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Is there a way to analyze TimeSeries-Data with irregular timeSamplingInterval?

ph1
3-Visitor
3-Visitor

Is there a way to analyze TimeSeries-Data with irregular timeSamplingInterval?

When uploading Data Sets to Analytics Builder I need to add a meta data file which defines the different fields in the csv-file containing the data.

 

For the column containing the Time Stamp I need to define a parameter called "timeSamplingInterval" which defines how much time passes between each measurement.

 

However in my data set, the time intervals often vary between different measurements and the file upload gets rejected because of this, as shown in the attached png.

Is there some way to deal with this or an established workaround solution?
Should I try to use another module/extension to deal with TimeSeries-Data with irregular intervals?

 

 

1 ACCEPTED SOLUTION

Accepted Solutions

Hello,

 

My team has recently had a similar problem and we found a workaround solution. In the meta data file we set the time stamp to be an informational field (dataType: STRING and opType: INFORMATIONAL). We then created an additional field called timecount which is our time series field (dataType: DOUBLE, opType: TEMPORAL and timeSamplingInterval: 10 000).

 

The timecount field is essentially just and integer field counting the number of rows using a constant value. in Our case, we used a 10 second interval. 10 seconds is roughly the average time it took for us to gather a data sample.

 

I have attached snippets of our meta data file and our data.

Please see the following community post as well.

https://community.ptc.com/t5/IoT-Tech-Tips/How-to-work-with-ordinal-and-categorical-data-in-ThingWorx/m-p/542406

 

Hope this helps.

 

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4 REPLIES 4
jgreiner
12-Amethyst
(To:ph1)

Hello,

 

Timeseries in ThingWorx Analytics typically requires a regular timeSamplingInterval although a little variability is accepted. 

 

For the timeSamplingInterval you could try using the average interval that the data inputs are coming in at as long as there is not too much variability.

 

If there is a good amount of variability between each input, you could create a separate column called count and increment it to increase by 1 for each column, and then set the the timeSamplingInterval to 1.  

 

Let me know if you have any other questions or concerns.

 

Warm Regards,

 

John

Hello,

 

My team has recently had a similar problem and we found a workaround solution. In the meta data file we set the time stamp to be an informational field (dataType: STRING and opType: INFORMATIONAL). We then created an additional field called timecount which is our time series field (dataType: DOUBLE, opType: TEMPORAL and timeSamplingInterval: 10 000).

 

The timecount field is essentially just and integer field counting the number of rows using a constant value. in Our case, we used a 10 second interval. 10 seconds is roughly the average time it took for us to gather a data sample.

 

I have attached snippets of our meta data file and our data.

Please see the following community post as well.

https://community.ptc.com/t5/IoT-Tech-Tips/How-to-work-with-ordinal-and-categorical-data-in-ThingWorx/m-p/542406

 

Hope this helps.

 

Thanks for the answer.

Does the "ttf"-column between the Timetamp and TimeCount-fields have any meaning related to the issue?

Hi 

 

No it doesn't. It is just a column specific to my data. The screenshots I attached was of a project I am working on. It is not related.

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