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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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The Data Bank operates a computer program service related to nuclear energy applications. The software library collects programs, compiles and verifies them in an appropriate computer environment, ensuring that the computer program package is complete and adequately documented. This collection of material contains more than 2000 documented packages and group cross-section data sets. We distribute these codes on CD-ROM, DVD and via electronic transfer to about 900 nominated NEA Data Bank establishments (see the rules for requesters). Standard software verification procedures are used following an ANSI/ANS standard.
The Google Code Archive contains the data found on the Google Code Project Hosting Service, which turned down in early 2016. This archive contains over 1.4 million projects, 1.5 million downloads, and 12.6 million issues. Google Project Hosting powers Project Hosting on Google Code and Eclipse Labs. Project Hosting on Google Code Eclipse Labs. It provides a fast, reliable, and easy open source hosting service with the following features: Instant project creation on any topic; Git, Mercurial and Subversion code hosting with 2 gigabyte of storage space and download hosting support with 2 gigabytes of storage space; Integrated source code browsing and code review tools to make it easy to view code, review contributions, and maintain a high quality code base; An issue tracker and project wiki that are simple, yet flexible and powerful, and can adapt to any development process; Starring and update streams that make it easy to keep track of projects and developers that you care about.
The CAD-60 and CAD-120 data sets comprise of RGB-D video sequences of humans performing activities which are recording using the Microsoft Kinect sensor. Being able to detect human activities is important for making personal assistant robots useful in performing assistive tasks. Our CAD dataset comprises twelve different activities (composed of several sub-activities) performed by four people in different environments, such as a kitchen, a living room, and office, etc. Tested on robots reactively responding to the detected activities.
Data products developed and distributed by the National Institute of Standards and Technology span multiple disciplines of research and are widely used in research and development programs by industry and academia. NIST's publicly available data sets showcase its committment to providing accurate, well-curated measurements of physical properties, exemplified by the Standard Reference Data program, as well as its committment to advancing basic research. In accordance with U.S. Government Open Data Policy and the NIST Plan for providing public access to the results of federally funded research data, NIST maintains a publicly accessible listing of available data, the NIST Public Dataset List (json). Additionally, these data are assigned a Digital Object Identifier (DOI) to increase the discovery and access to research output; these DOIs are registered with DataCite and provide globally unique persistent identifiers. The NIST Science Data Portal provides a user-friendly discovery and exploration tool for publically available datasets at NIST. This portal is designed and developed with data.gov Project Open Data standards and principles. The portal software is hosted in the usnistgov github repository.
>>>!!!<<< stated 13.02.2020: the repository is offline >>>!!!<<< Data.DURAARK provides a unique collection of real world datasets from the architectural profession. The repository is unique, as it provides several different datatypes, such as 3d scans, 3d models and classifying Metadata and Geodata, to real world physical buildings.domain. Many of the datasets stem from architectural stakeholders and provide the community in this way with insights into the range of working methods, which the practice employs on large and complex building data.