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Found 52 result(s)
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.
Welcome to the largest bibliographic database dedicated to Economics and available freely on the Internet. This site is part of a large volunteer effort to enhance the free dissemination of research in Economics, RePEc, which includes bibliographic metadata from over 1,800 participating archives, including all the major publishers and research outlets. IDEAS is just one of several services that use RePEc data. Authors are invited to register with RePEc to create an online profile. Then, anyone finding some of your research here can find your latest contact details and a listing of your other research. You will also receive a monthly mailing about the popularity of your works, your ranking and newly found citations. Besides that IDEAS provides software and public accessible data from Federal Reserve Bank.
DSpace@MIT is a service of the MIT Libraries to provide MIT faculty, researchers and their supporting communities stable, long-term storage for their digital research and teaching output and to maximize exposure of their content to a world audience. DSpace@MIT content includes conference papers, images, peer-reviewed scholarly articles, preprints, technical reports, theses, working papers, research datasets and more. This collection of more than 60,000 high-quality works is recognized as among the world's premier scholarly repositories and receives, on average, more than 1 million downloads per month.
<<<!!!<<< The RDP website is no longer available. A stand-alone version of the RDP Classifier is available on Sorceforge https://sourceforge.net/projects/rdp-classifier/. Instructions for installing a command-line version of RDP Tools can be found at Dr. J.Quensen's Website https://john-quensen.com/tutorials/tutorial-1/ and https://jfq3.gitbook.io/rdptools-docker/rdptools-docker/readme. >>>!!!>>>
The RIT DML captures, distributes and preserves RIT's digital products. Here you can find articles, working papers, preprints, technical reports, conference papers and data sets in various digital formats.
Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.
The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.
Scholars' Mine is an online collection of scholarly and creative works produced by the faculty, staff, and students of the Missouri University of Science and Technology.
The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).
The information in the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer relates cytogenetic changes and their genomic consequences, in particular gene fusions, to tumor characteristics, based either on individual cases or associations. All the data have been manually culled from the literature by Felix Mitelman in collaboration with Bertil Johansson and Fredrik Mertens.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
Merritt is a curation repository for the preservation of and access to the digital research data of the ten campus University of California system and external project collaborators. Merritt is supported by the University of California Curation Center (UC3) at the California Digital Library (CDL). While Merritt itself is content agnostic, accepting digital content regardless of domain, format, or structure, it is being used for management of research data, and it forms the basis for a number of domain-specific repositories, such as the ONEShare repository for earth and environmental science and the DataShare repository for life sciences. Merritt provides persistent identifiers, storage replication, fixity audit, complete version history, REST API, a comprehensive metadata catalog for discovery, ATOM-based syndication, and curatorially-defined collections, access control rules, and data use agreements (DUAs). Merritt content upload and download may each be curatorially-designated as public or restricted. Merritt DOIs are provided by UC3's EZID service, which is integrated with DataCite. All DOIs and associated metadata are automatically registered with DataCite and are harvested by Ex Libris PRIMO and Thomson Reuters Data Citation Index (DCI) for high-level discovery. Merritt is also a member node in the DataONE network; curatorially-designated data submitted to Merritt are automatically registered with DataONE for additional replication and federated discovery through the ONEMercury search/browse interface.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.
IEEE DataPort™ is a universally accessible online data repository created, owned, and supported by IEEE, the world’s largest technical professional organization. It enables all researchers and data owners to upload their dataset without cost. IEEE DataPort makes data available in three ways: standard datasets, open access datasets, and data competition datasets. By default, all "standard" datasets that are uploaded are accessible to paid IEEE DataPort subscribers. Data owners have an option to pay a fee to make their dataset “open access”, so it is available to all IEEE DataPort users (no subscription required). The third option is to host a "data competition" and make a dataset accessible for free for a specific duration with instructions for the data competition and how to participate. IEEE DataPort provides workflows for uploading data, searching, and accessing data, and initiating or participating in data competitions. All datasets are stored on Amazon AWS S3, and each dataset uploaded by an individual can be up to 2TB in size. Institutional subscriptions are available to the platform to make it easy for all members of a given institution to utilize the platform and upload datasets.
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.”
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
GeoCommons is the public community of GeoIQ users who are building an open repository of data and maps for the world. The GeoIQ platform includes a large number of features that empower you to easily access, visualize and analyze your data. The GeoIQ platform powers the growing GeoCommons community of over 25,000 members actively creating and sharing hundreds of thousands of datasets and maps across the world. With GeoCommons, anyone can contribute and share open data, easily build shareable maps and collaborate with others.
BrainMaps.org, launched in May 2005, is an interactive multiresolution next-generation brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and that is integrated with a high-speed database for querying and retrieving data about brain structure and function over the internet. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, and Tyto alba.
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).