Welcome to Mozilla Science Lab's Open Data Primers!


OK, open data sounds great, but...

You’ve probably already heard some counter-arguments to open data and you may have a few lingering questions yourself. Here are three of the most frequently voiced challenges to open data, and our answers to them.

“I’ll be scooped! Someone could discover something amazing in my data before I have a chance publish.”

Of course, you want to get as much as you can out of the data you collect and maintain. However, when you make data publicly available, you’re letting everyone know that you did it first. Open data is the ultimate security: no one can steal what has been freely shared.

“I do not have time to clean up all my raw datasets for sharing.”

We understand this argument -- no one has time. But, you’re doing this for yourself in six months or five years as much as you are for making the data open. Time spent adding context and meta-information to your data now will save you hours down the road. Take baby-steps to tackle this a little at a time:

"I don't get to make the decision as to whether or not my data gets shared."

Things are changing fast. Your supervisor may not realize that new funder and publisher requirements are changing the way data should be managed by members of the research group, and what data must be shared along with a publication. We’re here to help! If you want to move your research group towards open data, you don’t have to do all at once. Start with data management to lay the foundation. There are lots of simple ways to get started, and we’ve outlined them in the second primer in this series, How to Open Your Data. Take a look and see if there are one or two best practices in data management that you can incorporate into your workflow now.

For more challenges to open data and snappy and convincing responses to each of them, check out these two resources:

These are great talking points to use when telling your colleagues, friends, and loved ones about open data.