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What (who) is data driven - definition

DDDAS; Dynamic Data Driven Application Simulation; Dynamic Data Driven Application System; Dynamic data driven application system; Dynamic data-driven application system; Dynamic data driven application systems; Dynamic data driven applications systems; Dynamic Data Driven Applications Systems - (DDDAS)

data driven

A data driven architecture/language performs computations in an order dictated by data dependencies. Two kinds of data driven computation are dataflow and demand driven. From about 1970 research in parallel data driven computation increased. Centres of excellence emerged at MIT, CERT-ONERA in France, NTT and ETL in Japan and Manchester University.

Data-driven testing

SOFTWARE TESTING METHODOLOGY THAT IS USED IN THE TESTING OF COMPUTER SOFTWARE TO DESCRIBE TESTING DONE USING A TABLE OF CONDITIONS DIRECTLY AS TEST INPUTS AND VERIFIABLE OUTPUTS

Data-Driven Testing; Parameterized test; Parameterized testing

Data-driven testing (DDT), also known as table-driven testing or parameterized testing, is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. In the simplest form the tester supplies the inputs from a row in the table and expects the outputs which occur in the same row.

https://en.wikipedia.org/wiki/Data-driven_testing

Data-driven programming

PROGRAMMING PARADIGM

Applications of data-driven programming

In computer programming, data-driven programming is a programming paradigm in which the program statements describe the data to be matched and the processing required rather than defining a sequence of steps to be taken. Standard examples of data-driven languages are the text-processing languages sed and AWK, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.

https://en.wikipedia.org/wiki/Data-driven_programming

Wikipedia

Dynamic Data Driven Applications Systems

Dynamic Data Driven Applications Systems (DDDAS) is a new paradigm whereby the computation and instrumentation aspects of an application system are dynamically integrated in a feed-back control loop, in the sense that instrumentation data can be dynamically incorporated into the executing model of the application, and in reverse the executing model can control the instrumentation. Such approaches have been shown that can enable more accurate and faster modeling and analysis of the characteristics and behaviors of a system and can exploit data in intelligent ways to convert them to new capabilities, including decision support systems with the accuracy of full scale modeling, efficient data collection, management, and data mining. The DDDAS concept - and the term - was proposed by Frederica Darema for the National Science Foundation (NSF) workshop in March 2000.

There are several affiliated annual meetings and conferences, including:

DDDAS workshop at ICCS (since 2003)
DyDESS conference and workshop at MIT organized by Sai Ravela and Adrian Sandu
DDDAS special session at the ACC organized by Puneet Singla and Dennis Bernstein and Sai Ravela
DDDAS Special Session Information Fusion

https://en.wikipedia.org/wiki/Dynamic Data Driven Applications Systems

Examples of use of data driven

1. "It‘s possible to shift to a more data–driven approach of environmental protection," said Daniel C.

2. "Our economy is increasingly data–driven," she told the American Constitution Society for Law and Policy convention in June.

3. He said he hopes the rise of data–driven decision–making in education will continue when a new administration begins.

4. Some researchers argue that better methods of calculation indicate a much smaller racial gap nationwide.) Goals and data–driven decisions make a difference Baltimore County is particularly effective because it has "goals, master plans, and data–driven decisionmaking," all with an eye toward equitable outcomes, says educational research consultant Michael Holzman, author of the Schott reports.

5. The central bank, however, was a little more hawkish on future policy than most Fed watchers had forecast, saying the next decision would be data driven.