Research Workflow

To understand how to be more productive in research, one must understand how the research flow works. This not only helps us understand which part we are lazing behind and correct our flow. If there is a disruption in any part of the research flow cycle there is a breakdown which leads to more and more procrastination. The flow cycle consists of mainly :

1. Identify Research Area :
2. Identify the research question 
3. Why is it interesting/ what motivates you and 
4. form a hypothesis/ experiment 
5. Analyze Data, Infer and conclude
6. Is hypothesis correct ? Yes ..then publish.
7. No ? Then correct hypothesis and go back to 4.

Identify Research Areas and questions

It happens quite often that in academia people are clueless after just submitting a paper. It is like an existential crisis, What should I do now ? Where will I go ? All these questions demand you to find a new vocation to engage your burning mind. Therefore it is always good to have ideas which strike you during the project and write them in a book/record.
Find a research question is to essentially find the gaps and loop holes left by researchers. You can find these open questions at the end of the latest review articles or papers. 

1. Set aside some thinking time : Find papers to read and try making a mind map as to what are their contributions to the fields. Go away from computers and have some thinking time. 
2. Keep track of ongoing research: Mind Maps is the way to go in keeping track of most esssential ideas. Summarize a paper in few key words and then write the conclusion in one line.
3. Record Ideas : Make an Idea Book to keep all your silly, crazy ideas in one place. Then review them as to when to convert them into papers. Assign them priority in terms of their do-ability and the impact they will have on the community.

From idea to paper 

Converting a simple thought into action is almost similar to converting energy into matter. It is creating tangible out of intangible. This conversion needs effort and persistence. Your ideas will get recognized only if they get validated and published. If you keep them in your idea book for too long, you get scooped which means somebody did what you intended to do. This is very frustrating if you were doing repeat experiments and hoped to make the research into a high impact paper but it finally ends up useless. So, the execution must be fast enough. If you are not able to drive the project, ask someone else to help you out. An external viewpoint always helps understanding what is stopping you from finishing the project. So go ask a colleague or a friend, what is going wrong.

Steps to follow :

1. Idea/Hypothesis 
2. Validation/Experiment/Simulation 
3. Correct hypothesis if not fitting the data
4. Repeat the experiments to confirm
5. Understand and write up

Importance of experimental log and periodic review

As a serial criminal in this regard, I can't just feel more regretful for not carefully documenting the experimental details and procedures followed during the course of your experiments. You may think that you will remember the reason you named a file abasas.dat on the day of your experiment, but the next time it will just appear as stupid data much like the others. Also, I have seen this a thousand times happening with me that the name of the experimental files begin with new,final. e.g. NewData.txt, Finaldata.txt, AmazingResult.txt. After a few days, you might forget what the context was. A good practice is to use a sample prefix for a set of experimental data, add a date and time if it is important, add the basic conditions at which the experiment was performed. This gives a clear usable file name which will be usable until eternity by your academic generations.

Periodical review is very important as well. However you named your file, you will still not be able to find it when you need critically while making a powerpoint. Make sure you analyse your data the following week and then make all the usable plots out of it. After that put them in a powerpoint presentation which makes your data more visible. You can add your inferences from the data.

Backup research data

Backup as much as possible. You always can delete the copies. If you lose the only copy that ever existed, you are pretty much busted. Signing up for cloud storage has its own advantages. Google drive and Dropbox have great starting packages and quite useful for storing your hard earned data. It always good to have access to your data from multiple computers.

Limited Working Hours/Time

One cannot stress the importance of time management enough in a research environment. We have to manage time to achieve your goals and also leave enough time for the life outside lab. Thinking that more hours in lab will lead to better results is a vanity. One must start the day with the aim to finish by evening and leave the lab for the next day. You could always read in your free time at nights but spending it in lab will not help out.

Will keep updating this with new ideas as and when I get better with my research life. These are few things to remind myself and be better at research. Please do share if you find some important missing here !!