awesome-quantified-self VS QS-data-flow-network-graph

This sounds like something Beeminder [1] is doing since 2011, have you heard of them?

They have a huge community and tools ecosystem.

You might also want to check the Awesome List "Quantified Self" [2] if you like these kind of tools.

[1] https://www.beeminder.com/overview

[2] https://github.com/woop/awesome-quantified-self

Sorry also to add, you might find something meeting your requirements here: https://github.com/woop/awesome-quantified-self

https://github.com/woop/awesome-quantified-self The Quantified Self is a movement to incorporate technology into data acquisition on aspects of a person's daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousal, blood oxygen levels), and performance (mental and physical).

https://github.com/woop/awesome-quantified-self MIT's OCW https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s897-machine-learning-for-healthcare-spring-2019/lecture-videos/lecture-1-what-makes-healthcare-unique/ https://github.com/ran88dom99/QS-data-flow-network-graph

Was it? Seems that it had some updates (maybe not as active as it used to https://github.com/woop/awesome-quantified-self/commits/mast... )

Either way don't think I've seen anything better, so the best way would be to suggest them updates or help maintaining :)

I wonder if you'd like this community: https://github.com/woop/awesome-quantified-self

It's similar to what you're describing and aligns well with the idea of using your personal data in a more open way.

There are many other apps/services too - a list can be found at Awesome Quantified Self. The idea of a centralized aggregator for personal data is really popular, and many people are trying to make them - including me! However, as far as I know, none of them have truly caught on/offered really deep insight into data yet.

My understanding so far is that if you have some programing background, the best workable solution today is to write little pieces of code that recover your data regularly from different APIs (store in csv). There are frequently such things already existing on github you can reuse like the Awesome QS project.

https://github.com/woop/awesome-quantified-self MIT's OCW https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s897-machine-learning-for-healthcare-spring-2019/lecture-videos/lecture-1-what-makes-healthcare-unique/ https://github.com/ran88dom99/QS-data-flow-network-graph

mbientlabs can be set to measure acceleration (gravity) in 3d space. Probably want a less technical solution somewhere in datasets in here: https://github.com/ran88dom99/QS-data-flow-network-graph.

https://github.com/ran88dom99/QS-data-flow-network-graph if line is green its easy to do

If you don't mind csv files then anything seen here: https://github.com/ran88dom99/QS-data-flow-network-graph except quantified mind, human benchmark and miband.

try openhumans.org . they do alot of what you intend. here is what I use : https://github.com/ran88dom99/QS-data-flow-network-graph

Letting google have a bit of data is fine. I think. I just give it the sensors in the android phone and a band. Everything else: https://github.com/ran88dom99/QS-data-flow-network-graph

I think you have lots of competitors whom you should reach out to. Openhumans, https://github.com/ran88dom99/QS-data-flow-network-graph https://github.com/woop/awesome-quantified-self

Sorry. I missed a very important word: Named they are all named daily tracker + some minor change. two databases of possible competitors and collaborators. https://github.com/ran88dom99/QS-data-flow-network-graph/blob/master/Connections.csv https://github.com/woop/awesome-quantified-self