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http://www.delsaglobal.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 1, 2022. Organization whose mission is to build and promote a sustainable ecosystem of professional societies, funding agencies, foundations, companies, and citizens together with life science researchers and innovators in computing, infrastructure and analysis with the expressed goal of translating new discoveries into tools, resources and products.

Proper citation: DELSA (RRID:SCR_006231) Copy   

•   Source: SciCrunch Registry

https://www.xsede.org/

XSEDE is a single virtual system that scientists can use to interactively share computing resources, data and expertise. People around the world use these resources and services things like supercomputers, collections of data and new tools to improve our planet. XSEDE resources may be broadly categorized as follows: High Performance Computing, High Throughput Computing, Visualization, Storage, and Data Services. Many resources provide overlapping functionality across categories. Scientists, engineers, social scientists, and humanists around the world - many of them at colleges and universities - use advanced digital resources and services every day. Things like supercomputers, collections of data, and new tools are critical to the success of those researchers, who use them to make our lives healthier, safer, and better. XSEDE integrates these resources and services, makes them easier to use, and helps more people use them. XSEDE supports 16 supercomputers and high-end visualization and data analysis resources across the country. Digital services, meanwhile, provide users with seamless integration to NSF''s high-performance computing and data resources. XSEDE''s integrated, comprehensive suite of advanced digital services will federate with other high-end facilities and with campus-based resources, serving as the foundation for a national cyberinfrastructure ecosystem. Common authentication and trust mechanisms, global namespace and filesystems, remote job submission and monitoring, and file transfer services are examples of XSEDE''s advanced digital services. XSEDE''s standards-based architecture allows open development for future digital services and enhancements. XSEDE also provides the expertise to ensure that researchers can make the most of the supercomputers and tools.

Proper citation: XSEDE - Extreme Science and Engineering Discovery Environment (RRID:SCR_006091) Copy   

•   Source: SciCrunch Registry

https://commonfund.nih.gov/metabolomics/index

A US national program which supoorts the development of technologies in order to enhance the metabolomics field. It specifically increases the national metabolomics research capacity by supporting five core programs: Training in Metabolomics, Metabolomics Technology Development, Metabolomics Reference Standard Synthesis, Metabolomics Data Sharing and International Collaboration, and Comprehensive Metabolomics Resource Cores.

Proper citation: NIH Metabolomics program (RRID:SCR_014634) Copy   

•   Source: SciCrunch Registry

http://coins.mrn.org/

A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.

Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy   

•   Source: SciCrunch Registry

https://open-brain-consent.readthedocs.io/en/stable/

Platform for informing research participants and obtaining consent to share brain imaging data. Provides suggested wording/templates for MRI studies human participant consent forms (including GDPR version), reference of tools for data anonymization, etc to make prospective data sharing possible.

Proper citation: Open Brain Consent (RRID:SCR_022972) Copy   

•   Source: SciCrunch Registry

https://docs.osparc.io

Simulation platform that enables users to create, access, tune, and run models or computational algorithms through web based interface. Web interactive simulation platform that hosts SPARC computational models and solvers. Allows collaborative development and sharing, model coupling and cloud based execution, data visualization and analysis, and ensures sustainability of computational models developed within SPARC. Enables users to create predictive, multiscale, multi-physics models spanning from modulation sources acting on peripheral nervous system (PNS) to resulting modulation of organ functional response.

Proper citation: o²S²PARC (RRID:SCR_018997) Copy   

•   Source: SciCrunch Registry

https://www.data.casearth.cn/

Portal built for the release and sharing of data resources of "Big Earth Data Science Engineering Program (CASEarth)" launched by the Chinese Academy of Sciences. A global raster data of land cover and land use. This data can be used for mapping and spatial modeling in Geographic Information Systems (GIS) or other computer programs. This website is not accessible from the USA.

Proper citation: Chinese CASEarth Data Sharing and Service Portal (RRID:SCR_025660) Copy   

•   Source: SciCrunch Registry

http://genomicsandhealth.org/

An international coalition formed to enable the sharing of genomic and clinical data to help unlock potential advancements in medicine and science. Bringing together more than 145 leading institutions working in healthcare, research, disease advocacy, life science, and information technology, the Global Alliance is working together to create and promulgate harmonized approaches to enable the responsible, voluntary, and secure sharing of genomic and clinical data.

Proper citation: Global Alliance for Genomics and Health (RRID:SCR_003555) Copy   

•   Source: SciCrunch Registry

http://www.patientslikeme.com/

A for-profit health data-sharing platform that can transform the way patients manage their conditions, change the way industry conducts research and improve patient care. PatientsLikeMe aligns patient and industry interests through data-sharing partnerships. They work with trusted nonprofit, research and industry Partners who use this health data to improve products, services and care for patients. They take the information patients share about their experience with the disease and sell it to their partners (i.e., companies that are developing or selling products to patients). These products may include drugs, devices, equipment, insurance, and medical services. Except for the restricted personal information entered when registering for the site, participants should expect that every piece of information submitted (even if it is not currently displayed) may be shared with their partners and any member of PatientsLikeMe, including other patients. They do not rent, sell or share personally identifiable information for marketing purposes or without explicit consent. Because they believe in transparency, they tell members exactly what they do and do not do with their data. Patients have the opportunity to share both personal stories and health data about their conditions to help uncover great ideas and new knowledge. By sharing information on the site, they can put their disease experiences in context and find answers to the questions they have. Every partnership we develop must bring them closer to aligning patient and industry interests. Their end goal is improved patient care and quality of life.

Proper citation: PatientsLikeMe (RRID:SCR_003781) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/beyondthepdf/workshop-papers/beyond-the-dead-sea-pdfs

A standard next-generation paper (NGP) digital format for reading and digitally archiving scientific research papers to offer better imaging, data sharing and an improved reading experience. The NGP format is designed to retain traditional elements (i.e. Abstract, Introduction, etc.). Papers are viewed using any web browser running on any computing platform, including mobile devices. A button menu system provides navigation between pages. The format provides a more streamlined reading experience by providing as much information to the reader inline as possible, without requiring the user to skip between pages. To accomplish this, pop-up figure and reference details provide additional information without disrupting the flow of the paper. Clicking on standard figure data reveals full-resolution images, and live web links can be optionally followed from pop-up citations or inline links for additional information. Multimedia, such as hi-definition video or audio clips, is easily embedded within the new NGP format. The reader may also customize their reading experience by selecting alternative text and background color themes. The NGP format was created using non-proprietary open-source software including HTML and Javascript, and can be packaged to run offline independent of a live Internet connection. Data are fully captured and communicated utilizing the latest technologies available. The SCORE Imaging (Petzold et al.) paper was submitted to the publisher using this format to take advantage of its superior technical capabilities (http://zfishbook.org/NGP/).

Proper citation: NPG publishing format (RRID:SCR_000201) Copy   

•   Source: SciCrunch Registry

http://dataver.net/

DataVer is the premier data management verification service for scientific data. DataVer''s data management plan (DMP) Compliance Review and the companion Star Ratings will bring transparency to the investigator''s compliance with data management and sharing guidelines on a grant by grant basis. DataVer will accomplish this through 1) open publication of its review standards and procedures that it applies to all submitted grants and 2) openly report the results of its findings through its web portal so anyone can look up the compliance history of an investigator or lab. The Data Management Plan. The NIH and the NSF typically require a DMP detailing data types and quantity, its storage duration, and plans for making the data accessible to fellow scientists. The DMP is supposed to meet their published guidelines outlining the data management and sharing requirements to which the PI must agree as a condition of funding. The compliance record to date is less than ideal.. Institutional funders may not require a specific DMP as such but many have specific requirements for data management and post-grant data availability. While a specific DMP as such may not be produced for these grants, the data management and sharing is expected to comport with the funders'' guidelines. To date, there are no standardized or uniform means to track or assess the compliance of the investigator with the DMP or published guidelines. While individual institutions have tasked program managers with monitoring the compliance, the process is not uniform and the data stays within the specific institute, unavailable for other granting institutes or foundations. What DataVer does. DataVer offers two services with variations. First, it offers a DMP (or funder guideline) compliance review. For this DataVer compares the actual data management and data sharing of the grant funded data to the approved DMP and with the guidelines its funding agency(s). Second, DataVer rates the actual usability and accessibility of the data based on its own published standards on a three star rating scale. This indicates at a glance how well the data is organized and whether it''s available for reuse by an outside investigator. These procedures give the funders and the scientific community accurate, standardized and timely reports on an investigators'' data storage and data sharing in a publicly available database. We at DataVer believe this light, cast on actual data openness, will further encourage increased care in data management and archiving as well as increased data sharing. This openness and transparency will be a positive means to increase data management plan and guideline compliance, and will stimulate increased attention to the accessibility and usability of the data, so important to its reuse. We will offer a means by which universities, investigators, research facilities, and data repositories can obtain a compliance certification for consistently setting a high standard of data accessibility and usability across multiple grants. This certification is a means by which these stakeholders can demonstrate their achievement in support of data sharing. Grantors will be able to see an institution or facility''s pattern of compliance when deciding where to spend their limited resources.

Proper citation: DataVer (RRID:SCR_005954) Copy   

•   Source: SciCrunch Registry

http://www.genestack.com

A universal collaborative platform for bioinformatics application development that allows users to store and share large data sets securely within and across organizations, with free access to public data from major databases. The platform includes open-source and proprietary genomics applications, working together independent of file formats. For developers an SDK, APIs and a marketplace are provided.

Proper citation: Genestack (RRID:SCR_011885) Copy   

•   Source: SciCrunch Registry

https://www.iprox.cn/

Integrated proteome resources center in China to accelerate data sharing in proteomics. Composed of data submission system and proteome database. Submission system is established under the guidance of data-sharing policy made by ProteomeXchange consortium. Registered users can submit their proteomic datasets to iProX in public or private modes. Once associated manuscript has been published, dataset becomes automatically public.

Proper citation: Integrated Proteome Resources (RRID:SCR_026109) Copy   

•   Source: SciCrunch Registry

http://www.neuinfo.org/developers/nif_web_services.shtm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Representational State Transfer (REST) model based service for accessing a set of Neuroscience Information Framework (NIF) data through a fixed set of operations. They are defined by a WADL file which allows clients to automatically generate code for these services. The services (AnnotateService, FederationService, LdaService, LexicalService, LiteratureService, QueryService, SummaryService, VocabularyService) include the ability to: * Retrieve a federation summary, e.g., http://nif-services.neuinfo.org/servicesv1/v1/summary?q=* * Retrieve data records from a NIF federation source for a search, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/data/nif-0000-00007-1?q=purkinje * Retrieve registry data records from NIF, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/data/nlx_144509-1?q=miame * Retrieve a complete search summary, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/search?q=cortex * Retrieve NIF auto-complete suggestions, e.g., http://nif-services.neuinfo.org/servicesv1/v1/vocabulary?prefix=hippo * Use the NIF annotator for arbitrary text, e.g., http://nif-services.neuinfo.org/servicesv1/v1/annotate?content=The%20cerebellum%20is%20a%20wonderful%20thing These services are documented for developers in the WADL file (and client stubs should have the comments embedded in them). Visit, http://nif-services.neuinfo.org/servicesv1/ for more information

Proper citation: NIF Web Services (RRID:SCR_001631) Copy   

•   Source: SciCrunch Registry

http://www.adcs.org/

An initiative for Alzheimer's disease clinical studies that works to facilitate the discovery, development and testing of new drugs, and is a part of the Alzheimer's Disease Prevention Initiative. This resource has an emphasis on expanding the range of its patients, mainly by enhancing the recruitment of minority groups. There is a further emphasis placed on testing agents that cannot be patented, as well as developing novel compounds that had been developed by individuals, academic institutions and drug discovery units. This resource also helps in the development of Alzheimer's disease centers to carry out studies, as well as establish administrative, data, operations and medical cores in San Diego. This organization is specifically involved in studies demonstrating the lack of benefit associated, previously used treatments such as: the use of estrogen, non-steroidal anti-inflammatory drugs, B vitamins and a statin drug. The Alzheimer's Disease Cooperative Study also develops assessment instruments to be used in clinical trials. The most frequently used of these tools include: the Alzheimer's Disease Assessment Scale-Cognitive sub-scale (ADAS-cog), Activities of Daily Living (ADL), and the Clinical Global Impression of Change Scale (CGIC). There is also an associated tissue bank at UCSD that includes materials from the clinical trials including: human tissue, blood, plasma, DNA, urine and cerebrospinal fluid.

Proper citation: Alzheimer's Disease Cooperative Study (RRID:SCR_008254) Copy   

•   Source: SciCrunch Registry

https://github.com/SD-Jiang/MorphoHub

Software package to streamline workflow of imaging data management, visualization, reconstruction and collaboration, and data sharing.

Proper citation: MorphoHub (RRID:SCR_022817) Copy   

•   Source: SciCrunch Registry

http://www.esri.com/software/arcgis/arcgis-for-desktop

Geographical information system software produced by Esri.

Proper citation: ArcGIS for Desktop Basic (RRID:SCR_011081) Copy   

•   Source: SciCrunch Registry

http://www.ebisc.org/

Consortium to address the increasing demand by researchers for quality-controlled, disease-relevant research grade induced Pluripotent Stem Cell (iPSC) lines, data and cell services by demonstrating an operational banking and distribution service of iPSC lines after 3 years and establishing subsequently for Europe a centralized, not-for-profit bank providing all qualified users with access to scalable, cost-efficient and customized products. The main facility will be at the Babraham Research Campus (Cambridge, UK) and will undertake cell expansion, QC and characterization. The European Cell Culture Collection (ECACC) of Public Health England (Department of Health, UK) will coordinate cell line distribution. The Fraunhofer IBMT (Saarbr��cken, Germany) will provide comprehensive operational back up. In a phased business strategy EBiSC will hot-start distribution of lines contributed by iPSC Centres in 2014, lines collected based on specified user demand, will reach full scale operations in 2016, and with extended funding will become self-sustaining as a not for profit banking operation by 2019. EBiSC will spearhead Europe in the international standardization of iPSC banking by forging collaborative links with similar endeavors in the USA and Asia. It will also provide training to encourage adoption and use of the bank. The project has up to one year after completion to disseminate intellectual property or data created by the project.

Proper citation: EBiSC (RRID:SCR_003856) Copy   

•   Source: SciCrunch Registry

http://brainml.org/goto.do?page=.home

Set of standards and practices for using XML to facilitate information exchange between user application software and neuroscience data repositories. It allows for common shared library routines to handle most of the data processing, but also supports use of structures specialized to the needs of particular neuroscience communities. This site also serves as a repository for BrainML models. (A BrainML model is an XML Schema and optional vocabulary files describing a data model for electronic representation of neuroscience data, including data types, formats, and controlled vocabulary. ) It focuses on layered definitions built over a common core in order to support community-driven extension. One such extension is provided by the new NIH-supported neuroinformatics initiative of the Society for Neuroscience, which supports the development of expert-derived terminology sets for several areas of neuroscience. Under a cooperative agreement, these term lists will be made available Open Source on this site.
The repository function of this site includes the following features:
* BrainML models are published in searchable, browsable form.
* Registered users may submit new models or new versions of existing models to accommodate data of interest. * BrainML model schema and vocabulary files are made available at fixed URLs to allow software applications to reference them.
* Users can check models and/or instance documents for correct format before submitting them using an online validation service.
To complement the BrainML modeling language, a set of protocols have been developed for BrainML document exchange between repositories and clients, for indexing of repositories, and for data query.

Proper citation: BrainML (RRID:SCR_007087) Copy   

•   Source: SciCrunch Registry

http://mipav.cit.nih.gov

A Java-based application that enables quantitative analysis and visualization of medical images of numerous modalities such as DTI, PET, MRI, CT, or microscopy. Using MIPAV's standard user-interface and analysis tools, researchers at remote sites (via the internet) can easily share research data and analyses, thereby enhancing their ability to research, diagnose, monitor, and treat medical disorders. MIPAV can be run on any Java-enabled platform such as Windows, UNIX, or Macintosh OS X. Functionality includes segmentation, inter- and intra multi-modality registration, surface rendering, volume rendering and reading and writing a large number of biomedical file formats including: DICOM 3.0, Analyze, NIFTI, SPM, MINC, Phillips, GE, Zeiss, Biorad, jpeg, png, tiff, mrc, fits, interfile, and many more.

Proper citation: MIPAV: Medical Image Processing and Visualization (RRID:SCR_007371) Copy   

•   Source: SciCrunch Registry