Open data on what people eat?

An example of an indicator: % of households in a country consuming iodised salt. Not much data there...

I received an interesting question from some good colleagues in the Global Open Data for Agriculture and Nutrition (GODAN) initiative: can we have access to data about what people eat? The question originally focused on whether there exists a central database and/or very large dataset (including multiple years/countries) capturing what people eat.  This means not just caloric consumption per person, but what they actually consume.  For example – today I have consumed a small apple, half small melon, 5 pieces bacon. This got me into a little bit of thinking: do we have access to such data? And from what type of sources?


What do people really eat?


I know for sure that we do have access to general statistics about health & nutrition in different countries. There is the example of the World Bank and its DataBank repository: it published data on Health Nutrition and Population Statistics per country that can give an indication of what people eat. Again, this source is providing information on very specific indicators (mostly related to malnutrition) that is not always complete (not all countries and not all years are covered, even for those indicators). I assume that this is the case with many data sets coming from governmental sources – you may find data that is missing, that need cleaning, or that would have extra value only after you combine them with data from other sources.


An example of an indicator: % of households in a country consuming iodised salt. Not much data there...

An example of an indicator: % of households in a country consuming iodised salt. Not much data there…


I think that the type of data that my colleagues are looking for is logged in all these apps for calorie monitoring that are so popular in the “developed” world. Such applications (see examples here and here) help their users reduce their daily calorie consumption (and therefore become more fit) by logging all their meals during their day. Sometimes, the creators of these apps are also affiliated with the academia, being able to do research on this massive data set that they are collecting from their users. This got me wondering about how you could convince such companies to open up (parts of) their data for open research purposes. And of course the way in which such an open move should be carried out – thinking about issues like anonymising the data, licensing the use of the data from the users, etc.


Noom is one of the popular examples: millions of people have downloaded this app and using it to log what they eat every day – imagine the amount of data that these guys are collecting (and how much valuable such a data set would be for research)


And if we are into such a crowd-sourced way of collecting data about what people eat, how about thinking in terms of really open platforms where people pro-actively contribute and share their data? I would imagine platforms like the one from Numbeo that collect user-provided information on various indicators (for instance, more than 1,3 million prices of products and services, from more than 4,5 thousands cities, provided by more than 150 thousand people), creating again a massive data source that could be of tremendous value for research and innovation.


Want to know about the cost of living in a particular country? The Numbeo community documents everything…


My conclusion is that I don’t have the definite answer in the question “What do people eat?”. But I can think of different sources, that use different collection mechanisms and models, and that have their own value in assembling this information and generating this knowledge. Which are exactly the needed next steps after the various relevant data sources are identified: “assembling information from various sources” and then “generating knowledge out of the data”…


  1. This approach raises some really interesting issues:

    1. The motivation for anyone to record and share his/her daily food consumption details; for example, even though I know (and I remember sometimes) more or less what I have eaten throughout a day, I am not keeping track of this information. Why should I do that and in which way? Will it help me eat more healthy? Should I use a paper notebook, a spreadsheet, a shared document? This leads us to the second point:

    2. The mean for anyone to do so in an attractive way: People tend to be social and share more information than they should. They share private information through Facebook, they check in at various places using Foursquare, they report on how long their run was and how much time it took them using Fitness Trackers etc. There’s nothing easier for me than use a mobile app to keep track of what I have eaten and even take a nice photo of it! In this context, apps like a Personal Food Trainer (I am sure that there are plenty of them for Android/iOS, too) are a nice way for people to record what they have eaten and how much, when etc. Each similar app may collect a significant amount of data from people all over the world but I can see two points raised here:

    2.1: Interoperability: I guess that such apps do not use a common way to describe the same dishes/food; e.g. roasted chicken can also be chicken (roasted) or be described in several different ways. I know that there are tools that could be used for homogenizing the different means of expressing the same term, so I guess that this is not a problem.

    2.2. Accessibility: Even in the case that these apps collect large amounts of data, can they be shared through e.g. an API? Would this be legal? Could there be a way for these data to be published online, even after they have been anonymized or are they still personal sensitive information? Which in turn leads us to point 3

    3. The licensing of data: How are these data submitted to the servers of the corresponding mobile apps? What are the terms of use of each similar service/app and do these term allow the reuse of the data collected for e.g. statistical purposes?

    Thanks for sharing your ideas through the initial post; it made me see things on food data in a different (and maybe more structured) way.


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