DATA FLAGS AND LOCKING*

Classify and colour your data with DataSight’s new data flagging feature. Select from preconfigured flags or create your own tailored flags to identify suspect data, apply quality coding and lock or archive data for security.

For example, data imported from a data logger can be flagged as ‘RAW’ on import, flagged as ‘VERIFIED’ following user review and verification, then flagged as ‘ARCHIVE’ data by the DataSight administrator to prevent further editing.

Flag settings can also be included in DataSight’s powerful data filtering, allowing you to quickly access and view data with a particular flag.

The Data Quality component within DataSight allows you to quickly and visually assign flags to data points using the graphical data quality interface. In the image to the right, for example, irregular temperature readings are quickly identified and flagged as ‘poor quality’ or ‘bad’ data.

Using Application Flags, data can be automatically flagged during the Import process and while completing calculations on existing data. The ability to flag ‘Archive’ data also flags it as Read-Only, preventing further editing of the data by users.

TASK SCHEDULING

In addition to scheduled reporting, datasheets and graphs, DataSight’s scheduler now allows users to:

• Schedule conversions;
• Email reports, graphs and datasheets; and
• Log scheduled tasks.

INTERPOLATIONS*

DataSight’s new Interpolations feature provides users with the ability to construct new data points within the range of a discrete set of known data points. This graphical curve fitting feature expands on DataSight’s existing calculations and analysis capability, allowing simple linear spline interpolation along with cubic spline and Akima spline to perform interpolation operations with ease.

CONVERSION FUNCTIONS

Three new functions have been added to the conversions module:

• Previous Value (PVAL) – returns the previous value.
• Next Value (NVAL) – returns the next value.
• Rate of Change (RofC) – calculate the progressive rate of change for points in a time series.

These functions are useful for identifying changes in data within a dataset and implementing warning or alarm systems to alert users to specific data. For example, the Rate of Change function can be applied to incoming water level data in order to detect a greater (or less) than expected rate of change in the water level.

MAP PRINTING

Right-click on a Google map to directly access printing options, allowing you to print maps and map information.