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Found 14 result(s)
Country
AUSSDA - The Austrian Social Science Data Archive is a certified, national research infrastructure for the social science community. We offer sustainable and easy-to-use services in the field of digital archiving and preservation. The main beneficiaries are researchers, students, educational institutions and media professionals. We implement international standards to make research data findable, accessible, interoperable and reusable according to the FAIR principles. AUSSDA supports the open science movement to maximize the potential for data reuse. We stand for integrity in archiving and advocate for compliance with data protection and ethical principles in research data management. AUSSDA represents Austria as a national service provider in CESSDA ERIC, has locations at the universities of Vienna, Graz, Linz, Innsbruck, Krems and at the OeAW (Austrian Academy of Sciences) and works within a network of national and international partners.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
Country
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.
The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.
Country
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/).
Country
Sikt archives research data on people and society to make sure the data can be shared and is made available for reuse. We continuously enrich our data collections to provide a richer basis for research. Sikt’s main focus is quantitative data matrices on individuals, organisations, administrative, political, and geographical actors. The archive specialise in survey data, which undergoes extensive curation at the variable level and detailed metadata is produced and published in Norwegian and English.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
Country
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.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
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.
Country
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.