Maverick, TACC’s latest addition to its suite of advanced computing systems, combines capacities for interactive advanced visualization and large-scale data analytics as well as traditional high performance computing. Recent exponential increases in the size and quantity of digital datasets necessitate new systems such as Maverick, capable of fast data movement and advanced statistical analysis. Maverick debuts the new NVIDIA K40 GPU for remote visualization and GPU computing to the national community. This will be added to Statistics Resources and Big Data Subject Tracer™.
Sense – A Collaborative Cloud Platform for Data Science and Big Data Analytics https://senseplatform.com/
Collaborate on, scale, and deploy data analysis and advanced analytics projects radically faster. Use the most powerful tools — R, Python, JavaScript, Redshift, Hive, Impala, Hadoop, and more — supercharged and integrated in the cloud. Join some of the world’s smartest researchers, data scientists, and enterprises using Sense to do more with data, faster. Features include: a) Use the Most Powerful Tools, Supercharged in the Cloud – Use the powerful tools you know — R, Python, JavaScript, Redshift, Hive, Impala, Hadoop, or any engine — supercharged by Sense’s scalable cloud platform. Build, scale, and deploy data analysis, statistical modeling, and advanced analytics projects radically faster; b) Scale Your Analysis Without the Typical Hassles – Scale your analysis to a larger machine or across hundreds of distributed cores, all without managing servers, transferring files, or fighting complex dependencies. Enjoy instant provisioning, simple billing, and blazing fast connectivity to Amazon’s S3, Redshift, DynamoDB, and Hadoop EMR services; c) Collaborate on Projects Easily – Collaborate on public and private projects on an unified platform for data science and big data analytics. Never be out-of-sync again or struggle to share results with the people you work with; and d)Deploy Your Analytics as Reproducible Jobs – Build and automate your analytics and reporting pipelines. Turn ad-hoc analysis into reproducible jobs without complex deployment processes. Share reproducible workflows powered by isolated containers not fragile scripts. This will be added to the tools section of Research Resources Subject Tracer™ Information Blog. This will be added to Statistics Resources and Big Data Subject Tracer™. This will be added to Grid, Distributed and Cloud Computing Resources Subject Tracer™.
The Earth Observing System Data and Information System (EOSDIS) is a key core capability in NASA’s Earth Science Data Systems Program. It provides end-to-end capabilities for managing NASA’s Earth science data from various sources – satellites, aircraft, field measurements, and various other programs. For the EOS satellite missions, EOSDIS provides capabilities for command and control, scheduling, data capture and initial (Level 0) processing. These capabilities, constituting the EOSDIS Mission Operations, are managed by the Earth Science Mission Operations (ESMO) Project. NASA network capabilities transport the data to the science operations facilities. The remaining capabilities of EOSDIS constitute the EOSDIS Science Operations, which are managed by the Earth Science Data and Information System (ESDIS) Project. These capabilities include: generation of higher level (Level 1-4) science data products for EOS missions; archiving and distribution of data products from EOS and other satellite missions, as well as aircraft and field measurement campaigns. The EOSDIS science operations are performed within a distributed system of many interconnected nodes (Science Investigator-led Processing Systems and distributed, discipline-specific, Earth science data centers) with specific responsibilities for production, archiving, and distribution of Earth science data products. The distributed data centers serve a large and diverse user community (as indicated by EOSDIS performance metrics) by providing capabilities to search and access science data products and specialized services. Learn more about the EOSDIS Science System and details of the EOSDIS Science System’s internal and external interfaces. This will be added to the tools section of Research Resources Subject Tracer™ Information Blog. This will be added to Statistics Resources and Big Data Subject Tracer™.
The U.S. Census Bureau recently released a new interactive tool designed to visualize the key economic findings found in the statistical agency’s most recent Business Dynamics Statistics report released in July. The Business Dynamics Statistics Visualization Tool spans four decades of information about America’s economy – providing key insights on job creation and loss during the most recent recession. Economic measures such as employment, number of establishments and number of firms can be analyzed for a single year or multiple years from 1977 to 2011. The tool has three major components: an interactive thematic map for the 50 states, interactive bar charts that give side-by-side comparisons of states and business sectors as well as time series data comparisons over a range of time. “We are providing a new and easy way for users to look at key economic trends about America’s economy by visualizing statistics over time,” said Thomas Louis, the associate director for research and methodology and chief scientist at the Census Bureau. “The latest Business Dynamics Statistics report shows older firms dominate the economy, new firms are entering the economy slowly, and there has been an overall decline in job creation in recent years.” In partnership with the Ewing Marion Kauffman Foundation, the Census Bureau has produced annual data series for the Business Dynamics Statistics since 2008. For more information on the Business Dynamics Statistics program, go to <http://www.census.gov/ces/dataproducts/bds/>. Guidance on how to use the visualization tool can be found at <http://www.census.gov/ces/dataproducts/bds/what_to_do_first.html>. This will be added to the tools section of Research Resources Subject Tracer™ Information Blog. This will be added to Statistics Resources and Big Data Subject Tracer™.
The Open Data Institute is catalysing the evolution of open data culture to create economic, environmental, and social value. It helps unlock supply, generates demand, creates and disseminates knowledge to address local and global issues. They convene world-class experts to collaborate, incubate, nurture and mentor new ideas, and promote innovation. They enable anyone to learn and engage with open data, and empower their teams to help others through professional coaching and mentoring. Founded by Sir Tim Berners-Lee and Professor Nigel Shadbolt, the ODI is an independent, non-profit, non-partisan, limited by guarantee company. This will be added to Research Resources Subject Tracer™ Information Blog. This will be added to Statistics Resources and Big Data Subject Tracer™.
I have just updated my white paper dataset link compilation for Statistics Resources Subject Tracer™ by Marcus P. Zillman, M.S., A.M.H.A. It is now a 25 page .pdf document 231KB. [Updated on December 19, 2013] Other white papers are available by clicking here.
The Open Data Barometer takes a multidimensional look at the spread of Open Government Data (OGD) policy and practice across the world. Combining peer-reviewed expert survey data and secondary data sources, the Barometer explores countries readiness to secure benefits from open data, the publication of key datasets, and evidence of emerging impacts from OGD.The Open Data Barometer was conceived of as a companion study to the 2013 Web Index. The Web Index is a multidimensional measure of the Web’s use, utility and impact. The Barometer focuses in on the context, availability and emerging impacts of Open Government Data (OGD)The Barometer is designed to provide a clear and comparable analysis of the macro-level context for open data, the availability of open data, and emerging impacts of open data, across the world. It will support advocates, researchers and policy makers to better understand the development of open data globally, and will contribute to a growing evidence base on open government data.The Barometer is supported by the common assessment methods component of the Web Foundation’s ‘Exploring the Emerging Impacts of Open Data in Developing Countries’ (ODDC) project, and by the Open Data Institute, as well as by the Web Index team at the World Wide Web Foundation. The 2013 Open Data Barometer is focused on piloting methods for assessing open data supply, building towards further iterations of the methodology and survey in 2014 and beyond. This will be added to the tools section of Research Resources Subject Tracer™ Information Blog. This will be added to Statistics Resources and Big Data Subject Tracer™.
Orange – Open Source Data Visualization and Analysis for Novice and Experts http://orange.biolab.si/
Open source data visualization and analysis for novice and experts. Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining. Packed with features for data analytics. This will be added to Statistics Resources and Big Data Subject Tracer™ This will be added to Data Mining Resources Subject Tracer™.
SCaVis is an environment for scientific computation, data analysis and data visualization designed for scientists, engineers and students. The program incorporates many open-source software packages into a coherent interface using the concept of dynamic scripting. SCaVis can be used everywhere where an analysis of large numerical data volumes, data mining, statistical analysis and mathematics are essential (natural sciences, engineering, modeling and analysis of financial markets). SCaVis is fully multiplatform and runs on any platform where Java is installed. As a Java application, SCaVis takes the full advantage of multicore processors. This will be added to Statistics Resources and Big Data Subject Tracer™ This will be added to Data mining Resources Subject Tracer™.
Knoema is a knowledge platform. The basic idea is to connect data with analytical and presentation tools. As a result, they end with one uniformed platform for users to access, present and share data-driven content. Within Knoema, they capture most aspects of a typical data use cycle: accessing data from multiple sources, bringing relevant indicators into a common space, visualizing figures, applying analytical functions, creating a set of dashboards, and presenting the outcome. This will be added to Knowledge Discovery Resources Subject Tracer™ Information Blog. This will be added to Statistics Resources and Big Data Subject Tracer™. This will be added to the tools section of Research Resources Subject Tracer™ Information Blog. This has been added to Online Research Browsers white paper.
