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"CTSAsearch is a federated search engine using Linked Open Data published by members of the CTSA Consortium and other interested parties. To try it out, use the form below or click on the "CTSA Search" entry in the menu on the left to see a ranked list of matching investigators. Check the "Display Map" box or click on the "CTSA Map" entry in the menu to visualize coauthorship amongst the matching investigators."

"ELIXIR unites Europe's leading life science organisations in managing and safeguarding the increasing volume of data being generated by publicly funded research. It coordinates, integrates and sustains bioinformatics resources across its member states and enables users in academia and industry to access services that are vital for their research. See About us."

"Share, discuss and improve your data, tools, workflow and overall knowledge of our Solar System"

"SDSS-III's newest release is Data Release 10 (DR10). DR10 contains the first spectra of the APO Galactic Evolution Experiment (APOGEE), as well as additional sky coverage and better galaxy parameter estimates from BOSS."

"World Wind is a free, open source API for a virtual globe. World Wind allows developers to quickly and easily create interactive visualizations of 3D globe, map and geographical information. Organizations across the world use World Wind to monitor weather patterns, visualize cities and terrain, track the movement of planes, vehicles and ships, analyze geospatial data, and educate people about the Earth."

"The rapid improvement in DNA sequencing has sparked a big data revolution in genomic sciences, which has in turn led to a proliferation of bioinformatics tools. To date, these tools have encountered little adversarial pressure. This paper evaluates the robustness of such tools if (or when ) adversarial attacks manifest. We demonstrate, for the first time, the synthesis of DNA which - when sequenced and processed - gives an at- tacker arbitrary remote code execution. To study the feasibility of creating and synthesizing a DNA-based exploit, we performed our attack on a modified down- stream sequencing utility with a deliberately introduced vulnerability. "

'A key enabler to advance brain science EBRAINS is a new digital research infrastructure, created by the EU-funded Human Brain Project, that gathers an extensive range of data and tools for brain-related research. EBRAINS will capitalize on the work performed by the Human Brain Project teams in digital neuroscience, brain medicine, and brain-inspired technology and will take it to the next level.'

The contamination and potential ecological risk posed by heavy metals from thirteen (13) sediment samples from different sampling sites along the lower portion of Agusan River were analyzed and assessed using different pollution indices. The results obtained shows that the total digest concentrations of different heavy metals under investigation have the following order: Cd < Pb < Zn < Mn, for both first sampling periods. The speciation and distribution pattern have shown that significant amounts of all metals are present in the residual fraction. Similarly, oxide-bound and organic-bound fractions were found to be highly important for Zn and Mn while Cd and Pb were significantly associated in the residual and exchangeable fractions. The results of different pollution indices moreover, showed that among all the heavy metals being studied, Cd posed the highest environmental risk across all sampling stations in both sampling periods and Mn metal was highly enriched and abundant in all of the sampling stations. Importantly, PCA results suggest that Zn, Mn and Pb may have the same origin while Cd might be coming from different sources, and this is corroborated well with the cluster analysis results. The results obtained from this work provide baseline data on the assessment of heavy metal pollution in the lower portion of Agusan River. Importantly, the acquired environmental indices will certainly help safety managers in assessing and interpreting the potential risk of the sediment associated chemical status that might adversely affect aquatic organisms in the selected sampling sites.

Dead simple machine learning. Our intuitive, easy-to-use platform for machine learning enables anyone to build and deploy models with a few simple clicks. Work in a team? Our platform is specifically designed for collaborative machine learning.

Current, partner and retired OKFN projects are listed below. These are projects that are actively being managed and fostered by the OKFN's staff and communities. To start a new project of your own, see our project proposal page.

Open Economics Working Group is run by the Open Knowledge Foundation in association with the Centre for Intellectual and Property Law (CIPIL) at the University of Cambridge. Its membership consists of leading academics and researchers, public and private sector economists, representatives from national and international public bodies and other experts from around the world.

UBY is a large-scale lexical-semantic resource for natural language processing (NLP) based on the ISO standard Lexical Markup Framework (LMF). UBY combines a wide range of information from expert-constructed and collaboratively constructed resources for English and German. Currently, UBY holds structurally and semantically interoperable versions of nine resources in two languages:  English WordNet, Wiktionary, Wikipedia, FrameNet and VerbNet,  German Wikipedia, Wiktionary and GermaNet, and multilingual OmegaWiki. 

The network of scientists will facilitate scholarly discovery. Institutions will participate in the network by installing VIVO, or by providing semantic web-compliant data to the network.

"Seasonal influenza epidemics are a major public health concern, causing tens of millions of respiratory illnesses and 250,000 to 500,000 deaths worldwide each year1. In addition to seasonal influenza, a new strain of influenza virus against which no previous immunity exists and that demonstrates human-to-human transmission could result in a pandemic with millions of fatalities2. Early detection of disease activity, when followed by a rapid response, can reduce the impact of both seasonal and pandemic influenza3, 4. One way to improve early detection is to monitor health-seeking behaviour in the form of queries to online search engines, which are submitted by millions of users around the world each day. Here we present a method of analysing large numbers of Google search queries to track influenza-like illness in a population."

We build tools and communities to promote open knowledge around the world.