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http://search.driver.research-infrastructures.eu/
Data infrastructure project that merged with OpenAIRE. Cohesive, robust and flexible, pan-European infrastructure for digital repositories, offering sophisticated services and functionalities for researchers, administrators and the general public. Access the network of freely accessible digital repositories with content across academic disciplines with over 3,500,000 scientific publications, found in journal articles, dissertations, books, lectures, reports, etc., harvested regularly from more than 295 repositories, from 38 countries. DRIVER has established a network of relevant experts and Open Access repositories. DRIVER-II will consolidate these efforts and transform the initial testbed into a fully functional, state-of-the art service, extending the network to a larger confederation of repositories. It aims to optimize the way the e-Infrastructure is used to store knowledge, add value to primary research data and information making secondary research more effective, provide a valuable asset for industry, and help bridging research and education. The objectives of DRIVER-II, the second phase of the project, include efforts to expand, enrich, and strengthen the results of DRIVER, in the following areas: * strategic geographic and community expansion by means of the DRIVER confederation * establish a robust, scalable repository infrastructure accompanied by an open source software package D-Net * broader coverage of content through the use of enhanced publications * advanced end-user functionality to support scientific exploration of complex digital objects * larger outreach and advocacy programs * continued repository support * guidelines for interoperability in the larger European digital library community
Proper citation: Digital Repository Infrastructure Vision for European Research (RRID:SCR_002752) Copy
Central data repository that supplies organisms and reagents to the broad community of microbiology and infectious diseases researchers.
Proper citation: BEI Resource Repository (RRID:SCR_013698) Copy
Provides online, collaborative working space and data-sharing platform. Provides services with data management planning, boilerplate text for proposal, sample plans and individual consultation. Each dataset gets DOI. PURR publishes and archives digital datasets from researchers across campus and welcomes all kinds of open data from images and videos to spreadsheets and source code.
Proper citation: Purdue University Research Repository (PURR) (RRID:SCR_027877) Copy
https://models.physiomeproject.org
Repository of mainly CellML models powered by collection of software tools and libraries with PMR2 software suite as core power. Third party integration suites are RICORDO, Virtuoso, BiVeS/BudHat, OpenCOR, CombineArchive Web, WebCAT, Morre/MaSyMoS.
Proper citation: Physiome Model Repository (RRID:SCR_017374) Copy
https://simtk.org/home/cv-gmodels
Repository of geometric models collected from on-going and past research projects in the Cardiovascular Biomechanics Research Laboratory at Stanford University. The geometric models are mostly built from imaging data of healthy and diseased individuals. For each of the models, a short description is given with a reference. The geometric models are in VTK PolyData XML .vtp format. * Audience: Biomechanical and computational researchers interested in complex models of cardiovascular applications * Long Term Goals and Related Uses: Allow users to download geometric models for cardiovascular applications. These geometric models can be used for research purposes, such as meshing and scientific visualization. Users are welcome to contact the project administrator, join the project and contribute additional models.
Proper citation: Cardiovascular Model Repository (RRID:SCR_002679) Copy
THIS RESOURCE IS NO LONGER IN SERVICE.Documented on January 14, 2023. Infrastructure for sharing data, tools and services, this virtual research environment (VRE) supports e-Neuroscience and is designed to provide services for data and processing of that data. While the system is initially focused on electrophysiology data (neural activity recordings are the primary data types), it is equally applicable to many domains outside neuroscience. The Portal Provides: * User login and customization. * Data upload/download. * Data handling including custom permissions for public, shared or private data. * The ability to invoke custom public, shared or private services that consume and produce data. For example, it would allow spike series to be run through a sorter, producing new data representing the sorted spikes. * The ability to host services written in a number of languages including, but not limited to Matlab, R, Python, Perl, Java. * A system to support metadata for data objects, which provides extensive support for entering metadata at the point of upload, and allows the generation of metadata from services to provide provenance information. * The ability to invoke additional visualization for the data, for example, via the Signal Data Explorer. A core part is the development of: (i) minimum reporting guidelines for annotation of data and other computational resources for the purpose of sharing, and; (ii) intermediate formats and APIs for translation between proprietary and bespoke data types. These recommendations are being implemented and the global community is encouraged both to engage in their specification and make use of them for their own data sharing systems. * MINI: Minimum Information about a Neuroscience Investigation - This framework represents the formalized opinion of the CARMEN consortium and its associates, and identifies the minimum reporting information required to support the use of electrophysiology in a neuroscience study, for submission to the CARMEN system. * NDTF: Neurophysiology Data Translation Format - This framework provides a vendor-independent mechanism for translating between raw and processed neurphysiology data in the form of time and image series. They are implementing NDTF in CARMEN but it may also be useful for third party applications.
Proper citation: Code Analysis Repository and Modelling for e-Neuroscience (RRID:SCR_002795) Copy
An article repository which archives peer-reviewed papers and non-peer-reviewed preprints in PeerJ. It includes papers and preprints from the biological and medical sciences PeerJ journal and from the computer science PeerJ journal.
Proper citation: PeerJ Article Repository (RRID:SCR_014698) Copy
https://edspace.american.edu/openbehavior/project/laubach-lab-github-repository/
Portal related to control and decision making, focusing on role of prefrontal cortex. American University scientists through their GitHub repository provide 3D print files for many of behavioral devices used in their lab, including Nosepoke and Lickometer designed from rats.
Proper citation: Laubach Lab GitHub Repository project (RRID:SCR_021464) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. A repository of models of neuronal networks maintained by the Nengo (http://nengo.org) project. Most but not all models use Nengo. Nengo is a graphical and scripting based software package for simulating large-scale neural systems.
Proper citation: Repository of neural and cognitive models (RRID:SCR_000822) Copy
International registry of institutional open access mandates. Total Mandates to Date (by type) (2013): * Institutional Mandates (166) * Sub-Institutional Mandates (36) * Multi-Institutional Mandates (4) * Funder Mandates (80) * Thesis Mandates (101) * Proposed Institutional Mandates (6) * Proposed Sub-Institutional Mandates (4) * Proposed Multi-Institutional Mandates (6) * Proposed Funder Mandates (11)
Proper citation: ROARMAP: Registry of Open Access Repositories Mandatory Archiving Policies (RRID:SCR_005950) Copy
Cardiovascular Biorepository for Type 1 Diabetes Program (CaRe-T1D) to fill a major void of knowledge that exists related to cardiovascular disease in type 1 diabetes.
Proper citation: NIH Cardiovascular Repository for Type 1 Diabetes (RRID:SCR_027353) Copy
Cell repository for Alzheimer's disease that collects and maintains biological specimens and associated data. Its data is derived from large numbers of genetically informative, phenotypically well-characterized families with multiple individuals affected with Alzheimer's disease, as well as individuals for case-control studies.
Proper citation: National Cell Repository for Alzheimer's Disease (RRID:SCR_007313) Copy
http://www.nitrc.org/projects/ibsr
Data set of manually-guided expert segmentation results along with magnetic resonance brain image data. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results. Please see the MediaWiki for more information. This repository is meant to contain standard test image data sets which will permit a standardized mechanism for evaluation of the sensitivity of a given analysis method to signal to noise ratio, contrast to noise ratio, shape complexity, degree of partial volume effect, etc. This capability is felt to be essential to further development in the field since many published algorithms tend to only operate successfully under a narrow range of conditions which may not extend to those experienced under the typical clinical imaging setting. This repository is also meant to describe and discuss methods for the comparison of results.
Proper citation: Internet Brain Segmentation Repository (RRID:SCR_001994) Copy
http://www.ldeo.columbia.edu/core-repository
Core repository and one of the world's most unique and important collections of scientific samples from the deep sea. Sediment cores from every major ocean and sea are archived at the Core Repository. The collection contains approximately 72,000 meters of core composed of 9,700 piston cores; 7,000 trigger weight cores; and 2,000 other cores such as box, kasten, and large diameter gravity cores. They also hold 4,000 dredge and grab samples, including a large collection of manganese nodules, many of which were recovered by submersibles. Over 100,000 residues are stored and are available for sampling where core material is expended. In addition to physical samples, a database of the Lamont core collection has been maintained for nearly 50 years and contains information on the geographic location of each collection site, core length, mineralogy and paleontology, lithology, and structure, and more recently, the full text of megascopic descriptions. Samples from cores and dredges, as well as descriptions of cores and dredges (including digital images and other cruise information), are provided to scientific investigators upon request. Materials for educational purposes and museum displays may also be made available in limited quantities when requests are adequately justified. Various services and data analyses, including core archiving, carbonate analyses, grain size analyses, and RGB line scan imaging, GRAPE, P-wave velocity and magnetic susceptibility runs, can also be provided at cost. The Repository operates a number of labs and instruments dedicated to making fundamental measurements on material entering the repository including several non-destructive methods. Instruments for conducting and/or assisting with analyses of deep-sea sediments include a GeoTek Multi-Sensor Core Logger, a UIC coulometer, a Micromeritics sedigraph, Vane Shear, X-radiograph, Sonic Sifter, freeze dryer, as well as a variety of microscopes, sieves, and sampling tools. They also make these instruments available to the scientific community for conducting analyses of deep-sea sediments. If you are interested in borrowing any field equipment, please contact the Repository Curator.
Proper citation: Lamont-Doherty Core Repository (RRID:SCR_002216) Copy
Curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts.
Proper citation: Biological General Repository for Interaction Datasets (BioGRID) (RRID:SCR_007393) Copy
https://edspace.american.edu/openbehavior/project/hao-chen-lab-repository/
Project aims to establish computing platform for rodent behavior research using Raspberry Pi computer. They have built several devices for conducting operant conditioning and monitoring environmental data.
Proper citation: Hao Chen Lab Repository project (RRID:SCR_021467) Copy
Collection of databases, domain theories, and data generators that are used by machine learning community for empirical analysis of machine learning algorithms. Datasets approved to be in the repository will be assigned Digital Object Identifier (DOI) if they do not already possess one. Datasets will be licensed under a Creative Commons Attribution 4.0 International license (CC BY 4.0) which allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given
Proper citation: UCI Machine Learning Repository (RRID:SCR_026571) Copy
https://github.com/google/fully-homomorphic-encryption
Software toolkit to perform Fully Homomorphic Encryption operations on encrypted data set. FHE compiler for C++ that converts subset of C++ programs into FHE circuits implemented in various backend libraries.
Proper citation: Fully Homomorphic Encryption Repository (RRID:SCR_025207) Copy
http://sig.biostr.washington.edu/projects/wirm/
WIRM is an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. WIRM reduces the complexity of building custom biomedical web applications and it's visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems. WIRM is a Perl-based application server that provides a high-level programming environment for developing web information systems. WIRM consists of an object-relational database and a suite of Perl interfaces for visualizing, integrating and analyzing heterogeneous multimedia data. WIRM provides facilities for creating context-sensitive views over a multimedia database, allowing developers to rapidly build dynamic web sites that adapt their content and presentation to multiple classes of end-users. WIRM was developed by Rex Jakobovits as part of his PhD dissertation at the University of Washington Computer Science department, under the guidance of Dr. James F. Brinkley of the Department of Biological Structure. The system was generalized from work funded by NIH SBIR grant R43-MH61277-01 and Human Brain Project grant DC/LM02310.
Proper citation: WIRM - Web Interfacing Repository Manager (RRID:SCR_002039) Copy
http://amser.org./index.php?P=AMSER--About
AMSER is a portal of educational resources and services built specifically for use by those in Community and Technical Colleges but free for anyone to use. AMSER provides links to resources for faculty, staff, librarians, students and others for use in both educational settings or in their pursuit of life long learning. Sponsors: AMSER is funded by the National Science Foundation (NSF) as part of the National Science Digital Library, and is being created by a team of project partners led by Internet Scout.
Proper citation: Applied Math and Science Education Repository (RRID:SCR_008501) Copy
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