How to Present Research Data: A Lesson!

I guess I am not only the prize sap, and may not only be this time. I think I may be ignorant in the past too. I was doing experiment on real testbed last summer and was logging all the real time data for later analysis. I predefined my mind that what I need to discover from this data, I was looking for time delay of the traffic and throughput of all data. I plotted all graphs and I thought I am done with the experiments. Though, the throughput I got was not good, but I was able to justify the reasons and there were lots of spikes in the graphs . I knew "why these spikes are?" due to my one set of topology. I repeated the experiment 100 times but because setting were same, so didn't get the significant difference. I closed the results in my research report and moved on...

Now the things after a year:

1. I didn't mention anywhere in my report that why these spikes were, though I know it..but I should have mentioned it explicitly for the reader. Isn't?
2. If I knew that spikes are due to one set of topology, I should have tried to normalize results by making different topologies. But I was too lazy to do that, so I convinced my self, that if somebody enquire about it, why these spikes, I'll clearly say that due to topology. But I didn't bother to think that if somebody asks , did you try with other topologies or Why you chose this particular topology? Is it standard? So, now as a result, I learnt that either I had have selected standard topology or provided normalized results. Should try to give answers of all the questions in written form in the report before anybody asks you.
3. When I was analyzing results(I mean drawing graphs etc.), I found sink has more data from nearest node than distant node, but then I thought, so what?
Its obvious that near nodes traffic reaches earlier and suffers with less error rates. But Again, I didn't write my this observation in the report. If I would have drawn a graph to show in what proportion this occur and more reasons..it would have been a publishable work!
So, I hope I'll learn from my own mistakes, but wish you shouldn't repeat the same :).

Research Ethics

Recently, I was chatting with one of my acquaintance about research and degree in research and realized the importance of knowing research ethics before pondering into the deep sea of hard work. Learning from the researchers whom I met in last three years, I prefab word to the wise about the research ethics. Here, I am not considering medical science research ethics, as my research work doesn't involve human subject use (HSU).

First and foremost, Originality is always paramount in scientific research, avoid plagiarism by proper citing of the other works [ Proper understanding of plagarism is required]

Avoid Research misconduct by avoiding the intentional fabrication of data/results.

Evidence Support by keeping and maintaining the experiments log files and proper recording of experiment settings and assumptions.

Proper validation of experiments by repeating the experiments in same settings.

The following links are further suggested for researchers to read.

Enjoy reading and feel free to update with other useful information.

http://www.dartmouth.edu/~ethics/archives/Stern_Elliott.pdf