Web of Life: ecological networks database. The Web of Life project is developed at Jordi Bascompte's lab (www.bascompte.net), a research group focused on the structure and dynamics of ecological networks. It is supported by an ERC's Advanced Grant of the European Union.
Decline can mean 80% of data are unavailable after 20 years.
In their parents' attic, in boxes in the garage, or stored on now-defunct floppy disks — these are just some of the inaccessible places in which scientists have admitted to keeping their old research data. Such practices mean that data are being lost to science at a rapid rate, a study has now found.
The authors of the study, which is published today in Current Biology1, looked for the data behind 516 ecology papers published between 1991 and 2011. The researchers selected studies that involved measuring characteristics associated with the size and form of plants and animals, something that has been done in the same way for decades. By contacting the authors of the papers, they found that, whereas data for almost all studies published just two years ago were still accessible, the chance of them being so fell by 17% per year. Availability dropped to as little as 20% for research from the early 1990s.
Valuable information produced by researchers in many EU-funded projects will be shared freely as a result of a Pilot on Open Research Data in Horizon 2020. Researchers in projects participating in the pilot are asked to make the underlying data needed to validate the results presented in scientific publications and other scientific information available for use by other researchers, innovative industries and citizens. This will lead to better and more efficient science and improved transparency for citizens and society. It will also contribute to economic growth through open innovation. For 2014-2015, topic areas participating in the Open Research Data Pilot will receive funding of around €3 billion.
canSAR is an integrated knowledge-base that brings together multidisciplinary data across biology, chemistry, pharmacology, structural biology, cellular networks and clinical annotations, and applies machine learning approaches to provide drug-discovery useful predictions.
Newly released data allows researchers to review cognitive function and personality traits across the whole life course, from ages 16 to 102.
Wave 3 of Understanding Society – the UK Household Longitudinal Study – includes the results of testing the cognitive ability of nearly 50,000 adults and 4,500 children aged 10 to 15. The study integrates 18 years of data from the British Household Panel Survey (BHPS) and Wave 3 provides up to 21 years of evidence about the changing nature of our society, individuals’ circumstances and behaviours.
Syria Tracker is a crowdsourcing effort that has been collecting citizen reports on human rights violations and casualties in Syria, since April 2011. Syria Tracker's ultimate goal is not only to provide the number of the fatalities, but also to preserve the name, location and details of each victim. Whenever possible, each name is linked to a photo or video of each casualty.Syria Tracker providesA continually updated list of eye witness reports from within Syria, often accompanied by media linksAggregate reports including analysis and visualizations of deaths and atrocities in SyriaA stream of content-filtered media from news, social media (Twitter and Facebook) and official sources
It’s always fascinating to take a look at the data visualizations and in-depth reports widely available on the web. As an aspiring (or active) data scientist, however, one of the best things you can do to learn about a particular field is to get your own hands dirty.
We have various types of data available to share. They are categorized into Ratings, Language, Graph, Advertising and Market Data, Computing Systems and an appendix of other relevant data and resources available via the Yahoo Developer Network.
Before the digital age, neuroscientists got their information in the library like the rest of us. But the field's explosion has created nearly 2 million papers—more data than any researcher can read and absorb in a lifetime.
Welcome to Academic Torrents!Currently making 207.87GB of research data available.
Sharing data is hard. Emails have size limits, and setting up servers is too much work. We've designed a distributed system for sharing enormous datasets - for researchers, by researchers. The result is a scalable, secure, and fault-tolerant repository for data, with blazing fast download speeds.
The British Library has uploaded one million public domain scans from 17th-19th century books to Flickr! They're embarking on an ambitious programme to crowdsource novel uses and navigation tools for the huge corpus.
When the Large Hadron Collider (LHC) is humming along, the data come in a deluge. The four experimental detectors at the facility, based at CERN, Europe’s particle-physics laboratory near Geneva, Switzerland, collect some 25 petabytes of information each year. Storing the data is not a problem: hard drives are cheap and getting cheaper. The challenge is preserving knowledge that is less commonly stored — the software, algorithms and reference plots specific to each experiment.
JASPAR (http://jaspar.genereg.net) is the largest open-access database of matrix-based nucleotide profiles describing the binding preference of transcription factors from multiple species. The fifth major release greatly expands the heart of JASPAR—the JASPAR CORE subcollection, which contains curated, non-redundant profiles—with 135 new curated profiles (74 in vertebrates, 8 in Drosophila melanogaster, 10 in Caenorhabditis elegans and 43 in Arabidopsis thaliana; a 30% increase in total) and 43 older updated profiles (36 in vertebrates, 3 in D. melanogaster and 4 in A. thaliana; a 9% update in total). The new and updated profiles are mainly derived from published chromatin immunoprecipitation-seq experimental datasets. In addition, the web interface has been enhanced with advanced capabilities in browsing, searching and subsetting. Finally, the new JASPAR release is accompanied by a new BioPython package, a new R tool package and a new R/Bioconductor data package to facilitate access for both manual and automated methods.
Iraq Body Count (IBC) records the violent civilian deaths that have resulted from the 2003 military intervention in Iraq. Its public database includes deaths caused by US-led coalition forces and paramilitary or criminal attacks by others.
IBC’s documentary evidence is drawn from crosschecked media reports of violent events leading to the death of civilians, or of bodies being found, and is supplemented by the careful review and integration of hospital, morgue, NGO and official figures
After four years of data digitization and processing, the Project Tycho™ Web site provites open access to newly digitized and integrated data from the entire 125 years history of United States weekly nationally notifiable disease surveillance data since 1888. These data can now be used by scientists, decision makers, investors, and the general public for any purpose. The Project Tycho™ aim is to advance the availability and use of public health data for science and decision making in public health, leading to better programs and more efficient control of diseases.
The Project Tycho™ data are organized as counts. A count is defined as the number of cases or deaths due to a disease in a specific location and time period. A count is equivalent to a data point. During the 125 year period of weekly disease reporting, the types of reports have been changed regularly, leading to different types of data counts across time. This makes the integration and standardization of these data a complex task. Currently, available data are categorized in three levels based on the type of counts included. Level 1 includes different types of counts that have been standardized into a common format for a specific analysis published recently in the NEJM. Level 2 data only includes counts that have been reported in a common format, e.g. diseases reported for a one week period and without disease subcategories. These data can be used immediately for analysis, includes a wide range of diseases and locations but this level does not include data that have not been standardized yet. Level 3 data include all the different types of counts ever reported. Although this is the most complete data, the large number of different counts requires extensive standardization and various judgment calls before they can be used for analysis.
For decades, drug development was mostly a game of trial and error, with brute-force candidate screens throwing up millions more duds than winners. Researchers are now using computers to get a head start. By analysing the chemical structure of a drug, they can see if it is likely to bind to, or ‘dock’ with, a biological target such as a protein. Such algorithms are particularly useful for finding potentially toxic side effects that may come from unintended dockings to structurally similar, but untargeted, proteins.
Here, you can find the dataset of a multiplex network composed of the airlines operating in Europe. You are free to use the dataset. We kindly ask you to cite the following paper as the source of the data: Emergence of Network Features from Multiplexity A. Cardillo, J. Gómez-Gardeñes, M. Zanin, M. Romance, D. Papo, F. del Pozo, S. Boccaletti, Scientific Reports 3, 1344 (2013).
The data contains up to thirty-seven different layers each one corresponding to a different airline. We have also prepared two subsets: one containing only the three biggest mayor airlines and another one similar but containing only low-fare (low-cost) airlines.
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