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Found 82 result(s)
The Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system was developed to share data across the entire TBI research field and to facilitate collaboration between laboratories, as well as interconnectivity with other informatics platforms. Sharing data, methodologies, and associated tools, rather than summaries or interpretations of this information, can accelerate research progress by allowing re-analysis of data, as well as re-aggregation, integration, and rigorous comparison with other data, tools, and methods. This community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
FungiDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the kingdom Fungi. FungiDB was first released in early 2011 as a collaborative project between EuPathDB and the group of Jason Stajich (University of California, Riverside). At the end of 2015, FungiDB was integrated into the EuPathDB bioinformatic resource center. FungiDB integrates whole genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining.
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SODHA is the federal Belgian data archive for social sciences and the digital humanities. SODHA is a new service of the State Archives of Belgium and acts as the Belgian service provider for the Consortium of European Social Science Data Archives (CESSDA).
EuPathDB (formerly ApiDB) is an integrated database covering the eukaryotic pathogens in the genera Acanthamoeba, Annacaliia, Babesia, Crithidia, Cryptosporidium, Edhazardia, Eimeria, Encephalitozoon, Endotrypanum, Entamoeba, Enterocytozoon, Giardia, Gregarina, Hamiltosporidium, Leishmania, Nematocida, Neospora, Nosema, Plasmodium, Theileria, Toxoplasma, Trichomonas, Trypanosoma and Vavraia, Vittaforma). While each of these groups is supported by a taxon-specific database built upon the same infrastructure, the EuPathDB portal offers an entry point to all of these resources, and the opportunity to leverage orthology for searches across genera.
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DATICE was established in late 2018 and is funded by the University of Iceland's (UI) School of Social Sciences, with a contribution from the university's Centennial Fund. DATICE is the appointed service provider for the Consortium of European Social Science Data Archives (CESSDA ERIC) in Iceland and is located within the UI Social Science Research Institute (SSRI). The main goal of the data service is to ensure open and free access to high quality research data for the research community as well as the general public.
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IDSC is IZA's organizational unit whose purpose is to serve the scientific and infrastructural computing needs of IZA and its affiliated communities. IDSC is dedicated to supporting all users of data from the novice researcher to the experienced data analyst. IDSC aims at becoming the place for economically minded technologists and technologically savvy economists looking for data support, data access support and data services about labor economics. IDSC is actively involved in organizing events (see our next Red Cube Seminar Talk) for data professionals, data analysts, and scientific data users and young researchers to discuss and share findings and to establish contacts for future cooperation. All data collected are accessible to the scientific community as scientific use files for scholarly analyses free of charge. The Data Repository is available at https://datasets.iza.org/
ISRIC - World Soil Information is an independent foundation. As regular member of the ICS World Data System it is also known as World Data Centre for Soils (WDC-Soils). ISRIC was founded in 1966 through the International Soil Science Society (ISSS) and United Nations Educational, Scientific and Cultural Organization (UNESCO), with a mission to "help to increase the availability and use of soil data, information and knowledge to enable better decision making for sustainable land management around the world". Our work is organised according to four work streams: 1) Global soil information & standards, 2) Community of practice for soil information providers, 3) Products and services to support SLM (sustainable land management) decision making, and 4) Awareness, education and dialogues. data.isric.org is our central location for searching and downloading soil data bases/maps from around the world. We support Open Data whenever possible, respecting inherited rights (licenses).
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.
Giardia lamblia is a significant, environmentally transmitted, human pathogen and an amitochondriate protist. It is a major contributor to the enormous worldwide burden of human diarrheal diseases, yet the basic biology of this parasite is not well understood. No virulence factor has been identified. The Giardia lamblia genome contains only 12 million base pairs distributed onto five chromosomes. Its analysis promises to provide insights about the origins of nuclear genome organization, the metabolic pathways used by parasitic protists, and the cellular biology of host interaction and avoidance of host immune systems. Since the divergence of Giardia lamblia lies close to the transition between eukaryotes and prokaryotes in universal ribosomal RNA phylogenies, it is a valuable, if not unique, model for gaining basic insights into genetic innovations that led to formation of eukaryotic cells. In evolutionary terms, the divergence of this organism is at least twice as ancient as the common ancestor for yeast and man. A detailed study of its genome will provide insights into an early evolutionary stage of eukaryotic chromosome organization as well as other aspects of the prokaryotic / eukaryotic divergence.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
ReefTEMPS is a temperature, pressure, salinity and other observables sensor network in coastal area of South, West and South West of Pacific ocean, driven by UMR ENTROPIE. It is an observatory service from the French national research infrastructure ILICO for “coastal environments”. Some of the network’s sensors have been deployed since 1958. Nearly hundred sensors are actually deployed in 14 countries covering an area of more than 8000 km from East to West. The data are acquired at different rates (from 1sec to 30 mn) depending on sensors and sites. They are processed and described using Climate and Forecast Metadata Convention at the end of oceanographic campaigns organized for sensors replacement every 6 months to 2 years.
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OGS is recognised as the Italian National Oceanographic Data Centre (OGS-NODC) within the International Oceanographic Data Exchange System of the UNESCO Intergovernmental Oceanographic Commission (IOC) since 27/6/2002. OGS is also listed in EurOcean (Marine Research Infrastructures Database) and in EDMO (European Directory of Marine Organisations). OGS as part of the IOC's network of National Oceanographic Data Centres has designated responsibility for the coordination of data and information management at national level. The oceanographic database covers the fields of marine physics, chemical, biological, underway geophysics and general information on Italian oceanographic cruises and data sets. The main objectives are (revision IODE-XXII, March 2013): -Facilitate and promote the discovery, exchange of, and access to, marine data and information including metadata, products and information in real-time, near real time and delayed mode, through the use of international standards, and in compliance with the IOC Oceanographic Data Exchange Policy for the ocean research and observation community and other stakeholders; - Encourage the long term archival, preservation, documentation, management and services of all marine data, data products, and information; - Develop or use existing best practices for the discovery, management, exchange of, and access to marine data and information, including international standards, quality control and appropriate information technology; - Assist Member States to acquire the necessary capacity to manage marine research and observation data and information and become partners in the IODE network; - Support international scientific and operational marine programmes, including the Framework for Ocean Observing for the benefit of a wide range.
The NCBI Taxonomy database is a curated set of names and classifications for all of the organisms that are represented in GenBank. The EMBL and DDBJ databases, as well as GenBank, now use the NCBI Taxonomy as the standard classification for nucleotide sequences. Taxonomy Contains the names and phylogenetic lineages of more than 160,000 organisms that have molecular data in the NCBI databases. New taxa are added to the Taxonomy database as data are deposited for them. When new sequences are submitted to GenBank, the submission is checked for new organism names, which are then classified and added to the Taxonomy database.
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Geoscientific Data & Discovery Publishing Center (GDD) is based on the geological scientific data generated globally, establishing policies and systems for the scientific data publishing, absorbing the concepts and methods of international open data, and joint Digital Object Unique Identifier-DOI registration agencies to provide standard data reference formats and permanent access address for data references, doing publishing through the Internet platform, which combines innovation and advance. GDD mainly includes data descriptor and entity data publishing. The data papers describe entity data and corresponding metadata information. The entity data includes common shared data such as geographic information, geologic maps, and databases, and also includes multiple data types, such as documents, archive records, data forms and other multimedia formed during geological work, various data-centric applications, database interface services, and typical data services.
UNC Dataverse is an open-source repository software application for archiving, sharing, and accessing research data of all kinds. Each dataverse within the larger repository contains a multitude of datasets, and each dataset contains descriptive metadata and data files. UNC Dataverse is hosted by Odum Institute for Research in Social Science.
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The CORA. Repositori de dades de Recerca is a repository of open, curated and FAIR data that covers all academic disciplines. CORA. Repositori de dades de Recerca is a shared service provided by participating Catalan institutions (Universities and CERCA Research Centers). The repository is managed by the CSUC and technical infrastructure is based on the Dataverse application, developed by international developers and users led by Harvard University (https://dataverse.org).
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The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. The platform aggregates and harmonizes information already entered in various public repositories such as DRKS, clinicaltrials.gov, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated. The service started during the COVID-19 pandemic.
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DataverseNO 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.
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IDOC-DATA is a department of IDOC IDOC (Integrated Data & Operation Center) has existed since 2003 as a satellite operations center and data center for the Institute of Space Astrophysics (IAS) in Orsay, France. Since then, it has operated within the OSUPS (Observatoire des Sciences de l'Univers de l'Université Paris-Saclay - first french university in shanghai ranking), which includes three institutes: IAS, AIM (Astrophysique, Interprétation, Modélisation - IRFU, CEA) and GEOPS (Geosciences Paris-Saclay) . IDOC participates in the space missions of OSUPS and its partners, from mission design to long-term scientific data archiving. For each phase of the missions, IDOC offers three kinds of services in the scientific themes of OSUPS and therefore IDOC's activities are divided into three departments: IDOC-INSTR: instrument design and testing, IDOC-OPE: instrument operations, IDOC-DATA: data management and data value chain: to produce the different levels of data constructed from observations of these instruments and make them available to users for ergonomic and efficient scientific interpretation (IDOC-DATA). It includes the responsibility: - To build access to these datasets. - To offer the corresponding services such as catalogue management, visualization tools, software pipeline automation, etc. - To preserve the availability and reliability of this hardware and software infrastructure, its confidentiality where applicable and its security.
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The Repositori Ilmiah Nasional (RIN) is a means for storing, preserving, citing, analyzing and sharing research data. RIN acts as an online media in managing, storing and sharing research data. Researchers, data writers, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility. Researchers, agencies, and funders have full control over research data.