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Hello, and welcome to the VisTrails Wiki.
= VisTrails =


== What is it? ==
'''VisTrails''' is an open-source scientific workflow and provenance management system developed at the [https://vida.engineering.nyu.edu/ VIDA Center] at New York University. It supports computational science by capturing and managing the complete history of the exploratory process: the workflows, their executions, and the results they produce.


Recently, workflows have been emerging as a paradigm for representing and managing complex
VisTrails is actively developed again. The new version, '''[[VisTrailsJL]]''', is a complete reimplementation in [https://julialang.org/ Julia] that brings modern performance, notebook-based workflow authoring, and native compatibility with existing <code>.vt</code> files. See the [https://github.com/VIDA-NYU/VisTrailsJL GitHub repository] to get started.
computations. Workflows can capture complex analyses processes at various levels of detail and
provide the provenance information necessary for reproducibility, result publication and result
sharing among collaborators. Because of the formalism they provide and the automation they
support, workflows have the potential to accelerate and transform the information analysis
process. Workflows are rapidly replacing primitive shell scripts as evidenced by the release of
Apple’s Mac OS X Automator, Microsoft Windows Workflow Foundation, and the SGI
Scientific Workflow Solution.
VisTrails is a new scientific workflow management system developed at the University of Utah that
provides support for data exploration and visualization. Whereas workflows have been
traditionally used to automate repetitive tasks, for applications that are exploratory in nature, very
little is repeated---change is the norm. As an engineer or scientist generates and evaluates
hypotheses about data under study, a series of different, albeit related, workflows are created
while a workflow is adjusted in an interactive process. VisTrails was designed to manage these
rapidly-evolving workflows. VisTrails streamlines the creation, execution and sharing of complex
visualizations, data mining or other large-scale data analysis applications. By automatically
managing the data, metadata, and the data exploration process, VisTrails allows users to focus on
the task at hand and relieves them from tedious and time-consuming tasks involved in organizing
the vast volumes of data they manipulate. VisTrails provides infrastructure that can be combined
with and enhance existing visualization and workflow systems.  
Although VisTrails was originally built to address the needs of exploratory scientific applications,
the infrastructure it provides is very general. This became clear as the system was demoed to
people from different domains, both from industry and academia. VisTrails has the potential to  
reduce the time to insight in virtually any exploratory task.


== Downloading ==
== What's New ==


Get the open source version of VisTrails [[downloads|here]].
After a hiatus since 2018, VisTrails is back. '''VisTrailsJL''' (v2.2) is a ground-up reimplementation in Julia that preserves everything that made the original system valuable — comprehensive provenance, visual workflow management, and support for real scientific use cases — while modernizing the foundation:


== Publications and Presentations ==
* '''Julia reimplementation''' — Julia's JIT compilation brings performance suitable for demanding scientific workflows, and its rich ecosystem (DataFrames.jl, DifferentialEquations.jl, Plots.jl) is a natural fit.
* '''Notebook-based workflow authoring''' — Workflows can now be defined directly in Jupyter notebooks using simple <code>#|</code> directives, with no GUI required.
* '''Full <code>.vt</code> compatibility''' — Existing workflows created with the Python version can be loaded, replayed, and visualized without modification.
* '''Git-native version control''' — Standard git replaces the custom versioning infrastructure for workflow history.
* '''Python interoperability''' — Existing Python modules and libraries remain accessible via PyCall.jl.


[http://www.vistrails.org/download/download.php?type=PUB&id=ipaw2006.pdf Managing Rapidly-Evolving Scientific Workflows]  (by Juliana Freire, Claudio T. Silva, Steven P. Callahan, Emanuele Santos, Carlos E. Scheidegger and Huy T. Vo) Invited paper, in the proceedings of the International Provenance and Annotation Workshop (IPAW), 2006. [http://www.vistrails.org/download/download.php?type=PUB&id=ipaw2006-slides.pdf presentation]
The original Python codebase (v2.2) is preserved in the repository for reference and compatibility testing.


[http://www.sci.utah.edu/publications/SCITechReports/UUSCI-2006-017.pdf Visualization in Radiation Oncology: Towards Replacing the Laboratory Notebook] (by Erik W. Anderson, Steven P. Callahan, George T. Y. Chen, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) SCI Institute Technical Report, No. UUSCI-2006-17, University of Utah, 2006.
; Quick links
: [https://github.com/VIDA-NYU/VisTrailsJL GitHub (VisTrailsJL)] &nbsp;|&nbsp; [[Documentation]] &nbsp;|&nbsp; [[Publications, Tutorials and Presentations]] &nbsp;|&nbsp; [[MailingLists|Mailing Lists]]


[http://www.sci.utah.edu/publications/SCITechReports/UUSCI-2006-016.pdf Using Provenance to Streamline Data Exploration through Visualization] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) SCI Institute Technical Report, No. UUSCI-2006-016, University of Utah, 2006.
== Core Features ==


[http://www.vistrails.org/download/download.php?type=PUB&id=sciflow2006.pdf Managing the Evolution of Dataflows with VisTrails] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) IEEE Workshop on Workflow and Data Flow for Scientific Applications (SciFlow) 2006. [http://www.vistrails.org/download/download.php?type=PUB&id=sciflow2006-slides.pdf presentation]
=== Provenance and Workflow History ===


[http://www.vistrails.org/download/download.php?type=PUB&id=sigmod2006.pdf VisTrails: Visualization meets Data Management] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) In Proceedings of ACM SIGMOD 2006. [http://www.vistrails.org/download/download.php?type=PUB&id=sigmod2006-slides.pdf presentation]
A defining feature of VisTrails is its '''comprehensive provenance infrastructure'''. Unlike systems that track only the current state of a workflow, VisTrails maintains the full history of every step taken during an exploratory analysis — what was tried, what was changed, and what results each version produced. This enables users to:


[http://www.vistrails.org/download/download.php?type=PUB&id=vistrails-tutorial.pdf VisTrails: A Short Tutorial] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) Technical Report. University of Utah, 2005.
* Navigate and compare workflow versions in an intuitive tree interface
* Undo changes without losing intermediate results
* Visually diff two workflows and their outputs side by side
* Reproduce any prior result exactly, long after it was first computed


[http://www.vistrails.org/download/download.php?type=PUB&id=vis2005.pdf VisTrails: Enabling Interactive Multiple-View Visualizations] (by Louis Bavoil, Steven P. Callahan, Patricia J. Crossno, Juliana Freire, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) In Proceedings of IEEE Visualization, 2005. [http://www.vistrails.org/download/download.php?type=PUB&id=vis2005-slides.pdf presentation]
Provenance information is stored as XML or in a relational database (Python version), or managed via standard git (Julia version).


[http://www.vistrails.org/download/download.php?type=PUB&id=poster.pdf A poster on VisTrails applications]
=== Building and Running Workflows ===


== Documentation ==
VisTrails supports workflows expressed as '''dataflows''', with support for functional loops and conditional branching. Workflows can be run interactively through the GUI or in batch mode via a server. The system is designed to connect loosely coupled resources — specialized libraries, web services, and grid computing infrastructure.


=== [[Users_Guide|User's Guide]] ===
In VisTrailsJL, workflows can also be defined declaratively in Jupyter notebooks:
On the link above is a (always evolving) User's Guide.


=== [[Video_Tutorial|Video Tutorial]]  ===
<pre>
#| workflow: my_analysis


We are in the process of creating a video tutorial that can be used to guide users through the process of learning to use VisTrails. The videos that follow below are a preliminary version of this tutorial, and will keep evolving towards a complete tutorial.
#| module-id: input
#| module-type: basic:Integer
#| params:
#|  - value: 42


{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_001_AddModule-H.264_LAN_960x540.mov|text=Adding a Module}}
#| module-id: process
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_002_AddParameter-H.264_LAN_960x540.mov|text=Adding a Parameter}}
#| module-type: mypackage:Transform
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_003_ConnectingModule-H.264_LAN_960x540.mov|text=Connecting Two Modules}}
#| inputs:
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_004_Add_ParameterModule-H.264_LAN_960x540.mov|text=Adding a Parameter via Modules}}
#|   - value: input.value
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_005_ParameterExploration-H.264_LAN_960x540.mov|text=Parameter Space Exploration}}
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_006_VersionTreeInteraction-H.264_LAN_960x540.mov|text=Version Tree Interaction}}
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_007_VisualDiff-H.264_LAN_960x540.mov|text=The Visual Diff}}
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=Tutorial_008_QueryByExample-H.264_LAN_960x540.mov|text=Querying the Version Tree and Pipelines}}


=== Videos  ===
#| execute
</pre>


Please note that some of these videos were generated using versions of VisTrails, and the interface might look different than the one available in the most up-to-date version.
Packages and modules are easy to add. The <code>JuliaSource</code> and <code>PythonSource</code> module types allow custom code to be embedded directly in a workflow without creating a full package.


{| {{Prettytable}}
=== Publishing Reproducible Results ===
 
VisTrails 2.0 introduced support for embedding reproducible results directly in LaTeX/PDF documents via a companion LaTeX package. A figure in a compiled PDF becomes active: clicking it invokes VisTrails and re-executes the workflow that produced it on any machine with the software installed.
 
<pre>
\usepackage{vistrails}
 
\begin{figure}
\begin{center}
\subfigure[a=0.9]{\vistrail[filename=alps.vt, version=2, pdf]{width=8cm}}
\caption{Clicking this figure retrieves and re-runs the workflow that produced it.}
\end{center}
\end{figure}
</pre>
 
=== Querying and Refining Workflows ===
 
Users can construct expressive queries over a collection of workflows using the same interface used to build them. An '''analogy mechanism''' allows complex modifications to be applied to one workflow by example from another, without manually editing workflow specifications — useful when a family of related analyses needs to evolve together.
 
=== Visualizing and Comparing Results ===
 
VisTrails provides a '''spreadsheet view''' for comparing the results of multiple workflows or multiple parameterizations of the same workflow side by side. The visual diff interface highlights structural differences between two workflow versions. Workflows and their version trees can be rendered as SVG (VisTrailsJL) or displayed on large-format display walls.
 
== Getting Started ==
 
=== VisTrailsJL (Julia — current) ===
 
<pre>
# Clone the repository
git clone https://github.com/VIDA-NYU/VisTrailsJL.git
cd VisTrailsJL/julia
 
# Install dependencies
julia --project=. -e 'using Pkg; Pkg.instantiate()'
 
# Load and render an existing workflow
julia --project=. -e '
using VisTrailsJL
vt = load_vistrail("../examples/gcd.vt")
workflow = get_pipeline(vt)
render_pipeline_svg(workflow, "workflow.svg")
'
</pre>
 
See the [https://github.com/VIDA-NYU/VisTrailsJL/blob/v2.2/julia/QUICKSTART.md Quickstart Guide] for a full walkthrough.
 
=== Python VisTrails (legacy reference) ===
 
The original Python version (v2.2, requires Python 2 / PyQt4) is preserved in the repository for reference and for loading existing <code>.vt</code> files in legacy environments.
 
<pre>
# GUI mode
python vistrails/run.py
 
# Batch mode
python vistrails/run.py --batch [options]
</pre>
 
== Projects Using VisTrails ==
 
VisTrails has supported real scientific workflows across a wide range of domains. The following projects reflect the breadth of communities that have relied on the system.
 
{| class="wikitable"
|-
|-
|http://www.vistrails.org/images/Demonstration_thumb.png
! USGS Habitat Modeling
|'''Demonstration'''
! NASA Climate Data Analysis
This video shows basic usage of VisTrails by going through three examples.  
! DOE CDAT
Some of the features shown are:
|-
* Manipulating a pipeline by adding modules and connections and setting parameters
| [[Image:usgs.png|200px|left]]
* Performing a parameter exploration
| [[Image:nasa.png|200px|left]]
As this is an old version of the system, some of the features are not currently available.
| [[Image:cdat.png|200px|left]]
|}
 
{| class="wikitable"
|-
! ALPS Simulations
! NSF STC CMOP
! NSF CDI Wildfire
|-
| [[Image:alps-shot.png|200px|left]]
| [[Image:cmop-ss.png|200px|left]]
| [[Image:wildfire.png|200px|center]]
|}


{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=demo_high_res.mov|text=High Resolution(81 MB)}}
{| class="wikitable"
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=demo_med_res.mov|text=Medium Resolution(29 MB)}}
{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=demo_low_res.mov|text=Low Resolution(16 MB)}}
|-
|-
|http://www.vistrails.org/images/Radiation_thumb.png
! NSF DataONE-EVA
|'''Radiation Oncology'''
|-
This video shows how some of VisTrails features were used on a Radiation Oncology study.
| [[Image:eva.png|200px|left]]
|}


As this is an old version of the system, some of the features are not currently available.
[https://vistrails.org/index.php/Projects_using_VisTrails See all projects using VisTrails]


{{qt|link=http://www.vistrails.org/download/download.php?type=MEDIA&id=vt-rad-onc.mov|text=High Resolution(70 MB)}}
== VisTrails in Teaching ==
|}
 
VisTrails has been used as a teaching tool in courses on Scientific Visualization and Digital Media. Its provenance infrastructure makes it particularly effective in educational settings, where capturing and comparing student workflows provides rich feedback for instructors and learners alike.
 
Our [http://www.cs.utah.edu/~juliana/pub/vistrails-teaching-eurographics2010.pdf paper] describing a provenance-rich teaching methodology received the '''Best Paper Award''' at Eurographics 2010 Education.
 
[[Vistrails and Teaching|More on VisTrails and Teaching]]
 
== System Documentation ==
 
* [[Documentation|Documentation overview]]
* [https://github.com/VIDA-NYU/VisTrailsJL/blob/v2.2/julia/README.md VisTrailsJL README]
* [https://github.com/VIDA-NYU/VisTrailsJL/blob/v2.2/julia/QUICKSTART.md Quickstart Guide]
* [https://github.com/VIDA-NYU/VisTrailsJL/blob/v2.2/julia/docs/IMPLEMENTATION_STATUS.md Implementation Status]
* [[FAQ]]
* [[Users_Guide|Python User's Guide (legacy)]]
 
To report bugs or request features, please use the [https://github.com/VIDA-NYU/VisTrailsJL/issues issue tracker].


== People ==
For questions not covered by the documentation, post to the [https://vistrails.org/index.php/MailingLists mailing list].


=== Principal Investigators ===
== Citing VisTrails ==


* Dr. [http://www.cs.utah.edu/~juliana Juliana Freire]
If you use VisTrails or VisTrailsJL in your research, please cite the relevant work:
* Dr. [http://www.cs.utah.edu/~csilva Claudio Silva]


=== Current Team ===
'''Original VisTrails system:'''
<pre>
@inproceedings{vistrails2006,
  title    = {VisTrails: visualization meets data management},
  author    = {Callahan, Steven P and Freire, Juliana and Scheidegger,
              Carlos E and Silva, Cl{\'a}udio T and Vo, Huy T},
  booktitle = {Proceedings of the 2006 ACM SIGMOD International Conference
              on Management of Data},
  pages    = {745--747},
  year      = {2006},
  doi      = {10.1145/1142473.1142574}
}
</pre>


* [http://www.sci.utah.edu/~eranders Erik Anderson]
'''VisTrailsJL (Julia reimplementation):'''
* [http://www.sci.utah.edu/~stevec Steven P. Callahan]
<pre>
* [http://www.cs.utah.edu/~dakoop David Koop]
@software{vistrailsjl2025,
* [http://www.sci.utah.edu/~emanuele Emanuele Santos]
  title  = {VisTrailsJL: A Julia Implementation of VisTrails},
* [http://www.sci.utah.edu/~cscheid Carlos E. Scheidegger]
  author = {Silva, Claudio T},
* [http://www.sci.utah.edu/~natesmith Nathan Smith]
  year  = {2025},
* [http://www.sci.utah.edu/~hvo Huy T. Vo]
  url    = {https://github.com/VIDA-NYU/VisTrailsJL}
}
</pre>


=== Previous Members ===
[[Publications, Tutorials and Presentations|Full publication list]]


* Louis Bavoil
== People ==
* Marcelo Nery dos Santos
[[People]]
* Wayne Tyler


== Sponsors ==
== Sponsors ==


This work has been partially supported by the National Science Foundation under grants  
This work has been supported in part by the National Science Foundation under grants
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0513692 IIS-0513692],  
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0905385 IIS-0905385],
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0401498 CCF-0401498],  
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0844572 IIS-0844572],
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0541560 CNS-0541560], [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0405402 OISE-0405402],  
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0746500 IIS CAREER-0746500],
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0424602 OCE-0424602],  
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0751152 CNS-0751152],
the Department of Energy under the SciDAC program
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0513692 IIS-0513692],
([http://www.scidac.org/compsci/SDM.html SDM]
[http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0401498 CCF-0401498],
and
and others; by the Department of Energy under the SciDAC program (SDM, VACET, and UV-CDAT);
[http://www.scidac.org/viz/VACET.html VACET]),
and by IBM Faculty Awards (2005–2008) and a University of Utah Seed Grant.
IBM Faculty Awards (2005 and 2006) and a University of Utah Seed Grant.
 
== Related ==
 
[[BirdVis]] &nbsp;|&nbsp;
[http://www.crowdlabs.org CrowdLabs] &nbsp;|&nbsp;
[[RepeatabilityCentral]] &nbsp;|&nbsp;
[[ProvenanceAnalytics]] &nbsp;|&nbsp;
[[Provenance: potpourri]]

Latest revision as of 22:15, 23 April 2026

VisTrails

VisTrails is an open-source scientific workflow and provenance management system developed at the VIDA Center at New York University. It supports computational science by capturing and managing the complete history of the exploratory process: the workflows, their executions, and the results they produce.

VisTrails is actively developed again. The new version, VisTrailsJL, is a complete reimplementation in Julia that brings modern performance, notebook-based workflow authoring, and native compatibility with existing .vt files. See the GitHub repository to get started.

What's New

After a hiatus since 2018, VisTrails is back. VisTrailsJL (v2.2) is a ground-up reimplementation in Julia that preserves everything that made the original system valuable — comprehensive provenance, visual workflow management, and support for real scientific use cases — while modernizing the foundation:

  • Julia reimplementation — Julia's JIT compilation brings performance suitable for demanding scientific workflows, and its rich ecosystem (DataFrames.jl, DifferentialEquations.jl, Plots.jl) is a natural fit.
  • Notebook-based workflow authoring — Workflows can now be defined directly in Jupyter notebooks using simple #| directives, with no GUI required.
  • Full .vt compatibility — Existing workflows created with the Python version can be loaded, replayed, and visualized without modification.
  • Git-native version control — Standard git replaces the custom versioning infrastructure for workflow history.
  • Python interoperability — Existing Python modules and libraries remain accessible via PyCall.jl.

The original Python codebase (v2.2) is preserved in the repository for reference and compatibility testing.

Quick links
GitHub (VisTrailsJL)  |  Documentation  |  Publications, Tutorials and Presentations  |  Mailing Lists

Core Features

Provenance and Workflow History

A defining feature of VisTrails is its comprehensive provenance infrastructure. Unlike systems that track only the current state of a workflow, VisTrails maintains the full history of every step taken during an exploratory analysis — what was tried, what was changed, and what results each version produced. This enables users to:

  • Navigate and compare workflow versions in an intuitive tree interface
  • Undo changes without losing intermediate results
  • Visually diff two workflows and their outputs side by side
  • Reproduce any prior result exactly, long after it was first computed

Provenance information is stored as XML or in a relational database (Python version), or managed via standard git (Julia version).

Building and Running Workflows

VisTrails supports workflows expressed as dataflows, with support for functional loops and conditional branching. Workflows can be run interactively through the GUI or in batch mode via a server. The system is designed to connect loosely coupled resources — specialized libraries, web services, and grid computing infrastructure.

In VisTrailsJL, workflows can also be defined declaratively in Jupyter notebooks:

#| workflow: my_analysis

#| module-id: input
#| module-type: basic:Integer
#| params:
#|   - value: 42

#| module-id: process
#| module-type: mypackage:Transform
#| inputs:
#|   - value: input.value

#| execute

Packages and modules are easy to add. The JuliaSource and PythonSource module types allow custom code to be embedded directly in a workflow without creating a full package.

Publishing Reproducible Results

VisTrails 2.0 introduced support for embedding reproducible results directly in LaTeX/PDF documents via a companion LaTeX package. A figure in a compiled PDF becomes active: clicking it invokes VisTrails and re-executes the workflow that produced it on any machine with the software installed.

\usepackage{vistrails}

\begin{figure}
\begin{center}
\subfigure[a=0.9]{\vistrail[filename=alps.vt, version=2, pdf]{width=8cm}}
\caption{Clicking this figure retrieves and re-runs the workflow that produced it.}
\end{center}
\end{figure}

Querying and Refining Workflows

Users can construct expressive queries over a collection of workflows using the same interface used to build them. An analogy mechanism allows complex modifications to be applied to one workflow by example from another, without manually editing workflow specifications — useful when a family of related analyses needs to evolve together.

Visualizing and Comparing Results

VisTrails provides a spreadsheet view for comparing the results of multiple workflows or multiple parameterizations of the same workflow side by side. The visual diff interface highlights structural differences between two workflow versions. Workflows and their version trees can be rendered as SVG (VisTrailsJL) or displayed on large-format display walls.

Getting Started

VisTrailsJL (Julia — current)

# Clone the repository
git clone https://github.com/VIDA-NYU/VisTrailsJL.git
cd VisTrailsJL/julia

# Install dependencies
julia --project=. -e 'using Pkg; Pkg.instantiate()'

# Load and render an existing workflow
julia --project=. -e '
using VisTrailsJL
vt = load_vistrail("../examples/gcd.vt")
workflow = get_pipeline(vt)
render_pipeline_svg(workflow, "workflow.svg")
'

See the Quickstart Guide for a full walkthrough.

Python VisTrails (legacy reference)

The original Python version (v2.2, requires Python 2 / PyQt4) is preserved in the repository for reference and for loading existing .vt files in legacy environments.

# GUI mode
python vistrails/run.py

# Batch mode
python vistrails/run.py --batch [options]

Projects Using VisTrails

VisTrails has supported real scientific workflows across a wide range of domains. The following projects reflect the breadth of communities that have relied on the system.

USGS Habitat Modeling NASA Climate Data Analysis DOE CDAT
Usgs.png
Nasa.png
Cdat.png
ALPS Simulations NSF STC CMOP NSF CDI Wildfire
Alps-shot.png
Cmop-ss.png
Wildfire.png
NSF DataONE-EVA
Eva.png

See all projects using VisTrails

VisTrails in Teaching

VisTrails has been used as a teaching tool in courses on Scientific Visualization and Digital Media. Its provenance infrastructure makes it particularly effective in educational settings, where capturing and comparing student workflows provides rich feedback for instructors and learners alike.

Our paper describing a provenance-rich teaching methodology received the Best Paper Award at Eurographics 2010 Education.

More on VisTrails and Teaching

System Documentation

To report bugs or request features, please use the issue tracker.

For questions not covered by the documentation, post to the mailing list.

Citing VisTrails

If you use VisTrails or VisTrailsJL in your research, please cite the relevant work:

Original VisTrails system:

@inproceedings{vistrails2006,
  title     = {VisTrails: visualization meets data management},
  author    = {Callahan, Steven P and Freire, Juliana and Scheidegger,
               Carlos E and Silva, Cl{\'a}udio T and Vo, Huy T},
  booktitle = {Proceedings of the 2006 ACM SIGMOD International Conference
               on Management of Data},
  pages     = {745--747},
  year      = {2006},
  doi       = {10.1145/1142473.1142574}
}

VisTrailsJL (Julia reimplementation):

@software{vistrailsjl2025,
  title  = {VisTrailsJL: A Julia Implementation of VisTrails},
  author = {Silva, Claudio T},
  year   = {2025},
  url    = {https://github.com/VIDA-NYU/VisTrailsJL}
}

Full publication list

People

People

Sponsors

This work has been supported in part by the National Science Foundation under grants IIS-0905385, IIS-0844572, IIS CAREER-0746500, CNS-0751152, IIS-0513692, CCF-0401498, and others; by the Department of Energy under the SciDAC program (SDM, VACET, and UV-CDAT); and by IBM Faculty Awards (2005–2008) and a University of Utah Seed Grant.

Related

BirdVis  |  CrowdLabs  |  RepeatabilityCentral  |  ProvenanceAnalytics  |  Provenance: potpourri