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Found 11 result(s)

ScienceData

Data store by DTU - the Technical University of Denmark

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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.

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.

Jurisdictional Ocean Information Sharing System

JOISS

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The Jurisdictional Ocean Information Sharing System (JOISS) is a research activity to promote joint utilization of marine R&D projects and marine scientific materials at home and abroad. As a representative research activity, data curation activities are continuously carried out in accordance with the data life cycle to expand the utilization of the JOISS portal system. In order to provide integrated and standardized marine information, we are conducting standardization research for the distribution of marine geographic information metadata by referring to international standards and domestic and international marine data centers. In addition, we provide information and guidance for marine education and research, and strive to strengthen the exchange of data between marine research data repositories.

EnviDat

Environmental Data Portal

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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.

Dados Abertos De Pesquisas

Repositório de Dados de Pesquisas do Instituto Federal Goiano – Campus Urutaí

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Research Data Repository of the Instituto Federal Goiano - Campus Urutaí, a Brazilian public institution of the Ministry of Education. The project is an initiative of the Directorate of Post-Graduate Studies, Research and Innovation of the Federal Institute of Goiás - Campus Urutaí, which follows the philosophy of Open Science, for expansion and valuation of scientific research, aiming to provide data from technical-scientific observations and experimentation, ensuring that its authors, researchers and students receive all the credit they deserve as agents generating data. At the same time, the appropriate reuse of data is envisaged, whether in didactic-pedagogical activities or in new research.

Gramene

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Gramene is a platform for comparative genomic analysis of agriculturally important grasses, including maize, rice, sorghum, wheat and barley. Relationships between cereals are queried and displayed using controlled vocabularies (Gene, Plant, Trait, Environment, and Gramene Taxonomy) and web-based displays, including the Genes and Quantitative Trait Loci (QTL) modules.

Open Forest Data

e-Puszcza

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Podlasie digital repository of natural science data

myExperiment

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myExperiment is a collaborative environment where scientists can safely publish their workflows and in silico experiments, share them with groups and find those of others. Workflows, other digital objects and bundles (called Packs) can now be swapped, sorted and searched like photos and videos on the Web. Unlike Facebook or MySpace, myExperiment fully understands the needs of the researcher and makes it really easy for the next generation of scientists to contribute to a pool of scientific methods, build communities and form relationships — reducing time-to-experiment, sharing expertise and avoiding reinvention. myExperiment is now the largest public repository of scientific workflows.

Ensembl Plants

e!EnsemblPlants

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EnsemblPlants is a genome-centric portal for plant species. Ensembl Plants is developed in coordination with other plant genomics and bioinformatics groups via the EBI's role in the transPLANT consortium.

InGeoCloudS

Inspired GEOdata CLOUD Services

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<<<!!!<<< The repository is no longer available. Information about the project see https://www.pole-inside.fr/en/page/ingeoclouds or https://www.eurogeosurveys.org/projects/ingeoclouds/>>>!!!>>>

DataverseNO

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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.