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Observations and Interviews
1. V.
V. is a postdoc working at a Biology lab at MIT that requires a lot of data processing support. V. herself does not do any computational work, although often solicits the help of computer scientists in analyzing her data.
V. is relatively satisfied with her interactions with the computer scientists, although she mentions that efficient communication is important because the computer scientist she works with needs to understand exactly what biological questions she is interested in. Where possible, V. uses workflows such as Galaxy (a software for performing basic computational biology tasks such as finding the intersection of two sets of regions). She mentions it is also sometimes difficult to wait until a computer scientist is free to do the work for her, as the available computer scientists are often oversubscribed. When asked if she often needs the computer scientist to perform similar tasks repeatedly, or to perform permutations of the same tasks, she said yes and agreed that it would be nice if she could perform the various permutations of a task herself rather than soliciting the help of a computer scientist each time.
When asked if there were other problems she encounters in her day-to-day life, she said that it is difficult to keep track of the various permutations of an experimental protocol that exist, and wished for a centralized way of knowing what people have tried in the past and what worked. For instance, she is currently working on a protocol for chromatin fractionation and is trying to gather as much information about it as she can. When we asked if we could see how she went about gathering information about a protocol, she revealed a large stack of papers and spent considerable time navigating it to find her desired paper, which was the experimental protocol published by the Young Lab. She then pulled up another set of papers which had the protocol that she had obtained from talking to the Young Lab directly. The latter protocol had several handwritten annotations and was messy to read, but also contained substantially more detail than the official published protocol. Photographs of the two papers side by side are included below: 
V also mentioned that even within the lab, variations of a protocol (eg: for chromatin immunoprecipitation) exist for different antibodies and conditions, and the only way to gather all the necessary information is to go talking to people which is inefficient. Other members in the lab who were present seconded this opinion. A quick look at the lab notebooks revealed that Biologists would copy protocols into their lab notebook even though they are present on the lab’s online wiki in order to make annotations like the one shown below (“JW” is another member of the lab): 
Furthermore, in optimizing an experimental procedure, biologists also keep track of their previous attempts and their mistakes, so that they know what worked and what did not. Very often biologists will commit an error in a step and will proceed with the protocol anyway, as it is a learning experience in how sensitive individual steps in the protocol are. An example of such an annotation is shown below: 
As the years progress, however, lab notebooks can become bulky, and the task of flipping through them to identify the desired iteration of an experiment can be tedious. Some biologists use electronic lab notebooks, but they are still not optimized for tracking the various iterations of an experiment.
Lessons learned:
- Biologists like V. are comfortable using GUI workflows to perform computational tasks (eg: the Galaxy webserver).
- If there is no available GUI, biologists like V. are dependent on a programmer for performing the analysis. However, they must work closely with the programmer to ensure that there is full understanding of the question under investigation. Communication is paramount.
- Biologists like V. do not personally run scripts that a programmer has written, even if the programmer has a readily useable script that could perform the desired analysis.
- Novel experimental protocols are not set in stone; the level of detail that is published in a journal is much less than the level of detail that one could obtain from talking to the biologists who developed the protocol.
- Experimental protocols also vary depending on the conditions/reagents used (eg: Chromatin immunoprecipitation is different for different antibodies).
- The “little details” are often critical to understanding how to get your experiment to work. It is important to gather as much information as possible directly from the people who have done the experiment in the past.
- Negative results are important too; if an experiment fails, it is valuable to remember why it failed.
- There is currently no efficient way to share the ‘little details’ about an experimental procedure between biologists.
2. S.
S is a graduate student in the Biology department at MIT and needs to do biological data processing for her research. She needs to run big computational jobs on the lab’s cluster occasionally. She often notes down the required commands and parameters for a program she needs to run in EverNote (A free note taking software for macbook users), so that she can copy paste them later. But she often forgets where she has put her notes and also finds it difficult to search and find the location of the input files on the server if she needs to do the same analysis again. When she can’t locate her notes about the required commands, she looks at the help file in the command line but does not find it very helpful since it has a lot of text and she is only interested in finding how to run the program. She feels that, it would be easier for her to do data analysis if she could just fill the boxes with the parameters and select the command to run. She would also want to see examples, caveats and history of her previous selections.
Lessons learned
- Uncomfortable in using the commands and parameters to run a program, often forgets them
- Feels comfortable in filling in forms and selecting commands
- Looks up the command line help file to see how to run a program
- Wants to see command format, examples and possible caveats
- Wants to see the history of commands she ran in the past