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Found 76 result(s)
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
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The Community Data Program (CDP) is a membership-based community development initiative open to any Canadian public, non-profit or community sector organization with a local service delivery or public policy mandate. The program facilitates access to the evidence needed to tell our stories and inform effective and responsive policy and program design and implementation. The CDP makes data accessible and useful for all members with training and capacity building resources. Through its vibrant network, the CDP facilitates and supports dialogue and the sharing of best practices in the use of community data. The CDP has emerged as a unique Canada-wide platform for generating information, convening and collaborating.
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Search from over 100 variety of datasets such as census results, city public WiFi locations, licensed eateries and more
The Health and Medical Care Archive (HMCA) is the data archive of the Robert Wood Johnson Foundation (RWJF), the largest philanthropy devoted exclusively to health and health care in the United States. Operated by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, HMCA preserves and disseminates data collected by selected research projects funded by the Foundation and facilitates secondary analyses of the data. Our goal is to increase understanding of health and health care in the United States through secondary analysis of RWJF-supported data collections
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On this server you'll find 127 items of primary data of the University of Munich. Scientists / students of all faculties of LMU and of institutions that cooperate with the LMU are invited to deposit their research data on this platform.
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The Atlantic Canada Conservation Data Centre (ACCDC) maintains comprehensive lists of plant and animal species. The Atlantic CDC has geo-located records of species occurrences and records of extremely rare to uncommon species in the Atlantic region, including New Brunswick, Nova Scotia, Prince Edward Island, Newfoundland, and Labrador. The Atlantic CDC also maintains biological and other types of data in a variety of linked databases.
State of the Salmon provides data on abundance, diversity, and ecosystem health of wild salmon populations specific to the Pacific Ocean, North Western North America, and Asia. Data downloads are available using two geographic frameworks: Salmon Ecoregions or Hydro 1K.
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The Research Data Centre of the Robert Koch Institute (FDZ RKI) publishes the data of population-representative health surveys in the form of public use files (PUFs).The main purpose of health surveys is to generate a maximum amount of information on the state of health and health-related behaviour of Germany's resident population while ensuring an optimum use of funds. The methodology - i.e. the sample design, the principles on operationalization and measurement, and data-collection techniques - is largely modelled on the tried-and-tested methods of empirical social research. Health interview surveys (HIS) use established survey techniques such as filling out questionnaires, computer-assisted telephone interviews (CATI), computer-assisted personal interviews (CAPI), and online polling via the internet or email. The main difference compared to purely sociological surveys lies in the additional biomedical examinations, tests and medical-biochemical measurements, which generate significant added value in addition to the results of the surveys; this part is referred to internationally as the health examination survey (HES).
INDEPTH is a global network of research centres that conduct longitudinal health and demographic evaluation of populations in low- and middle-income countries (LMICs). INDEPTH aims to strengthen global capacity for Health and Demographic Surveillance Systems (HDSSs), and to mount multi-site research to guide health priorities and policies in LMICs, based on up-to-date scientific evidence. The data collected by the INDEPTH Network members constitute a valuable resource of population and health data for LMIC countries. This repository aims to make well documented anonymised longitudinal microdata from these Centres available to data users.
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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.
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The Portal is intended to be used as catalog of datasets published by ministries/ department/ organizations of Government of India for public use, in order to enhance transparency in the functioning of the Government as well as to make innovative visualization of dataset. This National Data Portal is being updated frequently to make it as accessible as possible and completely accessible to all irrespective of physical challenges or technology.
!!! <<< the repository is offline >>> !!! The CBIF provides primary data on biological species of interest to Canadians. CBIF supports a wide range of social and economic decisions including efforts to conserve our biodiversity in healthy ecosystems, use our biological resources in sustainable ways, and monitor and control pests and diseases. Tools provided by the CBIF include the Integrated Taxonomic Information System (ITIS), Species Access Network, Online Mapping, and the SpeciesBank, including Butterflies of Canada. The CBIF is a member of the Global Biodiversity Information Facility (GBIF).
The EUDAT project aims to contribute to the production of a Collaborative Data Infrastructure (CDI). The project´s target is to provide a pan-European solution to the challenge of data proliferation in Europe's scientific and research communities. The EUDAT vision is to support a Collaborative Data Infrastructure which will allow researchers to share data within and between communities and enable them to carry out their research effectively. EUDAT aims to provide a solution that will be affordable, trustworthy, robust, persistent and easy to use. EUDAT comprises 26 European partners, including data centres, technology providers, research communities and funding agencies from 13 countries. B2FIND is the EUDAT metadata service allowing users to discover what kind of data is stored through the B2SAFE and B2SHARE services which collect a large number of datasets from various disciplines. EUDAT will also harvest metadata from communities that have stable metadata providers to create a comprehensive joint catalogue to help researchers find interesting data objects and collections.
The Museum is committed to open access and open science, and has launched the Data Portal to make its research and collections datasets available online. It allows anyone to explore, download and reuse the data for their own research. Our natural history collection is one of the most important in the world, documenting 4.5 billion years of life, the Earth and the solar system. Almost all animal, plant, mineral and fossil groups are represented. These datasets will increase exponentially. Under the Museum's ambitious digital collections programme we aim to have 20 million specimens digitised in the next five years.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
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The portal "Wissenschaftliche Sammlungen" is a project of the Coordination Office for Academic University Collections in Germany in cooperation with the Academic University and University Collections. Together we create a platform that makes information on scientific collections, activities and actors as well as metadata and digitised objects visible, searchable and scientifically usable via a web portal. The data will be freely and openly accessible via technical interfaces in standard formats and fed into national reference systems such as the German Digital Library.
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
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CANJEM (CANadian Job-Exposure Matrix) is a large source of retrospective information on job-based exposure for a given occupation and time period. Covering most occupations and many agents, it provides information on the probability, frequency and intensity of exposure from a list of 258 occupational risk factors. CANJEM was built from past individual expert evaluations of occupational exposures in a series of four case control studies of various cancers conducted since the mid-1980s up to 2010 in the greater Montreal area. During these studies over 30 000 jobs from 1930 to 2005 held by close to 10 000 subjects were evaluated by experts who assigned exposures based on descriptions of tasks, processes, work environment, and exposure control measures."
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Town is embracing the Open Data information movement and releasing data for free to the public.
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.