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As per the 3D Config feature, it should be good to have a Canvas Config option to configure the colouring for a quick highlight of the contextualization results in a Canvas for P&ID or any “plan” documents like isometrics loaded in a Canvas.In the configuration option we should be able to select attributes/data linked to the OCR captures, then in Canvas we should have a button to select and highlight all the OCR captures contextualized to PI-Tags, 3D tags, WOrkorders, SECE equipments…This option is of importance, it will avoid to check one by one each equipment in a P&ID, it will accelerate the completion of the contextualizations workflows, but not only… it’s also of importance for operations when preparing an intervention.
Due to the limit on the number or Views/revisions, we need to deprecate and delete old revisions on a regular basis (in periods with heavy data model development). For Atlas agents and Canvas’ we can find the View versions via the API, allowing us to identify users depending on models that are deprecated. However, with Charts I cannot find any way of programmatically finding this.Is there a hidden API somewhere that allows me to inspect what the different Charts are relying on? If not,. this is an important functionality for governance of data models and needs to be added.
When creating calculations in CHARTS it would be VERY useful to have logic functions (AND, OR, NOT, XOR) which allow multiple (>6 for AND and OR) boolean inputs (TRUE/FALSE) and a single output.This would be really useful for tracking events which may be dependent on multiple conditions being active (or not active).
If you in Charts add a timeseries that is contextualised to a CogniteAsset, you will get the “P&ID” link icon. By clicking on it you will enter search mode for that specific asset, showing the File links as default. This is a nice workaround for a “Find related data”, also allowing you to add CogniteActivities.The instance is shown as a CogniteAsset, and it obviously use the inspection endpoint since you are allowed to change between different views for this instance. However, it doesn’t show the View that is the CogniteAsset extension. The consequence of this is that I’m not able to see neither CogniteFiles nor CogniteActivities as their extension (my CogniteAsset extension has reverse direct relation to the CogniteFile and CogniteActivity extensions). This seriously limits me when filtering on important properties since they only exist in the extension. A workaround is to go directly to “+ Add data → Add time series”, and then select my CogniteAsset extension when I search, but then I have to repeat the search instead of going directly via the “P&ID” link, making it much more cumbersome.
When asking the embedded Atlas AI Agent to eg show the difference between two timeseries, it display both timeseries in a chart inside the Chat window. However, both lines get the same color, and there is no legend, so unless you know the average value for those timeseries you do not know which is which. Also, there is no y-axis, so the only way of knowing the value is to hover over the different lines.Legend and axis would help a lot on the user-friendliness
I need to download the video file in CDF to play it, but will it be possible to play it in CDF Explorer or Industrial Canvas?In particular, I think that the range of data utilization will be greatly expanded if videos taken from smartphones and tablets can be played back on CDF in Infield.
Example: The filter shows options in English, while in the list view they are displayed in Norwegian. For example, the filter shows “Ready”, whereas in the view it shows “Klar”.
Wants the option to print a checklist with selected attributes from InField.
Be able to copy the URL for a given checklist, template, etc. for sharing with a colleague.
Documents that are most important for the technician should be listed first, e.g. P&IDs (XB).
Using Search, when selecting an instance and then choosing the Properties tab, all the populated properties are listed with the key and value in two columns. The key column is apparently a fixed width column (40ish char wide), not possible to manually resize, and it doesn’t resize when the browser window is resized. This becomes a problem when the property key is long, something that may happen when the property is a JSONObject such that the key becomes “nested” Below is an example of how it looks It seems like the UI is able to wrap the line if the key either has a space or a hyphen, but not else (have not tried all characters...) We can of course mitigate this by creating more compact keys, but it would be really helpful if we could resize the column such that our key naming convention do not have to take a 40 character UI limitation into account.
Hello,With the current WITSML extractor configuration, we can only whitelist the mnemonics that we want to extract. Would it be possible to also support a blacklist configuration for mnemonics?In our case, the complete list of mnemonics to extract is not known beforehand, which makes maintaining a whitelist challenging.Thank you.
When listing instances of a view and using the to_pandas method, is there a simple way to use the data types defined on the container properties and use these to cast to similar python data types? Or could this be an option of the python SDK?In the classical CDF data types, this is implemented so that for example a date field and timestamp fields have the correct python data type. The data modelling instances will be either floats or string. It would be very convenient if the underlying container data type can be used so that you do not have to manually cast values in the pandas dataframe.
ContextWe currently run several custom Python extractors built on cognite-extractor-utils. For those, cognite-extractor-utils lets us configure a metrics.cognite block that periodically pushes the extractor's Prometheusmetrics (Counter/Gauge) directly to CDF Time Series — this gives us consistent,queryable observability (row counts, run duration, throughput, failure counts, etc.)across all our extractors, without any extra tooling.ProblemThe PI Extractor and the DB Extractor (official Cognite binaries) already exposePrometheus metrics internally (e.g. pi_extractor_timeseries_states,pi_extractor_stream_iterations, pi_extractor_pi_data_pipe_events,pi_extractor_streamer_data_points, pi_extractor_event_queue_size,pi_extractor_pi_data_loss, pi_extractor_pi_connection_time,pi_extractor_pi_connections, extractor_utils_cdf_datapoints, …), but today they canonly be exposed via a local Prometheus scrape endpoint (metrics.server) or a PushGateway (metrics.push-gateways). There is no equivalent of metrics.cognite to pushthese metrics natively to CDF Time Series, unlike our custom extractors.ImpactWithout native CDF Time Series push, we can't monitor these extractors the same way as our custom ones (no unified dashboarding/alerting in CDF/Grafana). We want to keep CDF as the single source of truth for observability, not add a separate tool just to collect metrics.RequestCould you add support for a metrics.cognite configuration block (or equivalent) in thePI Extractor and DB Extractor, consistent with the one already available viacognite-extractor-utils, so their internal Prometheus metrics can be pushedperiodically to CDF Time Series (external-id prefix, target data set, push interval)?
Today it is possible to specify the unit of a property of a View, enabling unit conversion on consumption (via the API). However, the CDF UI is currently not showing this unit. It means that we either have to create a dedicated “property_UOM”, or we have to add the unit into the @name in the View description. It would be preferable if the UI could show the unit, and also support the unit conversion.
When multiple canvas are created in a company, then we need to get some more meta data on each Canvas to ease the search of the right/relevant Canvas.It could be interesting to get the option to insert a description of the Canvas, potentially the main discipline concerned by the Canvas and the main documents mentioned in the Canvas. So then we can develop AI agents to ease the search for Canvas.
The closest to that solution as for now would be adding a timeseries on the canvas, then you have an option to Open in charts and then choose a new one or existing one. This is too cumbersome.See picture below of suggested solution directly in canvas:
When you add new assets or files in Canvas, the data is added to an area of the Canvas where there are no objects, and the focus moves to that location.While this is great in that it ensures the added data doesn’t interfere with the existing Canvas layout, the following sequence of events occurs every time, which can be cumbersome.① Add new data② The data is added to an area without any objects, and the screen focus automatically shifts there (since the location where the data is added is usually quite far from the main screen, the focus also shifts significantly away from the main screen)③ Move the added data to where you actually want to place it (because the focus from step ② is significantly away from the main screen, you have to move the data a long way to position it, which is quite a hassle)Therefore, is there a way to add data to a location that makes step ③ as easy as possible for the user?
When creating a pdf export of a Canvas it appears that hidden layers in the original document become visible after the export process. I have an example of a “Preliminary” watermark, not visible in Canvas becoming visible in the export. Can the pdf export be limited to the visible layer only.
Currently data modelling in CDF only support “soft deletes”, which in day to day operations works well and support the necessary sync features. However we have scenarios where we need to delete vast amounts of instances, ideally in a very short timeframe.During testing we sometimes need to delete and recreate a data model We are currently migrating data models and have two living in parallel for a time, eventually we will delete the old one, which has more than 50 million instances, with the current limit of 10 million soft deletes this would 15 days due to soft delete retention period. Cleanup of old test data Decommissioning of data models (or oil rigs for that matter)This is an ongoing issue in one of test environments where we have a need to do a full wipe of all instances within the CDF project.The feature I am looking for is a way to skip the soft delete default, and simply do a hard delete right away. In the scenarios I’ve listed the features of soft deletes are not needed as we do planned and coordinated complete deletes rather than a regular update from a source system. This is the first time we are facing this issue, but we see that this will be a recurring problem in the time to come for us. Markus PettersenAker BP - Data Platform Architect
Views that extends CogniteActivity can be included as an object in Charts, shown as a colored overlay in the timeseries. However, it seems it is a forced filter on assets that are included in the Chart. I can remove the default startTime and endTime filter, but not the asset filter. It is a very likely scenario that I want to add a notification or workorder for an asset that doesn’t contain the timeseries I’m interested in(sensor is upstream). It also might be the case that the asset with the notification/workorder do not have a timeseries at all (it resides further down in the hierarchy).It can be helpful to add a preconfigured asset filter based on the assets indirectly included via the timeseries, but it is an absolute requirement that I can remove that filter. Right now, if the asset with the notification do not have any timeseries I have not found a workaround allowing me to add the notifications I want.
The “Scheduled” feature, currently in beta, has proven to be user-friendly and well-received.I believe this feature is currently available only to users with both “Checklist admin” and “Template admin” roles, but would it be possible to make it available exclusively to “Checklist admins”?In our company, we assign permissions based on the following roles, and it is often the people who actually perform the inspections (i.e., “Checklist admins”) who issue checklists from the “Scheduled” tab.Therefore, making this feature available to “Checklist admins” as well would make it even easier to use.Template admin → People who edit templates. Only a few people.Checklist admin → People who actually perform inspections. All InField users.This may differ from the original design intent of this feature, but I would appreciate it if you could consider this as one suggestion.
Currently, when attempting to schedule certain functions—such as moving averages—the results may differ from the normal calculation results verified before the scheduled execution.Additionally, the results of scheduled executions vary depending on the execution cycle.A sample is shown in the screenshot.Although I haven’t been able to verify everything, I suspect that similar issues may occur with other functions that set the window size.Users typically assume that scheduled calculations are performing correctly without being aware of these discrepancies, and as things stand now, there is a risk that they may rely on incorrect results. Therefore, I expect that the correct calculation results will be recorded regardless of the schedule settings.
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