binjr is a Java based, open source, time series visualization tool. It can plot time series data from multiple sources as a set of charts, which end users can navigate or zoom in and out.
It is a client application, packaged as a single executable JAR file and has no other requirement than a compatible Java Runtime Environment.
Its focus is on enabling end users to constitute their own custom sets of views for the data exposed by various sources, generally in ways that are not proposed by the front-ends these sources might already propose.
As such, binjr aims to become a valuable tool in forensic analysis when working with data sources that do not provide such flexible visualization natively.
binjr is Java application, built on top of JavaFX, and requires a Java Runtime Environement version 1.8 with JavaFX version 8u40 or later.
Using the latest available version is highly recommended, as JavaFX is still an area where bug fixes and performance improvements are routinely provided with each new version.
The latest release can be found here
You can either build it from source using Maven after cloning the repository, or download binjr.jar.
All dependencies are packaged inside the executable jar, so in order to start the application simply run: java -jar binj.jar (or double-click the jar file, provided your environment is configured adequately).
The documentation can be found here. It’s not yet complete, but getting there.
If you encounter an issue, or would like to suggest an enhancement or a new feature, you may do so here.
If you would like to contribute, please sumbit a pull request.
How is it licensed?
binjr is released under the Apache License version 2.0.
What is the status of the project?
binjr is very much a work in progress but it has reached its first significant milestone. The current release should be reasonably stable and the feature set, while limited, should hopefully prove more useful than frustrating.
For the time being, the only source with significant support is JRDS, a monitoring application written in Java, but the project aims to quickly offer an API flexible enough to allow the rapid development of data adapters for any systems capable of exporting time series data.