--- title: "Post-Processed Data" slug: "post-processed-data" description: "Post-processed datasets sit in datasets_proc/date-time, holding anchors/, artifacts/, cam/, info/, logs/, maps/, pano/, pointclouds/ and wifi/. Also dataset.json, pointcloud.ply, sensor_frame.xml, qualitymap.png and workstation.cer." tags: ["Post-Processed Datasets", "Calibrated Point Clouds", "Panorama Imagery"] updated: 2026-03-09T07:22:11Z published: 2026-03-09T07:22:11Z canonical: "knowledge.navvis.com/post-processed-data" --- > ## Documentation Index > Fetch the complete documentation index at: https://knowledge.navvis.com/llms.txt > Use this file to discover all available pages before exploring further. # Post-Processed Data Post-processed datasets contain everything produced after raw mapping is turned into usable outputs: calibrated point clouds, panorama imagery, geo-registration maps, logs, and quality artifacts. This page explains how that data is structured in the datasets_proc/ folder and what each key file or directory represents, so you can quickly find the information you need for analysis, troubleshooting, or integration. During post-processing (see also [Post-Processing using SiteMaker](/v1/docs/running-post-processing-in-sitemaker)), the recorded sensor data is used to generate the Point cloud and/or panorama images. Artifacts generated during mapping are also re-computed with all algorithms tuned for higher resolution and higher accuracy. - For each Post-processed dataset, a corresponding folder is created named *datasets_proc/*. - A Post-processed dataset contains the following folders and files: | **File/Directory** | **Description** | | --- | --- | | `anchors/` | Contains various `<anchors>.txt` files as well as an `origin.json` file. These files provide control point information and indicate the state and success of anchor usage during different steps of post-processing with anchors. See also [Dataset Control Point Info File](/v1/docs/dataset-control-points-info-file). Additional log files (`anchors_alignment.log` `anchors_verification.log `and `anchors.log`) that are generated if you process your data using measured control points are also saved in this folder (see [Control Point Error Log Files](/v1/docs/control-point-error-log-files)). | | `artifacts/` | Contains generated output such as a log of [bluetooth beacon signals](/v1/docs/beacons) received (`bluetooth_beacons.csv`) and [trajectory data](/v1/docs/mapping-path) (`trace.csv` and `trajectory.bag`). | | `cam/` | Contains captured images. | | `cam/info.list` | Lists the `*info.json` files created in the `info/` folder. | | `info/*.json` | An `*info.json` file (see [Capture Location Info Files](/v1/docs/capture-location-info-files)) is created for each successful capture event (a panorama was created successfully). | | `logs/` | See [Log files](/v1/docs/logs). | | `maps/` | Contains 2D geo-registration maps (see [2D Geo-Registration Maps](/v1/docs/2d-geo-registration-maps)) for the processed data in different resolutions. YAML files containing the position and the orientation of each 2D geo-registration map are also provided. This ensures correct map alignment in IndoorViewer. Quality maps (see [Quality Map](/v1/docs/quality-map)) in different resolutions are also provided. This folder also contains 2D x-ray maps (see [2D X-Ray Maps](/v1/docs/2d-x-ray-maps)). | | `pano/` | Contains [panorama images](/v1/docs/panorama-images). | | `pano/info.list` | List of metadata (`*info.json`) files for each successful capture event (a panorama was created successfully). | | `pano/pano-poses.csv` | [Pose information for each panorama](/v1/docs/panorama-image-poses) relative to its dataset | | `pano_depth/` | Internal use | | `pointclouds/` | Internal use | | `pointclouds/poointcloud-raw.ply` | Raw point cloud files that are generated when processing **without** measured control points that are filtered to remove outliers but still contain the sharp edges and corners recorded by the laser scanners. | | `pointclouds/<dataset-name>-raw-registered.ply` | Raw point cloud files that are generated when processing **with** measured control points that are filtered to remove outliers but still contain the sharp edges and corners recorded by the laser scanners. | | `wifi/` | See [Captured WiFi data](/v1/docs/wifi-data). | | `dataset.json` | Contains the dataset name entered by the operator, the version layout (dataset identifier), and statistics such as the mapped area and mapping duration. | | `pointcloud.ply` | Used for filtered point clouds. See [Point Cloud](/v1/docs/point-cloud). | | `<datasetname>-registered.ply` | Contains the filtered and registered point cloud and is generated when the options […] are used. See [Point Cloud](/v1/docs/point-cloud). | | `sensor_frame.xml` | See [Calibration file](/v1/docs/calibration-parameters). | | `sensor_frame.xml.sig` | Digital signature of the calibration file | | `qualitymap.png` | Quality map for the processed dataset | | `workstation.cer` | Security certificate for your processing machine | A Point Cloud is as a collection of data points in space that typically represent the external surface of an object or environment. Point clouds are used in various applications, including 3D scanning and mapping, and can be visualized and manipulated using Navvis IVION. You can perform actions such as panning, orbiting, cleaning up noise, cropping, and downloading data in formats like .e57 or .ply. The resolution of point clouds processed with NavVis Software achieves a minimum detail of 5mm, indicating the precision of the spatial data points. Aggregate of data generated from a recorded dataset by running a post-processing task.