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The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
[8] R. Krishna et al. Berkeley 3-D Object Dataset 849 images taken in 75 different scenes. About 50 different object classes are labeled. Object bounding boxes and labeling. 849 labeled images, text Object recognition 2014 [9] [10] A. Janoch et al. Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500)
The sample JSONiq code below computes the area code and the number of all people older than 20 from a collection of JSON person objects (see the JSON article for an example object). for $ p in collection ( "persons" ) where $ p.age gt 20 let $ home := $ p.phoneNumber [][ $ $. type eq "home" ] . number group by $ area := substring-before ...
^ The current default format is binary. ^ The "classic" format is plain text, and an XML format is also supported. ^ Theoretically possible due to abstraction, but no implementation is included. ^ The primary format is binary, but text and JSON formats are available. [8] [9]
Dumps are produced for a specific set of namespaces and wikis, and then made available for public download. Each dump output file consists of a tar.gz archive which, when uncompressed and untarred, contains one file, with a single line per article, in json format. [Project's main homepage]
OData uses different formats for representing data and the data model. In OData protocol version 4.0, JSON format is the standard for representing data, with the Atom format still being in committee specification stage. For representing the data model, the Common Schema Definition Language (CSDL) is used, which defines an XML representation of ...
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The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski. [ citation needed ] PFA provides a way for analytic applications to describe and exchange predictive models produced by analytics and machine learning algorithms.