FAQ

DataPipe serves as a connection between an experiment and the Open Science Framework. To use DataPipe, you will need to use a webhost to get your experiment online (e.g., GitHub Pages) and then add some code to your experiment to send data to DataPipe. You will also need to have an OSF account to store the data and create an authorization token on the OSF to allow DataPipe to write data to your OSF account. Our getting started guide has more information about how to use DataPipe.

No, you will need to use a different service to make the experiment available online. The benefit of using this service is that you do not need to configure any of the backend/server components of an experiment, so you can use a provider like GitHub Pages to host the experiment for free.

This guide on GitHub Pages describes how to set up a free website using their service. In the guide, select "project site" and "start from scratch" and follow the guide to get an experiment hosted quickly.

Not directly. DataPipe helps you store your data on the Open Science Framework. When you use DataPipe, the data is routed through our service to (optionally) perform validation and then we send it to the OSF. DataPipe does not store a copy of the data.

DataPipe is free to use.

The expensive parts of hosting an experiment are providing storage and bandwidth for the experiment files and data. Fortunately there are providers who are willing to do both of these things for free. GitHub (and others) will host a website for free and the Open Science Framework will store data for free. Unfortunately these providers are not directly connected to each other, so that is what we are trying to solve. DataPipe is a very lightweight (i.e., cheap) service that makes it easy to link a hosting provider with a data storage provider.

We host DataPipe using Google Firebase, so the cost of DataPipe depends on how much usage it gets. Currently our resource consumption is less than $1 per month. Once we have been up and running for a while we will post more information about how much it costs to run the service. We have funding reserves in the Open Collective account for jsPsych development to sustain this serivce. Our goal is to provide transparent information about our costs and our available funds to run the service so you can determine whether we are likely to be able to keep the service running. We are grateful for donations to help keep the service running. If you donate a few dollars to our account you should cover the lifetime cost of providing this service to you.

The data that you send to DataPipe are not stored anywhere on our servers and we do not log any information about the data when it is sent. If your OSF component that receives the data is private, then you have full control over who can see the data. If your OSF component is public, then anyone can see the data.

There are a few risks that you should be aware of before using DataPipe.

1. In order to use this service you must provide us with an OSF authorization token so that we can write data to your OSF account on your behalf. This key enables full write access, so if we suffer a data breach it would be possible for someone who got access to the token to make malicious changes to your OSF account. To mitigate this risk, you should create an OSF token that is just for this service so that you can revoke authorization when you are done using the service. The strongest security would be to use an active token only when you need to collect data through this service.
2. This service does allow a technically savvy user to potentially write fake data to your OSF project. This is almost always a risk with online experiments because the data are usually recorded on the participant's computer before being sent to the server. It is possible for a malicious user to change or create the data before sending it to the service. It is also possible that a user could spam data to your OSF account or could send files that are not actually experiment data. We provide tools to mitigate these risks by allowing you to specify validation rules for the data that is sent and to rate limit the amount of data you are receiving.
3. This service is not a commercial venture with a dedicated user support team. If something goes wrong, we may not be able to respond quickly. However, the code that runs this service is open source and thoroughly tested. The service is hosted using the Google Cloud, so we get the benefit of Google's infrastructure to make sure the service is secure and keeps running.

DataPipe has an optional feature that will validate any incoming data before sending it to the OSF. Currently, this feature supports checking whether an incoming file is valid JSON or CSV data (meaning that it has the correct format) and it allows you to specify a set of columns/fields that the data must contain. For CSV data, the validation simply checks if all of the required columns are in the header row. For JSON data, the validation checks if all of the required fields are present in at least one object in the data. For example, if the data are an array of trials (as jsPsych generates), then this validation will generate a list of all of the unique fields that are present in any of the trials and then check if all of the required fields are present. This is equivalent to converting the data to CSV format and then checking if all of the required columns are present.

If an invalid data file is sent, it will be rejected and not sent to the OSF. There is no way to recover this data. This feature is not designed to catch errors in legitimate data files. It is designed to prevent malicious users from sending non-data files to your OSF project.

DataPipe has an optional feature that will collect data as base 64 encoded strings. This is useful if you want to collect data that is not text-based, like JSON or CSV. This feature is designed to collect a single file of data at a time. For example, if you are running an experiment where the participant will record several audio files, you could use this feature to send each file to the OSF as it is recorded. When DataPipe gets a base 64 encoded file, it will decode it and then send it to the OSF as a file.

Note that validating base 64 encoded data is not currently supported, so enabling this feature does create additional risk. We recommend minimizing this risk by enabling the feature only when you are actively collecting data and disabling it when you are not.

When you enable condition assignment, you can call an API endpoint to get the next condition for a participant. DataPipe will send you a number between 0 and n-1, where n is the number of conditions you set in your experiment. If you have an experimental design with multiple factors, set the number of conditions to the number of unique cells in your design, and then use the condition number to determine the appropriate level of each factor. DataPipe generates condition numbers sequentially, so if you have 3 conditions, the first participant will get condition 0, the second participant will get condition 1, the third participant will get condition 2, and then the cycle will repeat.