Data Types, Examples, Collaborators

The data types below are examples from which testing and tutorials can draw. Please add more data types and examples as you find them. And try finding software that will let you open and visualize the data, whether in VR or otherwise. Then document it, at least in your journal.

For an abbreviated list of common data types, a brief definition of each type, and recommended/feasible software to use with each type, please see the Software Recommendations by Data Type page.

Please note: many of the following files are very large (we're talking up to around a hundred MB for some of these)! Additionally, this page is a continual work in progress. The categories of data are not exhaustive and are listed in no partincular order, so be prepared for the page to be somewhat messy.

Scalar Volume Data

Description: 3D array of data values where each point corresponds to a single value

Data with Collaborators:

Data without Collaborators:

2D Image Data

Description: 2D array of data values that can be reduced to an RGB image before viewing or interactively during viewing.

Data without Collaborators

2D Vector Field or Flow Data

Description: A magnitude and direction at each point in a plane. Sometimes such vector fields can represent 2D fluid flow, but they can be other things, as well. Can be time-varying.

3D Vector Field or Flow Data

Description: A magnitude and direction at each more in 3D space. Can be 3D flow. Can be time-varying.

Data with Collaborators

Data without Collaborators

Point Cloud Data

Description: data that represents a collection of points in 2D or 3D space.

File Types:

  • las files: Lidar data comes comes in many forms, however, las files are one of the most popular Lidar data formats. An las file is a binary file which contains point cloud data, stored as X, Y, Z coordinates, and a header which contains file metadata, RGB information, GIS information, and many other optional fields. For more detailed information on las files, see the official las specification.

Data with Collaborators:

Data without Collaborators:

Point Cloud Visualization Software:

Point Cloud Processing Software:

Comparisons:

Tutorials:

Papers:


Created by Ross Briden and Ronald Baker; (T) signifies whether a particular software package has been tested; ($) signifies license required.

Planetary Geology Imaging Data

Description: This might be an amalgam of different data types, including collections of stars, collections of galaxies, outward-looking imagery (as from a telescope), or inward looking imagery (as from a satellite of a planet). Some such data is 2D imaging data, but with a particular underlying space, e.g., Earth, the moon, or Mars.

Data without Collaborators

  • NASA Global Imagery Browser Services (GIBS):

    • GIBS is a database of satellite imagery data collected by NASA JPL; the database supports an extensive REST API, however, it can be somewhat complicated to use.

    • GIBS returns satellite data in the form of tiles or maps (in Mercator projection)

  • NASA Earthdata

    • Earthdata is a massive database of atmospheric, land, and ocean data operated by NASA

  • OpenSpace data -- OpenSpace software is listed below as a way to look at many different kinds of data from NASA missions. But it has been somewhat challenging to get to work in the YURT, so it might be worth exploring other software tools for visualizign and interacting with those types of data.

Software:

  • OpenSpace software views some kinds of data of these types, and it has the potential to generalize to more. It almost runs in the Yurt and does run on desktops and HMD's.

CLARITY Imaging Data

Description: CLARITY imaging is a relatively new brain imaging technique which utilizes chemical compounds to visualize brain anatomy with vivid accuracy. CLARITY imaging data is typically represented as a stack of 2D images, which means that CLARITY data can be easily processed by Paraview and other software!

Data without Collaborators:

Software:

  • Paraview (T)

  • Matlab - in particular, Matlab has built-in libraries to visualize volume data, such as CLARITY imaging data.

  • Ipyvolume

Tutorials:

  • Visualizing CLARITY imaging data in Paraview.

Papers:

  • A technical description of CLARITY imaging.

  • Stanford provides a database of journal articles which utilize CLARITY imaging.

Similar to:

  • MRI Brain Imaging

  • CT Brain imaging


Created by Ross Briden; (T) signifies whether a particular software package has been tested.

MRI Imaging Data

Description: MRI imaging data comes in many forms, often depending on the type of MRI machine utilized when scanning a patient. Two of the most common MRI data formats are NIfTi and DICOM. Luckily, most MRI processing software can easily convert between these two formats, so we will focus on visualizing and processing only NIfTi files. For an in-depth comparison between NIfTi and DICOM, see Medical Imaging Formats.

Data:

  • Brain Tumor Segmentation Challenge (BRATS) - BRATS is a comprehensive MRI brain tumor data set comprised of 243 MRI scans, expertly labeled based on tumor pathology.

  • Alzheimer's Disease Neuroimaging Initiative (ADNI) - ADNI contains a collection of over 3000 MRI scans of Alzheimer's patients, captured over several years and with varying MRI scanners.

  • VR Brain Tumor Surgery - Robert Gilbert ***insert data

  • Note that both the BRATS and ADNI data sets are not public and must be requested.

Software:

Papers:

Similar to:

  • CLARITY Brain Imaging

  • CT Brain imaging


Created by Ross Briden; (T) signifies whether a particular software package has been tested.

Network Data

Data without Collaborators

Polygonal Model Data

Description: 3D data stored as polygonal meshes

Found in many 3D file extensions that hold 3d data points: OBJ, DAE, FBX, etc

Programs that use and view polygonal model data that could be YURT usable:

  • Unity, Blender, Unreal, Paraview

Unlikely to be YURT usable:

  • Maya, Adobe Dimension

Data without Collaborators

Time Series Data

Description: Series of data points indexed by time.

Data with Collaborators

Data without Collaborators

  • Human heart rate data - MIT

Genomics Data

Description: Data that captures various genetic information such as variances in genome sequences, DNA sequences, and other genetics information

Data without Collaborators

RGB-D

Description: Output from cameras with proximity sensors contain an extra channel for depth. Its value ranges from 0-255 just like color. It is often visualized alone as grayscale.

Example

MIDI Data

Description: MIDI (Musical Instrument Digital Interface) data allows musical instruments and other hardware to communicate with each other. MIDI holds information on notes and how they are played (for example note on, velocity, modulation, note duration, note off, etc.). In this form, MIDI attemps to digitally communicate the features of a musical performance.

MIDI visualization in Unity - Packages, Assets, and Helpful Libraries: