Synner is a tool that helps users generate real-looking synthetic data by visually and declaratively specifying the
properties of the dataset such as each field’s statistical distribution, its domain, and its relationship to other fields.
It provides instant feedback on every user interaction by updating multiple visualizations of the generated dataset and
even suggests data generation specifications from a few user examples and interactions. Synner visually communicates
the inherent randomness of statistical data generation.
Is this Real? Generating Synthetic Data that Looks Real
Miro Mannino, Azza Abouzied - UIST'19
Synner: Generating Realistic Synthetic Data
Miro Mannino, Azza Abouzied - SIGMOD'20
This repository contains:
Synner's source code and the datasets we used for our publications.
Synner can be run as a server, which also provides the user interface, or as a command line interface application.
Synner server can be run by launching the main static method in edu.nyu.dtl.synner.SynnerServerApplication
This method will run Synner's server as a Spring Boot application in the port 5000
Synner can be launched from the command line interface with Java by using the main static method in
class edu.nyu.dtl.synner.core.Main
This method accepts a path of a CSV file as console argument, where specifications are written. For example:
java -classpath "..." edu.nyu.dtl.synner.core.Main my-specifications.json