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Don’t Touch That – It’s Under Revision!

Don’t Touch That – It’s Under Revision!

Every good researcher knows what a vital role data sharing plays in the data life cycle. So in a perfect world, the decision to share data would be an easy one to make. By effortlessly passing data on to someone else, you would receive all the spectacular rewards data sharing has to offer – a reputation boost for yourself and a colleague, the satisfaction of fueling new projects and discoveries, and enough leisure time left over to start a new book or take up bird watching. What more could a researcher ask for?

Not surprisingly, however, researchers often find themselves at the mercy of the same mess of hierarchies, rules, and complications that plague the rest of the professional world. In this data story, a novice researcher finds himself in the murkier depths of data sharing where the boundaries of academic territory can seem hazy.

Daniel had just started out in ecological research, but already found himself invited to participate in a working group on species interactions. The group was made up of many experienced scientists in the midst of their careers… and Daniel. But what Daniel lacked in experience, he made up for in connections. The working group was very interested in a dataset Daniel had been working on for several years and had hopeful plans of incorporating it into a model they were developing. The problem? While Daniel held a copy of the dataset, he did not actually own it. In his work with faculty mentor Dr. Stevenson, Daniel had enjoyed liberal access to the PI’s impressive dataset. With a few years of collaborative work behind them, mentor and mentee had developed a trusting relationship where Daniel received an uncommon level of data access.

As someone already involved with the dataset, Daniel was in an ideal position to act as information broker between the enthusiastic working group and his mentor. With these connections, Daniel expected the data sharing process to be a smooth one. However, uneager to upset Stevenson or jeopardize their work relationship, Daniel knew he would first need to gain permission to share the data.

But when Daniel approached Stevenson with the request, he discovered the situation was more complicated than he had anticipated. Dr. Stevenson wanted to help Daniel and give him the information his working group needed, but the data was undergoing revisions. Advances in species identification with DNA barcoding had made it possible to more accurately distinguish one species from another. But with the shift away from morphological characteristics identification, the species in Stevenson’s dataset were suddenly thrown into question. After years of meticulously collecting and maintaining the data, the last thing Stevenson wanted was for it to become obsolescent. Determined to present a perfectly accurate dataset that would maintain relevance in a changing world, she embraced the new technology and began applying it to her existing samples. Revising the large body of data was possible, but it would take time. Meanwhile, Stevenson was hesitant to share the taxonomic databases while they underwent revisions, lest they later be found inaccurate. When those revisions would be completed was anyone’s guess.

Caught between his allegiance to the working group and his respect for Stevenson, Daniel found himself in the unenviable role of middle man. Emails zinged back and forth: polite pleas from the working group, and apologetically resolute responses from Stevenson. After months of correspondence and bouncing between working group and mentor, Daniel's efforts have yet to pay off. The dataset remains in the senior PI’s hands (in, Daniel hopes, a final draft version!).

While the uncertain outcome may remain a hurdle for the working group, Daniel feels assured he has made the right decision in waiting for Stevenson’s revised dataset. He has done what he can to push the project along without overstepping boundaries or straining his relationship with his mentor. The wait may be a temporary setback, but Daniel and the working group can rest easy knowing that when the dataset is finally delivered, its improved precision will make it all the more valuable.

Image: CC-BY-NC-SA by Tanakawho via flickr