A new data type has been added: Movement path data. This data type enables the representation and analysis of trips following road networks. It allows for detailed street analysis, traffic flow analysis, origin-destination analysis much like the already existing Movement data.

Figure 1. Example movement path data set from INRIX consisting of trips along a road network.

Time series, GeoJSON, and Movement path data now use a multi-scale approach when handling road segment data. If your data set has a property with special meaning Priority Level with values (starting with) a number from 1 to 9 where 1 corresponds to the most important road type (e.g., highways), an automatic multi-scale representation will be generated. The approach favors larger roads (i.e., priority level 1) when zoomed out and smaller roads (e.g., priority level 6 or more) when zoomed in. This enables you to use country-wide road networks in your analysis.

Figure 2. Multi-scale handling of road network data. Left; Only showing the motorways when zoomed out. Right: also showing the smaller roads when zooming in.

Time series, GeoJSON, and Movement path data now enable the analysis of two-way roads. If your data set has a property with special meaning Reverse ID, the platform automatically understands that the road is a two-way road. For instance, if the identifier of a road segment is 2014921_0, then the reverse identifier might be -2014921_0. When configuring the reverse identifier, the platform understands that the road segment needs to be handled (and visualized) as a two-way road.

Figure 3. Handling of two-way roads, with indication of driving direction.

Road networks defined in Time series, GeoJSON, and Movement path data sets now display an arrow pointing in the driving direction when the road is visualized sufficiently widely. This benefits analysis of traffic on bi-directional roads. You can change the width of the visualized road segments using the Size scale slider.

Time series and GeoJSON data sets now use the 'Style by' value as label instead of the shape’s name. This enables faster insight generation and more informative visualization. For instance, when displaying speed on a road segment, the label will now show the (average/min/max/…​) speed in the label. Additional information is now also shown when hovering with the mouse.

Time series and GeoJSON data sets now do not expose the shapes as areas of interest shapes by default. You now have to explicitly configure this. When disabled, you cannot select the shapes as areas on the different analytics pages, for instance to display multiple trends on the Trend Analytics pge. If enabled, you can use the shapes in the data set as before as areas of interest shapes.

Labels for Time series, GeoJSON, and Movement path data sets are now deconflicted (decluttered) for a better visual representation.

Some of the default styling options have changed. Styling by a numeric property now selects the Rainbow colormap by default. Accumulation styling is now also disabled by default. The latter can be enabled to apply a density effect based on the number of records or assets, in addition to the colormap used for styling.

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You can now edit and replace widgets on the dashboard. To modify an existing widget, click on it, make your changes on the page, then select Add as widget…​. Choose REPLACE and select the widget you want to update from the drop-down list. You can also replace a widget with an entirely different one (e.g., switching a visual analytics widget for a trend analytics widget).

Travel Time is now a derived property available in Movement Data sets. It represents the time difference between the end and start of an asset’s journey.

Categorized Trend Analytics now supports the creation of custom categories. In addition to categorizing based on data properties, time periods, or areas, users can now build categories using complex filters.

The Categorized Trend Analytics page now requires defining a Spatial Query Region to limit the search area when computing trends. This ensures that analytics are focused on a specific area of interest, such as a highway intersection or a port terminal, and prevents unintentional use of the entire dataset region.

The Categorized Trend Analytics feature now includes configurable Calculation Modes, offering a distinction between record-based and asset-based calculations.

You can configure a default timezone on the project. This timezone will be used by default on any of the analytics pages when you open that page for the first time.

The platform now supports a new data set type: Point Data. This type includes datasets composed of independent, unrelated measurements, each associated with a specific location. Examples include driving events such as harsh breaking, cornering,…​ For more details about the different types of datasets supported by the platform, please refer to the Different types of data sets article.

You can now use Parquet files in your data sets, whereas previously only CSV files were supported. The Different types of data sets article provides a list of supported file formats for each dataset type.

When defining the structure of a new data set through the wizard, you can now upload an example file and define the different properties from the uploaded file. Read the Auto-detection of the data properties article for more information.

For movement data sets, you can now enable labels for trajectories with icons. This enables you to more easily identify assets such as vessels moving on the map, e.g., showing the vessel’s MMSI identification number. In addition, you will now see a tooltip with all the record properties when moving with the mouse over a trajectory line or the associated icon.

You can now specify a start and/or end time on the origin-destination analytics page.

Widgets for dwell time and trend analytics now are sized responsively on the dashboard. Also various improvements were made to the categorized dwell time charts, including addition of titles, time ranges, and a legend consistent with the other charts.

All chart data can now be downloaded also as Excel files (.xlsx). This has the benefit over CSV files that the data can easily be opened in Excel with proper column layout and character formatting. Right-click on the chart, or on the three dots to find the new download functionality.

The vertical axis (y-axis) of the Visual Analytics timeline charts and the Trend Analytics charts can now be configured to a fixed range, for example, always showing number of assets on a scale from 0 to 1000. Click on the three dots and choose Edit.

You can now create a new data set by initializing it from the settings of an already existing data set. This means that the new data set takes all data (and metadata) properties and all configuration settings.

Performance of Origin-Destination and other route-related computations has been improved. Note also that the Origin-Destination analytics now defaults to "Strict From" and "Strict To".

You can now save and load layer styles on the Visual Analytics page. This enables you to configure styling once and re-use the same styling configuration for a compatible data set. Compatible data sets are data sets with the same data properties.

The advanced filter editor has been extended with improved syntax error highlighting, auto-completion, and adaptive documentation pointers.

You can now define one or more categories on the Trend Analytics page. This enables you to analyze and download trends divided in subgroups, e.g., by a property, or by different areas, or by logical time units. Choose Categorized as the mode on the Trend Analytics page.

You can now choose German, French, Spanish, and Dutch, next to English as the language.

We have added several new tutorials:

There is now a compact view for the projects, data sets, data stores, areas of interest, and background overview pages. You can toggle by clicking on the table icon at the top of the respective pages.