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Exploring and querying data
Data explorers provide an interface for inspecting information stored in NOOSAdmin. Users can browse paginated table views, combine field filters and follow links between related tables. Data administrators can also create customised explorers that bring together selected table elements and presentation options.
Exploration is useful when the question changes as the user investigates. Someone might begin with a collection of measurements, narrow the records to a particular piece of equipment and then examine the associated equipment information.
Automatic table views
NOOSAdmin provides automatic explorers for browsing data in paginated table views. Pagination presents records across successive pages, allowing users to inspect a collection in manageable portions.
The usefulness of a table view begins with the underlying model. Clear field names and meaningful relationships help readers understand what each record represents. In the equipment example, an equipment reference, observation time, measurement type, value and unit give a reading its context.
An explorer presents the application's stored information. Any calculated value that the application needs to inspect should be supplied through the relevant data or processing arrangement.
Following related records
Explorers support cross-linked tables. Relationships allow users to move between connected information, such as equipment records and their associated measurements.
This is useful when an individual value needs context. A reading may be meaningful only when the user also knows which asset it belongs to or what type of measurement it represents. Designing those relationships in the model makes the information easier to navigate.
The particular relationships available depend on the application's table definitions. A customised explorer can draw on selected table elements to support a more focused task.
Combining filters and queries
Users can filter and query data using combinations of fields. This supports narrowing a collection according to several relevant criteria instead of examining every record.
For example, an analyst might need measurements associated with a particular equipment record and a particular measurement type. Combining those criteria creates a more focused set of information to inspect. The exact filter operators and controls depend on the configured interface.
A useful investigation starts with a clear question: which records are relevant, and which field values distinguish them? As the question develops, the user can adjust the selection and follow related information.
Customised explorers
Data administrators can create customised explorers by combining different table elements and presentation options. This supports views organised around an audience's work.
An equipment-focused explorer could emphasise asset information and relevant measurements. An analysis-focused explorer could centre on stored model results and their connection to equipment. These are illustrative designs, with the available content determined by the application model and explorer configuration.
The configuration should make the information needed for the task easy to identify. It should also be considered alongside the entity permissions of the intended user groups.
Example: investigating a set of readings
In an illustrative monitoring application, an analyst wants to inspect readings for one piece of equipment. They use an explorer to narrow the measurement records by equipment and measurement type, then examine the resulting values and observation times.
Where the model provides a relationship, the analyst can follow the equipment reference for additional context. If analysis outputs are stored in a related table, an explorer can also support inspecting those result records.
This workflow supports investigation through the stored data. If the same selection becomes a recurring information need for a wider audience, a dashboard with a predefined query may provide a useful presentation.