Is data open to all?


I hope this finds everyone well. I’m a new hire at my firm, and am trying to understand the UK’s heat pump ecosystem/environment.

Is the data collected by OEM/emoncms open to all for usage/analytics?

Thank you so much for the help,


I’m sorry to sound a bit suspicious, Sam, but is your question driven by commercial considerations?

We welcome everyone who wishes to learn or share their experience, but are understandably wary of new users who might be motivated by personal gain.

It would help if you could provide us with a bit more of your background and the context of your query.

Best regards,
Sarah (Moderator)

Sorry Sarah! I’m not super sure what you mean…I started at my company last week and have come from a totally different industry, so was just trying to learn about the heat pump world and what data is/isn’t available around the devices, home energy, etc. I guess it’s accurate to say we’re a commercial organisation! Our mission is to decarbonise home heating by getting more heat pumps into consumer homes, and I’m a bit of a data nerd so my first instinct was to generate a whole bunch of charts and analyses to understand the market and the tech!

Sorry if I’ve made a faux pas!!

The majority of this data is private and not shared, but some of it has been made publicly available at specifically so people can see how well heat pumps perform in various different locations and property types. Some analysis and charts are already available via the menu in top-right corner.

What aspect of the data are you most interested in?

As for direct access to the underlying data, we’d have to ask @TrystanLea and @glyn.hudson.

Hey Tim

Thanks for your reply! I don’t know! You don’t know what you don’t know, you know? Given no restrictions I’d set up a daily grab of public data, start compiling it and see what interesting came out of it! Top of mind, it would be interesting to see how standard performance was, if there were any commonalities across the outliers, if I could get an estimate on operational costs at different energy supplier price points, if average or outlier performance across all installs was changing over time, etc etc

I don’t know haha, you work in data long enough and you enjoy just answering questions. I’ve seen the charts at the site you mention, thank you for the link - they’re why I wondered if there was a feed I could tap into :slight_smile:

Hello @Sam_Fornax

The table summary on HeatpumpMonitor is populated from this api: We haven’t documented the api’s yet as we’ve been focusing our efforts on other development for now.

We actually need to define the licence for the data being shared on and we will get back to you on this shortly. From our perspective we would welcome help analysing the data but wish to see results of this analysis and associated analysis methods shared publicly as a way of giving back to contributors who have taken the time and expense to monitor their systems.


PS: Thanks for asking this question @Sam_Fornax do you think you could be open about the firm that you are working for and how you would like to use the data? or how you would see this data being useful for your firm? could you contribute the findings of your analysis and methods with the community as a way of giving back here?

Hey Trystan - I work for!

Honestly a lot of the motivation is just to understand how to serve the market better. That includes understanding how to help our installers visualise what a good result looks like, and ensuring that our customers get the right setup. That’s probably the first thread. The second thread is general tracking and understanding, with some of my top-of-head ideas from my post above heading the list of questions I’d love to investigate.

I should stress I’ve literally only started on Monday so it’s very early stages. But broadly of course I’d expect to be open and collaborative with the community. Anything sensitive that involves our commercial data would probably have to stay internal, but if we were just transforming or aggregating OEM data to understand wider trends and outliers, and that analysis was all based on this community’s data, I think it’s an extremely fair request to have it shared back with the community after it’s created!

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Thanks Sam

that sounds great and exactly the kind of thing we want HeatpumpMonitor to be used for.

Perfect! that’s good to hear. is there to contribute to the public conversation and both customer and installer learning around this technology and so if you and Fornax are happy to be part of that, that’s what we are after really!

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Sam - If you want aggregate data for the whole year (i.e. for SCOP), have a look at - however, pay attention to the *_data_length (seconds) and quality_* (%) fields and filter out systems that are incomplete.

You may need to filter out outliers due to systems without MID meters or have been flagged with data errors. I’m not sure there’s feed for the system details, unless Trystan knows?

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Thank you Tim!

That’s a big old schema - is there a data dictionary anywhere on OEM’s site to help me understand what I’m looking at?

Unfortunately not, but you should be able to figure it out from the names.

Here are the main prefixes:

  • space_ is for space heating*
  • water_ is for domestic hot water*
  • combined_ is for both - all systems should have this at least
  • running_ excludes the idle period, i.e. only when consumed power > 100W
  • quality_ is the percentage of the time period with data

* Note: not all systems separate out space vs. water heating.

Then there’s the metrics that are collected:

  • cooling_kwh - energy of provided cooling, usually during defrosts
  • cop - Coefficient Of Performance
  • data_length - how many seconds of between first and last reading
  • elec_kwh - total electrical energy consumed
  • elec_mean - average electrical power consumed (W)
  • flowT_mean - average flow temperature (°C)
  • heat_kwh - total heat energy produced
  • heat_mean - average heat power produced (W)
  • outsideT_mean - average outside temperature (°C)
  • prc_carnot - percentage of carnot COP (usually around 50%)
  • returnT_mean - average return temperature (°C)
  • roomT_mean - average room temperature (°C)

If you want data for a specific period (say 91 days from November through January) you can query /system/stats?start=2023-11-01&end=2024-1-01


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