Tag Archives: interactive analysis

Multi-View Framework

The Multi-View Framework is a software component, which offers functionality to combine various visual representations of one or more data sets in a coordinated fashion.  Software components offering visualization capabilities can be included in such a network, as well as software components offering other functionality, such as statistical analysis. Multi-display scenarios can be addressed by the framework as coordination information can be distributed over network between view instances running on distributed machines.

The framework is composed of three libraries: nett, nett-python and nett-connect. nett implements a light-weight underlying messaging layer enabling the communication between views, whereas nett-python implements a python binding for nett, which enables the integration of python-based software components into a multi-view setup. nett-connect adds additional functionality to this basic communication layer, which enables non-experts to create multi-view setups according to their specific needs and workflows.

Interactive optimization of parameters for structural plasticity in neural network models (top left); comparative analysis of NEST simulations (top right); statistical analysis of NEST simulations (bottom left); multi-device and multi-user scenarios (bottom right)
Date of release2017
Version of softwareN/A
Version of documentationN/A
Software availablePlease contact the developers
Documentationhttps://devhub.vr.rwth-aachen.de/cnowke/nett-connect
ResponsibleU Trier: Weyers, Benjamin (weyers@uni-trier.de)
Requirements & dependencies
Target system(s)

InDiProv

The development of InDiProv was co-funded by the HBP during the Ramp-up Phase. This page is kept for reference but will no longer be updated.


This server-side tool is meant to be used for the creation of provenance tracks in context of interactive analysis tools and visualization applications. It is capable of tracking multi-view and multiple applications for one user using this ensemble. It further is able to extract these tracks from the internal data base into a XML-based standard format, such as the W3C Prov-Model or the OPM format. This enables the integration to other tools used for provenance tracking and will finally end up in the UP.

Date of releaseAugust 2015
Version of softwareAugust 2015
Version of documentationAugust 2015
Software availablehttps://github.com/hbpvis
Documentationhttps://github.com/hbpvis
ResponsibleRWTH Aachen: Benjamin Weyers (weyers@vr.rwth-aachen.de) and Torsten Kuhlen (kuhlen@vr.rwth-aachen.de)
Requirements & dependenciesWritten in C++ , Linux environment, MySQL server 5.6, JSON library for annotation, CodeSynthesis XSD for XML serialization and parsing, ZeroMQ library, Boost library, xercex-c library and mysqlcppcon library
Target system(s)Server-side systems