, anthropology history, ancient DNA, isotopes, zooarchaeology, archaeobotany, and paleoenvironmental and paleoclimatic studies, etc.). Pandora allows autonomous data communities to self-manage their webspace and community membership. Data communities self-curate their data plus other supporting resources. Datasets may be assigned a new DOI and a schema markup is employed to improve data findability. Pandora also allows for links to datasets stored externally and having previously assigned DOIs. Through this, it becomes possible to establish data networks devoted to specific topics that may combine a mix of datasets stored either within Pandora or externally.
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Etsin is a research data finder that contains descriptive information – that is, metadata – on research datasets. In the service you can search and find data from various fields of research. A researcher, research group or organisation can use Etsin to publish information on their datasets and offer them for wider use. The metadata contained in Etsin makes it easy for anyone to discover the datasets. Etsin assigns a permanent URN identifier to datasets, making it possible to link to the dataset and gather merit through its publication and use. The metadata enables users to search for datasets and evaluate the potential for reuse. Etsin includes a description of the dataset, keywords and various dataset identifiers. The dataset information includes, for example, its subject, language, author, owner and how it is licensed for reuse. Good description of data plays an important role in its discoverability and visibility. Etsin encourages comprehensive descriptions by adapting a common set of discipline independent metadata fields and by making it easy to enter metadata. Etsin only collects metadata on datasets, not the data themselves. Anyone may browse and read the metadata. Etsin can be used with a browser or through an open interface (API). The service is discipline independent and free to use. Etsin is a service provided by the Ministry of Education and Culture to actors in the Finnish research system. The service is produced by CSC – IT Center for Science (CSC). Customer service contacts and feedback is available through servicedesk@csc.fi. The service maintenance window is on the fourth Monday of every month between 4 and 6 PM (EET). During that time, the service will be out of use.
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 MHKDR is the repository for all data collected using funds from the Water Power Technologies Office (WPTO) of the U.S. Department of Energy (DOE). It was established to receive, manage, and make available all water power relevant data generated from projects funded by the DOE Water Power Technologies Office. This includes data from WPTO-funded projects associated with any portion of the water power project life-cycle (exploration, development, operation), as well as data produced by WPTO-funded research.