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Found 488 result(s)
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One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
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mdw Repository provides researchers with a robust infrastructure for research data management and ensures accessibility of research data during and after completion of research projects, thus, providing a quality boost to contemporary and future research.
The HSRC Research Data Service provides a digital repository facility for the HSRC's research data in support of evidence based human and social development in South Africa and the broader region. It includes both quantitative and qualitative data. Access to data is dependent on ethical requirements for protecting research participants, as well as on legal agreements with the owners, funders or in the case of data owned by the HSRC, the requirements of the depositors of the data.
By stimulating inspiring research and producing innovative tools, Huygens ING intends to open up old and inaccessible sources, and to understand them better. Huygens ING’s focus is on Digital Humanities, History, History of Science, and Textual Scholarship. Huygens ING pursues research in the fields of History, Literary Studies, the History of Science and Digital Humanities. Huygens ING aims to publish digital sources and data responsibly and with care. Innovative tools are made as widely available as possible. We strive to share the available knowledge at the institute with both academic peers and the wider public.
The Growing Up Today Study is a collaborative study between clinicians, researchers, and thousands of participants across the US and beyond. The aim of this study is to gain a deeper understanding of the factors that affect health throughout life. Together we are working to building one of the most powerful resources for fighting cancer, obesity, heart disease, depression, and so much more.
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The Life Science Database Archive maintains and stores the datasets generated by life scientists in Japan in a long-term and stable state as national public goods. The Archive makes it easier for many people to search datasets by metadata (description of datasets) in a unified format, and to access and download the datasets with clear terms of use. In addition, the Archive provides datasets in forms friendly to different types of users in public and private institutions, and thereby supports further contribution of each research to life science.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
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The GAVO data center at Zentrum für Astronomie Heidelberg provides VO publication services to all interested parties on behalf of the German Astrophysical Virtual Observatory. It's a A growing collection of data and services.
NCEP delivers national and global weather, water, climate and space weather guidance, forecasts, warnings and analyses to its Partners and External User Communities. The National Centers for Environmental Prediction (NCEP), an arm of the NOAA's National Weather Service (NWS), is comprised of nine distinct Centers, and the Office of the Director, which provide a wide variety of national and international weather guidance products to National Weather Service field offices, government agencies, emergency managers, private sector meteorologists, and meteorological organizations and societies throughout the world. NCEP is a critical national resource in national and global weather prediction. NCEP is the starting point for nearly all weather forecasts in the United States. The Centers are: Aviation Weather Center (AWC), Climate Prediction Center (CPC), Environmental Modeling Center (EMC), NCEP Central Operations (NCO), National Hurricane Center (NHC), Ocean Prediction Center (OPC), Storm Prediction Center (SPC), Space Weather Prediction Center (SWPC), Weather Prediction Center (WPC)
Antarctic marine and terrestrial biodiversity data is widely scattered, patchy and often not readily accessible. In many cases the data is in danger of being irretrievably lost. Biodiversity.aq establishes and supports a distributed system of interoperable databases, giving easy access through a single internet portal to a set of resources relevant to research, conservation and management pertaining to Antarctic biodiversity. biodiversity.aq provides access to both marine and terrestrial Antarctic biodiversity data.
This Web resource provides data and information relevant to SARS coronavirus. It includes links to the most recent sequence data and publications, to other SARS related resources, and a pre-computed alignment of genome sequences from various isolates. The genome of SARS-CoV consists of a single, positive-strand RNA that is approximately 29,700 nucleotides long. The overall genome organization of SARS-CoV is similar to that of other coronaviruses. The reference genome includes 13 genes, which encode at least 14 proteins. Two large overlapping reading frames (ORFs) encompass 71% of the genome. The remainder has 12 potential ORFs, including genes for structural proteins S (spike), E (small envelope), M (membrane), and N (nucleocapsid). Other potential ORFs code for unique putative SARS-CoV-specific polypeptides that lack obvious sequence similarity to known proteins.
IBICT is providing a research data repository that takes care of long-term preservation and archiving of good practices, so that researchers can share, maintain control and get recognition for your data. The repository supports research data sharing with Quote persistent data, allowing them to be played. The Dataverse is a large open data repository of all disciplines, created by the Institute for Quantitative Social Science at Harvard University. IBICT the Dataverse repository provides a means available for free to deposit and find specific data sets stored by employees of the institutions participating in the Cariniana network.
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The RDSC provides researchers access to selected microdata from the Bundesbank's data records for independent and non-commercial scientific research projects on basis of the legal requirements. The RDSC is the mediator between the Bundesbank’s wide range of different micro data in various departments and – on the other side – researchers or analysts. In connection with this, the RDSC is responsible for the methodological improvement, the access of and the comprehensive documentation of the high-quality microdata. It also offers additional consultancy and support services to existing and prospective data users and satisfies data protection requirements.
Open access repository for digital research created at the University of Minnesota. U of M researchers may deposit data to the Libraries’ Data Repository for U of M (DRUM), subject to our collection policies. All data is publicly accessible. Data sets submitted to the Data Repository are reviewed by data curation staff to ensure that data is in a format and structure that best facilitates long-term access, discovery, and reuse.
The Portal aims to serve as a unique access point to timely, comprehensive migration statistics and reliable information about migration data globally. The site is designed to help policy makers, national statistics officers, journalists and the general public interested in the field of migration to navigate the increasingly complex landscape of international migration data, currently scattered across different organisations and agencies. Especially in critical times, such as those faced today, it is essential to ensure that responses to migration are based on sound facts and accurate analysis. By making the evidence about migration issues accessible and easy to understand, the Portal aims to contribute to a more informed public debate. The Portal was launched in December 2017 and is managed and developed by IOM’s Global Migration Data Analysis Centre (GMDAC), with the guidance of its Advisory Board, and was supported in its conception by the Economist Intelligence Unit (EIU). The Portal is supported financially by the Governments of Germany, the United States of America and the UK Department for International Development (DFID).
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.
US National Science Foundation (NSF) facility to support drilling and coring in continental locations worldwide. Drill core metadata and data, borehole survey data, geophysical site survey data, drilling metadata, software code. CSDCO offers several repositories with samples, data, publications and reference collections about drilling and coring: LacCore Core Repository, Open Core Data, Index to Marine and Lacustrine Geological Samples. For " Botanical Reference Collections" contact the LacCore Curator for details.
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The University of Göttingen preserves one of the most important collections of scientific collections. At more than 30 distributed locations on the Göttingen Campus, the collections reflect its disciplinary diversity: the spectrum ranges from archeology to zoology, from astrophysical instruments to the living cell cultures of the algae collection. Historical legacy dating back to the Age of Enlightenment: The founding holdings of the Royal Academic Museum of Georgia Augusta are largely preserved. Research and teaching to date access to the collection objects and increase the stocks. Get to know our collections in this portal, which have been used to create knowledge for three centuries.
DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.
US Department of Energy’s Atmospheric Radiation Measurement (ARM) Data Center is a long-term archive and distribution facility for various ground-based, aerial and model data products in support of atmospheric and climate research. ARM facility currently operates over 400 instruments at various observatories (https://www.arm.gov/capabilities/observatories). ARM Data Center (ADC) Archive currently holds over 11,000 data products with a total holding of over 1.5 petabytes of data that dates back to 1993, these include data from instruments, value added products, model outputs, field campaign and PI contributed data. The data center archive also includes data collected by ARM from related program (e.g., external data such as NASA satellite).
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The "Flora of Bavaria" initiative with its data portal (14 million occurrence data) and Wiki representation is primarily a citizen science project. Efforts to describe and monitor the flora of Bavaria have been ongoing for 100 years. The goal of these efforts is to record all vascular plants, including newcomers, and to document threatened or former local occurrences. Being geographically largest state of Germany with a broad range of habitats, Bavaria has a special responsibility for documenting and maintaining its plant diversity . About 85% of all German vascular plant species occur in Bavaria, and in addition it has about 50 endemic taxa, only known from Bavaria (most of them occur in the Alps). The Wiki is collaboration of volunteers and local and regional Bavarian botanical societies. Everybody is welcome to contribute, especially with photos or reports of local changes in the flora. The Flora of Bavaria project is providing access to a research data repository for occurrence data powered by the Diversity Workbench database framework.
OSTI is the DOE office that collects, preserves, and disseminates DOE-sponsored R&D results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions. The information is typically in the form of technical documents, conference papers, articles, multimedia, and software, collectively referred to as scientific and technical information (STI).
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"IndExs" is a database comprising information on exsiccatae (=exsiccatal series) with titles, abbreviations, bibliography and provides a unique and persistent Exsiccata ID for each series. Exsiccatae are defined as "published, uniform, numbered sets of preserved specimens distributed with printed labels" (Pfister 1985). Please note that there are two similar latin terms: "exsiccata, ae" is feminine and used for a set of dried specimens as defined above, whereas the term "exsiccatum, i" is neutral and used for dried specimens in general. If available, images of one or more examplary labels are added to give layout information.