xyzt.ai is a spatio-temporal visual analytics platform to extract insights from data of things or people that move.

This article explains what the platform is and what the main concepts are.

This article explains how you manage the users in your team.

This article explains how you manage your account settings and change your password.

Learn how you can use the REST api to automate or script certain tasks.

Read about the terms and conditions, privacy policy and data agreement you agree with when using our software.

You can also consult the third party licenses of the third party software we use.

Discover the latest updates to the xyzt.ai platform.

Before you can analyze your data, you need to add it to the platform and create a project for it.

In this article, you will learn about the main concepts in this process and their relationships. It provides a high-level overview of what a project, dataset, background layer and area of interest are.

Learn about the different types of data (sets) the platform supports

Learn how to create a new data set or delete an existing one.

Learn how to create a new project or delete an existing one.

Each project contains a number of data sets, background layers and areas of interest.

This article explains how you can add or remove any of those to/from a project.

Learn how to open and activate one of your existing projects, or switch a different project.

Learn how to create a new background layer or delete an existing one.

Learn how to create a new area of interest (AOI) layer or delete an existing one.

Learn the differences between data sets and data stores

Learn how to create a new data store or delete an existing one

Learn how to extract a data set from a data store so that you can analyze it

Uploading movement data to the platform is a multistep process.

This article provides an overview of the different steps involved, and contains links to articles with more details about each step.

Before you can upload your movement data or metadata files, you need to define the structure of those files.

This article provides an overview on how to do that.

During processing, the data is divided into a spatial and temporal grid.

This article explains this in more detail, as well how you can configure the size of this grid.

During processing of trajectory data, successive records can be connected.

This article explains how you can control the connectivity between records.

Data is by default processed into a gridded representation using the configured spatio-temporal grid. Additionally, the processing engine can produce trajectories and/or realtime data representations as well.

This articles describes the properties of each of those representations, together with some example cases where activating these data representations makes sense.

Some records might have missing values for certain properties.

This article explains in more detail the different strategies the platform has to deal with those missing values.

Once the structure of your (meta)data is defined and the processing settings configured, you can start uploading your (meta)data.

Learn what the difference is between data and metadata.

You can define the structure of your (meta)data files by uploading a file defining the data properties.

This article explains the syntax of this file.

When defining the properties of your data, you can let the platform detect which properties are available.

This article explains how to do that.

The xyzt.ai platform calculates the travel time for movement data, and allows to visualize it for example on a histogram. This article explains what that travel time is, and how it is calculated.

Uploading points data to the platform is a multistep process.

This article provides an overview of the different steps involved, and contains links to articles with more details about each step.

Before you can upload your points data files, you need to define the structure of those csv or Parquet files.

This article provides an overview on how to do that.

During processing, the data is divided into a spatial grid.

This article explains this in more detail, as well how you can configure the size of this grid.

Once the structure of your data is defined and the processing settings configured, you can start uploading your data.

You can define the structure of your geometry files and data files by uploading a file defining the data properties.

This article explains the syntax of this file.

Uploading time series data to the platform is a multistep process.

This article provides an overview of the different steps involved, and contains links to articles with more details about each step.

Before you can upload your time series files, you need to define the structure of those files.

This article provides an overview on how to do that.

Once the structure of your geometry and measurement data files is defined, you can start uploading your GeoJSON and CSV files.

You can define the structure of your geometry files and data files by uploading a file defining the data properties.

This article explains the syntax of this file.

An introduction and overview of the most important features and UI elements of the visual analytics page.

This article describes all the ways you can create and edit spatial filters on the visual analytics page.

This article describes all the ways you can create and edit temporal filters on the visual analytics page.

This article describes all the ways you can create and edit filters based on the data attributes on the visual analytics page.

This article describes how you can adjust the colors on the spatial map.

Cheat-sheet to remember which functionality is located where on the visual analytics page.

Learn how to start a visual side-by-side comparison.

Learn how to open and customize the tabular view on the data

This article explains how timezones affect your filters, and illustrates this with some use cases.

When creating a data set, you can request to calculate trajectories and realtime data representations.

This article explains how to show those on the visual analytics page.

This article how you can draw your own shapes for filtering and analysis and how to manage the resulting Areas of Interest layers.

This article explains how you can hide/show parts of the visual analytics page, or move panels to a different location

This article explains how you can focus on a widget in the visual analytics page data distribution panel

An introduction and overview of the most important features and UI elements of the trend analytics page.

Cheat-sheet to remember which functionality is located where on the trend analytics page.

Cheat-sheet to remember which functionality is located where on the categorized trend analytics page.

This article explains how timezones affect your filters and selected time ranges, and illustrates this with a few use-cases.

This article provides more details on how the trend analytics results are calculated

An introduction and overview of the most important features and UI elements of the distribution analytics page.

Cheat-sheet to remember which functionality is located where on the distribution analytics page.

This article explains how timezones affect your filters and selected time ranges, and illustrates this with a few use-cases.

This article provides more details on how the distribution analytics results are calculated

An introduction and overview of the most important features and UI elements of the origin-destination page.

Cheat-sheet to remember which functionality is located where on the origin-destination page.

An introduction and overview of the most important features and UI elements of dwell-time page.

Cheat-sheet to remember which functionality is located where on the dwell-time page.

This article describes how you can filter your data using the query language

This article contains examples of different asset route filters

This article contains examples of commonly occurring queries that can be implemented using the advanced filters.

This article describes the syntax for the query language

This article describes how the platform selects, for movement data sets, which resolution level to evaluate in a filter pipeline, influencing the accuracy and performance of the filtering process.

Learn about the most important concepts when you want to save and share your analysis.

This article introduces the concept of bookmarks, links, and dashboards.

Learn how to create a new bookmark or link.

Cheat-sheet to remember which functionality is located where on the dashboard page.

Learn how to delete a bookmark or link.