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Found 62 result(s)

Energy Data eXchange

EDX

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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

Grouplens Datasets

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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.

ARM Data Center

Atmospheric Radiation Measurement Facility Data Center

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US Department of Energy’s Atmospheric Radiation Measurement (ARM) Data Center is a long-term archive and distribution facility for various ground-based, aerial and model data products in support of atmospheric and climate research. ARM facility currently operates over 400 instruments at various observatories (https://www.arm.gov/capabilities/observatories/). ARM Data Center (ADC) Archive currently holds over 11,000 data products with a total holding of over 3 petabytes of data that dates back to 1993, these include data from instruments, value added products, model outputs, field campaign and PI contributed data. The data center archive also includes data collected by ARM from related program (e.g., external data such as NASA satellite).

DataverseNL

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Online storage, sharing and registration of research data, during the research period and after its completion. DataverseNL is a shared service provided by participating institutions and DANS.

OpenML

Open Machine Learning

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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.

Repozytorium Uniwersytetu Łódzkiego

Repozytorium UŁ

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The University of Lodz Repository is an institutional repository whose purpose is to disseminate the scholarly output of its staff and promote research conducted at the UL. It is an archive of its own electronic documents – each deposited publication or collection of research data is given a permanent identifier (handle), enabling the document to be cited and indexed in scientific databases. The University of Lodz Repository operates as an institutional repository based on Regulation No. 51 of the Rector of the University of Lodz of 31 March 2015.

Stanford Digital Repository

SDR

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The Stanford Digital Repository (SDR) is Stanford Libraries' digital preservation system. The core repository provides “back-office” preservation services – data replication, auditing, media migration, and retrieval -- in a secure, sustainable, scalable stewardship environment. Scholars and researchers across disciplines at Stanford use SDR repository services to provide ongoing, persistent, reliable access to their research outputs.

Trinity River Restoration Program DataPort

TRRP DataPort

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The Online Data Portal (ODP) is an evolving project to support collaborative river restoration projects, such as the TRRP. The goal is to provide a centralized clearing house of documents and data for program partners, stakeholders, and the public. The functionality and data holdings will continue to be expanded over the next few years. The ability to store Data Packages is new as of Fall 2011 and holdings should expand substantially in the months afterward. A project to scan many older documents also began in December 2011. Simple time-series datasets have long been stored in the ODP, but holdings of these data are likely to increase as TRRP implements an upcoming Data Management and Utility Plan. Major upgrades to the Interactive Map are expected to start in winter and spring of 2012. The long term vision is that many data resources will be accessible both by text searches and via the Interactive Map. The ODP will be available for use by other river restoration programs. ODP is followed by TRRP DataPort.

FHSTP Phaidra

Phaidra

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Phaidra is the Institutional Repository and Digital Asset Management System of the St. Pölten University of Applied Sciences. The researchers and students at the University can use it to secure and archive their digital objects such as data, Open Access Publications and dissertations long-term as well as make them widely available to the public. Phaidra provides access to the objects using metadata in English and German. The Repository plays an important part in knowledge transfer in Austria and worldwide.

Open Access Power-Grid Frequency Database

OSF repository Open Access Power-Grid Frequency Database

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This repository stores and links the openly available power-grid frequency recordings across the globe. This database is comprised of open data existent across three dimensions: - TSO data: Transmission System's Operator (TSO) recordings made public; - Research projects: Open-data database research projects; - Independent Gatherings: Industrial, private, or personal recordings that were made publicly available.

Repositorio de datos de investigación de la Universidad del Rosario

Research data repository of Universidad del Rosario

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The Universidad del Rosario Research data repository is an institutional iniciative launched in 2019 to preserve, provide access and promote the use of data resulting from Universidad del Rosario research projects. The Repository aims to consolidate an online, collaborative working space and data-sharing platform to support Universidad del Rosario researchers and their collaborators, and to ensure that research data is available to the community, in order to support further research and contribute to the democratization of knowledge. The Research data repository is the heart of an institutional strategy that seeks to ensure the generation of Findable, Accessible, Interoperable and Reusable (FAIR) data, with the aim of increasing its impact and visibility. This strategy follows the international philosophy of making research data “as open as possible and as closed as necessary”, in order to foster the expansion, valuation, acceleration and reusability of scientific research, but at the same time, safeguard the privacy of the subjects. The platform storage, preserves and facilitates the management of research data from all disciplines, generated by the researchers of all the schools and faculties of the University, that work together to ensure research with the highest standards of quality and scientific integrity, encouraging innovation for the benefit of society.

Most Wiedzy Open Research Data Catalog

Most Wiedzy Katalog Danych Badawczych

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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.