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Found 28 result(s)
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The Open Energy Family aims to ensure quality, transparency and reproducibility in energy system research. It is a collection of various tools and information and that help working with energy related data. It is a collaborative community effort, everything is openly developed and therefore constantly evolving. The main module is the Open Energy Platform (OEP), a web interface to access most of the modules, especially the community database. It provides a way to publish data with proper documentation (metadata), and link it to source code and underlying assumptions. Open Energy Database is an open community database for energy, climate and modelling data.
An open digital archive of scholarly, intellectual and research outputs of the University of South Africa. The UnisaIR contains and preserves theses and dissertations, research articles, conference papers, rare and special materials and many other digital assets. With special collections from the Documentation Center for African Studies including manuscripts, photos, political posters and other archival materials about the history of South Africa.
The World Data Center for Remote Sensing of the Atmosphere, WDC-RSAT, offers scientists and the general public free access (in the sense of a “one-stop shop”) to a continuously growing collection of atmosphere-related satellite-based data sets (ranging from raw to value added data), information products and services. Focus is on atmospheric trace gases, aerosols, dynamics, radiation, and cloud physical parameters. Complementary information and data on surface parameters (e.g. vegetation index, surface temperatures) is also provided. This is achieved either by giving access to data stored at the data center or by acting as a portal containing links to other providers.
It is a platform for supporting Open Data initiative of Government of Odisha, intends to publish datasets collected by them for public use. It also supports widely used file formats that are suitable for machine processing, thus gives avenues for many more innovative uses of Government Data in different perspective. This portal has been created under Software as A Service (SaaS) model of Open Government Data (OGD) Platform India of NIC. The data available in the portal are owned by various Departments/Organization of Government of Odisha. It follows principles on which data sharing and accessibility need to be based include: Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
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The FDZ-DZA (Forschungsdatenzentrum DZA) is a facility of the German Centre of Gerontology (Deutsches Zentrum für Altersfragen, DZA) and has received accreditation as research data center DZA by the German Data Forum (RatSWD). Its main task is to make data of the German Ageing Survey DEAS and the German Survey on Volunteering (FWS) accessible to researchers by providing user-friendly Scientific Use Files (SUF), documentation of the contents and instruments as well support for scholars using the data.
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An open data sharing platform resulting from collaboration between cities and the Government of Quebec.
MEASURE DHS is advancing global understanding of health and population trends in developing countries through nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, HIV, and nutrition. The database collects, analyzes, and disseminates data from more than 300 surveys in over 90 countries. MEASURE DHS distributes, at no cost, survey data files for legitimate academic research.
InterPro collects information about protein sequence analysis and classification, providing access to a database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. Sequences in InterPro are classified at superfamily, family, and subfamily. InterPro predicts the occurrence of functional domains, repeats, and important sites, and adds in-depth annotation such as GO terms to the protein signatures.
The NF Data Portal is designed to help openly explore and share NF datasets, analysis tools, resources, and publications related to neurofibromatosis. Anyone can join the NF Open Science Initiative (NF-OSI) to participate! We welcome contributions from anyone in the neurofibromatosis and schwannomatosis research community, such as original datasets generated by the community or analyses of data from the NF Data Portal.
The Pfam database is a large collection of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). !!! Powering down the Pfam website On October 5th, redirecting the traffic from Pfam (pfam.xfam.org) to InterPro (www.ebi.ac.uk/interpro) will start. The Pfam website will be available at legacy.pfam.xfam.org until January 2023, when it will be decommissioned. You can read more about the sunset period in the blog post (https://xfam.wordpress.com/2022/08/04/pfam-website-decommission/). !!!
The National Sleep Research Resource (NSRR) is an NHLBI-supported repository for sharing large amounts of sleep data (polysomnography, actigraphy and questionnaire-based) from multiple cohorts, clinical trials, and other data sources. Launched in April 2014, the mission of the NSRR is to advance sleep and circadian science by supporting secondary data analysis, algorithmic development, and signal processing through the sharing of high-quality data sets.
diversitydata.org is an online tool for exploring quality of life data across metropolitan areas for people of different racial/ethnic groups in the United States. It provides values and rankings for the largest U.S. metropolitan areas on different indicators in 8 areas of life (domains), including demographics, education, economic opportunity, housing, neighborhoods, and health. It also provides a simple mapping utility, showing the range of indicator values for metros across the U.S. Data from 1999 indicators is archives in the companion Diversity Data Archive (https://diversitydata-archive.org/). For a wider selection of data on child wellbeing, visit our partner site, diversitydatakids.org (https://www.diversitydatakids.org/). diversitydata.org has been named a Health Data All Star by the Health Data Consortium. The list was compiled in consultation with leading health researchers, government officials, entrepreneurs, advocates and others to identify the health data resources that matter most.
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SAGE is a data and research platform that enables the secondary use of data related to child and youth development, health and well-being. It currently contains research data, and at a later stage we aim to also house administrative and community service delivery data. Technical infrastructure and governance processes are in place to ensure ethical use and the privacy of participants. This dataverse provides metadata for the various data holdings available in SAGE (Secondary Analysis to Generate Evidence), a research data repository based in Edmonton Alberta and an intiative of PolicyWise for Children & Families. In general, SAGE contains data holdings too sensitive for open access. Each study lists a security level which indicates the procedure required to access the data.
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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
Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.
MicrosporidiaDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the phylum Microsporidia. In its first iteration (released in early 2010), MicrosporidiaDB contains the genomes of two Encephalitozoon species (see below). MicrosporidiaDB integrates whole genome sequence and annotation and will rapidly expand to include experimental data and environmental isolate sequences provided by community researchers. The database includes supplemental bioinformatics analyses and a web interface for data-mining.
<<<!!!<<< Efforts to obtain renewed funding after 2008 were unfortunately not successful. PANDIT has therefore been frozen since November 2008, and its data are not updated since September 2005 when version 17.0 was released (corresponding to Pfam 17.0). The existing data and website remain available from these pages, and should remain stable and, we hope, useful. >>>!!!>>> PANDIT is a collection of multiple sequence alignments and phylogenetic trees. It contains corresponding amino acid and nucleotide sequence alignments, with trees inferred from each alignment. PANDIT is based on the Pfam database (Protein families database of alignments and HMMs), and includes the seed amino acid alignments of most families in the Pfam-A database. DNA sequences for as many members of each family as possible are extracted from the EMBL Nucleotide Sequence Database and aligned according to the amino acid alignment. PANDIT also contains a further copy of the amino acid alignments, restricted to the sequences for which DNA sequences were found.
The Mexican Health and Aging Study (MHAS) started as a prospective panel study of health and aging in Mexico. MHAS is nationally representative of the 13 million Mexicans born prior to 1951. The survey has national and urban/rural representation. The baseline survey, in 2001, included a nationally representative sample of Mexicans aged 50 and over and their spouse/partners regardless of their age. A direct interview was sought with each individual and proxy interviews were obtained when poor health or temporary absence precluded a direct interview. The sample was distributed in all 32 states of the country in urban and rural areas. Households in the six states which account for 40% of all migrants to the U.S. were over-sampled. A sub-sample was selected to obtain anthropometric measures.
The European Genome-phenome Archive (EGA) is designed to be a repository for all types of sequence and genotype experiments, including case-control, population, and family studies. We will include SNP and CNV genotypes from array based methods and genotyping done with re-sequencing methods. The EGA will serve as a permanent archive that will archive several levels of data including the raw data (which could, for example, be re-analysed in the future by other algorithms) as well as the genotype calls provided by the submitters. We are developing data mining and access tools for the database. For controlled access data, the EGA will provide the necessary security required to control access, and maintain patient confidentiality, while providing access to those researchers and clinicians authorised to view the data. In all cases, data access decisions will be made by the appropriate data access-granting organisation (DAO) and not by the EGA. The DAO will normally be the same organisation that approved and monitored the initial study protocol or a designate of this approving organisation. The European Genome-phenome Archive (EGA) allows you to explore datasets from genomic studies, provided by a range of data providers. Access to datasets must be approved by the specified Data Access Committee (DAC).
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More than a quarter of a million people — one in 10 NSW men and women aged over 45 — have been recruited to our 45 and Up Study, the largest ongoing study of healthy ageing in the Southern Hemisphere. The baseline information collected from all of our participants is available in the Study’s Data Book. This information, which researchers use as the basis for their analyses, contains information on key variables such as height, weight, smoking status, family history of disease and levels of physical activity. By following such a large group of people over the long term, we are developing a world-class research resource that can be used to boost our understanding of how Australians are ageing. This will answer important health and quality-of-life questions and help manage and prevent illness through improved knowledge of conditions such as cancer, heart disease, depression, obesity and diabetes.
The Cornell Center for Social Sciences (CCSS) houses an extensive collection of research data files in the social sciences with particular emphasis on data that matches the interests of Cornell University researchers. CCSS intentionally uses a broad definition of social sciences in recognition of the interdisciplinary nature of Cornell research. CCSS collects and maintains digital research data files in the social sciences, with a current emphasis on Cornell-based social science research, Results Reproduction packages, and potentially at-risk datasets. Our archive historically has focused on a broad range of social science data, including data on demography, economics and labor, political and social behavior, family life, and health. You can search our holdings or browse studies by subject area.
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The project analyzes educational processes in Germany from early childhood to late adulthood. The National Educational Panel Study (NEPS) has been set up to find out more about the acquisition of education in Germany, to plot the consequences of education for individual biographies, and to describe central educational processes and trajectories across the entire life span. Such an interdisciplinary consortium of research institutes, researcher groups, and research. personalities has been assembled in Bamberg. In addition, the competencies and experiences with longitudinal research available at numerous other locations have been networked to form a cluster of excellence.
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Open Government Data Portal of Tamil Nadu is a platform (designed by the National Informatics Centre), for Open Data initiative of the Government of Tamil Nadu. The portal is intended to publish datasets collected by the Tamil Nadu Government for public uses in different perspective. It has been created under Software as A Service (SaaS) model of Open Government Data (OGD) and publishes dataset in open formats like CSV, XLS, ODS/OTS, XML, RDF, KML, GML, etc. This data portal has following modules, namely (a) Data Management System (DMS) for contributing data catalogs by various state government agencies for making those available on the front end website after a due approval process through a defined workflow; (b) Content Management System (CMS) for managing and updating various functionalities and content types; (c) Visitor Relationship Management (VRM) for collating and disseminating viewer feedback on various data catalogs; and (d) Communities module for community users to interact and share their views and common interests with others. It includes different types of datasets generated both in geospatial and non-spatial data classified as shareable data and non-shareable data. Geospatial data consists primarily of satellite data, maps, etc.; and non-spatial data derived from national accounts statistics, price index, census and surveys produced by a statistical mechanism. It follows the principle of data sharing and accessibility via Openness, Flexibility, Transparency, Quality, Security and Machine-readable.