Okay, enough about the problems, here’s an article offering “Ten Simple Rules for the Care and Feeding of Scientific Data”:
Today, most research projects are considered complete when a journal article based on the analysis has been written and published. The trouble is, unlike Galileo’s report in Sidereus Nuncius, the amount of real data and data description in modern publications is almost never sufficient to repeat or even statistically verify a study being presented. Worse, researchers wishing to build upon and extend work presented in the literature often have trouble recovering data associated with an article after it has been published. More often than scientists would like to admit, they cannot even recover the data associated with their own published works.
Complicating the modern situation, the words “data” and “analysis” have a wider variety of definitions today than at the time of Galileo. Theoretical investigations can create large “data” sets through simulations (e.g., The Millennium Simulation Project: http://www.mpa-garching.mpg.de/galform/v?irgo/millennium/). Large-scale data collection often takes place as a community-wide effort (e.g., The Human Genome project: http://www.genome.gov/10001772), which leads to gigantic online “databases” (organized collections of data). Computers are so essential in simulations, and in the processing of experimental and observational data, that it is also often hard to draw a dividing line between “data” and “analysis” (or “code”) when discussing the care and feeding of “data.” Sometimes, a copy of the code used to create or process data is so essential to the use of those data that the code should almost be thought of as part of the “metadata” description of the data. Other times, the code used in a scientific study is more separable from the data, but even then, many preservation and sharing principles apply to code just as well as they do to data.
So how do we go about caring for and feeding data? Extra work, no doubt, is associated with nurturing your data, but care up front will save time and increase insight later. … More.
See also: If peer review is working, why all the retractions?
Hat tip: Pos-Darwinista