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Dashboards and information pages
Dashboards present queried data in NOOSAdmin. They support recurring information needs, such as consulting equipment summaries or reviewing stored analysis results. Data administrators can create dashboards and place them on pages available to selected groups.
The query establishes which information is presented. The page gives that presentation a place within the application, and group access determines its intended audience.
Presenting queried information
A dashboard uses queried data as its source. This may include collected records or results written to tables by processors and runners.
For example, a processor could calculate equipment summaries and store them in a summary table. A dashboard can then query that table to present the derived information. An external model's stored results can participate in the same way.
The dashboard's meaning depends on its source data and query. A useful presentation makes clear what the values represent, which equipment or records they concern and what period they describe, where those details are relevant.
Predefined queries and URL parameters
Dashboard queries can be predefined or supplied with parameters through the URL.
A predefined query is useful when a page serves a stable information need. For example, a dashboard could be configured around a particular collection of stored summaries.
URL parameters allow query context to be supplied through the address used to access the presentation. An illustrative use would be to supply an equipment reference so that a dashboard presents information for that asset. The supported parameter names and query behaviour depend on the configuration; the example does not prescribe a URL format.
Query context and access permissions serve separate purposes. A parameter selects relevant information within the configured presentation and should not be treated as an access-control mechanism.
Information pages and groups
Data administrators can create pages containing dashboards and make them available to groups. This allows a team to arrange recurring information around the audiences that need it.
For example, a group responsible for operational review could have a page presenting equipment summaries. An analytical audience could have a page presenting stored model outputs. These pages would draw on the data and queries configured for the application.
When arranging a page, identify the question it should answer and the data needed to answer it. Plan its availability alongside the underlying resource permissions described in Organisations, users and access.
Explorers, dashboards and portals
These features operate at different levels of the user experience.
| Feature | Main purpose | Illustrative use |
|---|---|---|
| Data explorer | Browse records, combine filters and follow related tables. | Investigate measurements associated with an asset. |
| Dashboard | Present queried information for a recurring need. | Consult summaries or stored analysis results. |
| Information page | Provide a location for dashboard content available to groups. | Give an audience a recurring review page. |
| Portal | Organise pages and actions within a branded experience. | Bring summaries, explorers and runner actions together for analysts. |
An application can use all of them. A portal might include a summary dashboard and an explorer for deeper investigation. The portal's organisation is described in Branded portals.
Example: presenting equipment summaries
In an illustrative application, a summary table contains calculated values associated with equipment and a defined period. A data administrator creates a dashboard querying that information and places it on a page for the relevant group.
A second presentation could query the Analysis results table. Clear labels would distinguish the model's returned values from the measured and calculated information used elsewhere in the application.
If the audience needs to investigate individual records, an explorer can provide that complementary view. The dashboard provides the recurring presentation; the underlying collection and computation remain part of the data workflow.