Tag Archives: open humans

Share Your Method of Analysis Without Sharing Your Data

How the author has used sad/loving/joyful emoji on Twitter over time.

This visualization from an example Personal Data Notebook shows how someone used various emoji on Twitter over time.

We are happy to have a guest post from Bastian Greshake Tzovaras, the director of research at the Open Humans project, on a new way to share personal data analysis methods. Read to the end to learn about a data analysis contest happening this month. Bastian can be found online at @gedankenstuecke. -Steven

The Quantified Self community builds its collective knowledge from individuals sharing insights gleaned from their own n-of-1 data. Not only do we learn from these projects, we also get inspired to do the same or similar projects of our own. But it’s easy to get tripped up when trying to do the same analysis on your own data. Is your input data in the same format? Are you running the code on the same operating system? Can you get all the dependencies installed? What if you have never really written code before or executed analysis scripts?

In the realm of academic science these issues are grouped under the label “reproducibility”. A solution to many of these issues are Jupyter Notebooks, which can be used to share code for analyzing data. JupyterHubs make it easy to host these notebooks online and overcome the difficulties that come with different operating systems, software packages, etc. Open Humans, a non-profit foundation that helps people donate their data to research, is using this technology to make the analysis of self-collected data reproducible for other members of the Quantified Self community.

We just released Open Humans’ Personal Data Notebooks. These are run in the browser and give people access to the data that they have stored in Open Humans. Data from Fitbit, Apple Health, Moves, Twitter, and a selection of genetic data providers is currently supported. People can write their personal data analysis in Python, R or Julia right in their web browser and see the results there – without having to worry about installing any local packages on their own computer. If you are proficient in any of these programming languages, it is easy to write your data analysis from scratch. If you are unfamiliar with coding in general – or with Python, R or Julia, in particular – the Personal Data Notebooks offer well-documented example notebooks which can be run without any prior knowledge as no modifications are needed and can serve as a great way to start coding.

Code from an example Personal Data Notebook.

For all notebooks the resulting analysis and visualizations can be shared easily with other users who then plug in their own data. We have made it easy to decouple the data analysis from the underlying data. You can share your data analysis code without having to share your personal data itself. Since data sources inside Open Humans are standardized, someone else’s Fitbit data will work just as well as your own.

There are step-by-step guides to get started with Personal Data Notebooks and example notebooks which can analyze your activity data from Fitbit and Apple Health or perform a  sentiment analysis of your Twitter data.

To celebrate the launch of the Personal Data Notebooks, Open Humans and Quantified Self are running a notebook competition.

To take part, all you have to do is:

Gary Wolf, Steven Jonas, and Azure Grant of Quantified Self will judge and rank the submitted notebooks. The most interesting notebooks will be highlighted and added to the set of existing samples that are preinstalled for each user. The winning notebooks will be featured here, on the Quantified Self blog. If you want to share and discuss your notebook ideas, The Open Humans community on Slack is eager to have you.

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Open Research, Open Data, Open Humans

“Open Humans aims to break down data silos in human health and research. We believe data has a huge potential to live and grow beyond the boundaries a single study or program. Our online portal allows members to aggregate data from the research they participate in. By connecting individuals willing to share existing research data about themselves with researchers who are interested in using that data, data can be re-used and built upon.” — OpenHumans.org

On March 24, 2015 the Open Humans Network officially opened their virtual doors and began allowing individuals to sign up and engage in a new model of participatory research. We spoke with Co-founder & Principal Investigator of the Public Data Sharing study, Madeleine Ball, Ph.D. about Open Humans, what it means for research, and what we can look foward to from this exciting initiative. The following is an edited transcript of that conversation.

It’s been a lot of work up to this point.

We’re grateful to have the funding support of two organizations to help get this off the ground, the Knight Foundation and the Robert Wood Johnson Foundation. It’s been a lot of work to get to this point, from hiring Beau Gunderson as our Senior Software Gardener to launching with our first three studies. We’re excited to be partnering with the Harvard Personal Genomes Project, the American Gut study, and the GoViral study. These are the seed studies, what we’ll build off of in the coming months and years. Today, we’re excited to start letting participants in these projects, and all individuals interested in participating in research, know about Open Humans.

This is an open invitation to join us.

We’re also working to make it easier for research partners to join the Open Humans Network. We’ve already started receiving interest from researchers that want to integrate with Open Humans or start working with our already growing public data sets. We’ve set parameters regarding how you have to behave as a study as well as how researchers looking to work with our members should engage with us. (You can find out more about that here.)

For members who sign up with us we’ve developed methods for them to control access to their data. Whether that is data from personal health devices and apps like Runkeeper (adding this to our next project), genetic data, or other data sources derived from participating studies, each individual member will have the ability to establish a peer-to-peer interaction. Members can allow access to some data, but not others. They may choose to release some or all of their data publicly, or the may choose to only share with one study. In the end it’s up to them and their individuals goals.


What excites me about Open Humans is the potential we have to transform future research studies — from how they treat data to how they think about data sharing. We’re building our system so that participants are central to the data process. A good example of this when researchers use our member’s data they must also agree to return any new data that results from their research back to the original participant. This decentralization of data is a key component of our design. No single person, researchers, or study has all the data.

We’ve also built in the ability for researchers to contact our members who contribute data. The idea that researchers must come up with all the right questions before starting a study is a recipe for failure. Researchers are not psychic, that can’t forsee what interesting questions might come up in the future. By opening up the ability for these connections to take place in the design of Open Humans, we’re creating the ability to continue asking questions of specific individuals, or groups of people, far in to the future.

We’re founded on the principle of transparency. You as a researcher, or participant member can see what we’re all about. You can even see our Open Human member profiles (Madeleine BallJason BobeBeau Gunderson). We worked with Marcia Hoffman, special counsel to the Electronic Frontier Foundation, to develop our Terms of Use and Data Use Policies so that they’re readable and easily understood. We want people to read them, we want them to ask us questions. We want people to be engaged and involved.

I think this work is creating a new form of data sharing that will unlock a world of new exciting possibilities. Our hope is that when participants start getting data back from studies, and have the ability to use it and share it how they wish, that participation in research will be more rewarding. This model helps participants become a respected member of the evolving research conversations happening all over world. We know a lot of people don’t participate in research, even researchers who rely on participants don’t participate in studies. Hopefully this work will help move the needle.

It’s wonderful to see the long scroll of members.

As of this writing the Open Humans Network has over 200 individuals who have created member profiles. If you’re interested in participating in open research you can learn more and sign up here. If you are a researcher or personal data company interested in integrating with Open Humans you can get in touch with the team here.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along here, on Medium, and @quantifiedself.

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