SOCR Distributome Project
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===Project Goals=== | ===Project Goals=== | ||
| - | The Probability Distributome Project aims to provide an intuitive, efficient, portable and | + | The [http://www.distributome.org/ Probability Distributome Project] aims to provide an intuitive, efficient, portable and extensible infrastructure for exploring, navigating, discovering and expanding the knowledge (meta-data) about the internal distribution properties and characteristics, and inter-distributional relations. |
| - | This specific project aims to design, implement, test and validate 2 new features of the [http://distributome.org/js/DistributomeNavigator.html Probability Distributome | + | This specific project aims to design, implement, test and validate 2 new features of the [http://distributome.org/js/DistributomeNavigator.html Probability Distributome] - Enable the Distributome Editor functionality, and Redesign Distributome XML database to enable Bib TeX reference citations. |
===Project Specifics=== | ===Project Specifics=== | ||
Revision as of 22:09, 29 March 2012
Contents |
SOCR Project - SOCR Distributome Project
Background
Probability mass (for discrete processes) or probability density (for continuous processes) functions describe the likelihood of random variables (observation of a process) to take certain values. For instance, we can assign a probability distribution functions to each possible value of discrete and continuous processes, e.g., rolling a hexagonal (6-face) die or picking a random number in the range [0:1]. Most (but not all) probability mass, density and distribution functions have analytical representation, can be computed efficiently, and have specific properties and characteristics. In addition, there are intricate relations between different probability distributions.
Project Goals
The Probability Distributome Project aims to provide an intuitive, efficient, portable and extensible infrastructure for exploring, navigating, discovering and expanding the knowledge (meta-data) about the internal distribution properties and characteristics, and inter-distributional relations.
This specific project aims to design, implement, test and validate 2 new features of the Probability Distributome - Enable the Distributome Editor functionality, and Redesign Distributome XML database to enable Bib TeX reference citations.
Project Specifics
Project Source
- Editor Prototype
- Navigator
- JavaScripts: protovis-r3.2.js, common.js, distributome.js, jquery.js, splitter.js, xml2json.js, editor.js
- XML Database: Distributome.xml, Distributome.xsd, and Distributome.xml.html.
Tasks
- (Easy) Enable the Editor functionality (DistributomeEditor.html, XML_Editor button) in the main Navigator window (DistributomeNavigator.html).
- (Creative) Enable the drag-and-drop functionality for selecting in the graph a node/distribution or an edge/relation and dropping them to populate the XML editor fields.
- (Easy) Test that newly-generated XML can be saved and consumed by the Navigator and displayed appropriately in the graph.
- (Creative) Review this slight redesign spec of the XML DB (Distributome.xml) and the suggested solution and see if you can implement a pilot that utilizes the new pair of XML(nodes/edges)+BiBTeX(references), replacing the current XML DB (Distributome.xml). Note that the project spec page already includes a specific solution; we just need to think about the packaging of the solution with the new XML/BiBTeX format.
- (Creative) Consider the redesign of the Editor according to these schematic diagrams Fig1 and Fig2.
References
- Current Distributome XML Database and XSD Model
- Distributome Prototype (Applet)
- Leemis and McQueston's TAS Distrubutions Article (2008)
- Song's IIE Transactions Distribution Relations Paper (2004)
See also
- Distributome Wiki Page
- Try to think of converting the Distributome HTML-embedded applet into a client-site executable Java application using Java Web-Start (see the example with Cytoscape).
- A Distribution-relationships chart
- A list of probability distributions
- A list of SOCR probability distributions
- XML DOM MathJax Parsing HTML Examples
- JavaScript By-Example Tutorial and JavaScript Object API
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