Reproducible research is a kind of philosophy. I can't give a precise definition, but it goes in the same direction as open-source. However, giving the code is not sufficient to do reproducible research. The package should satisfy a few additional constraints:
The important parts must be commented on.
It contains at least a simple demonstration with some explanations.
It contains the code to run all the experiments included in the related paper.
Why are you concerned about reproducible research?
Have you ever tried to reproduce the results of a publication? If you select one randomly, it's almost impossible. If it isn't, it will probably take you hours. The number of papers and researchers has explode in the last decades. In this jungle where everyone tries to show how his technique is better, it has become hard to know when something is true or only partially true. I believe that providing all codes and datasets is the only way to really control what is published.
As a result, I've decided to make the effort to provide documented codes for all my research and I hope it will be rewarded somehow in the future.
And for the datasets?
Unfortunately, I don't have a solution to this issue. The best you can do is to use open datasets. If your experiments are linked to a special non-open dataset, you can provide some synthetic data that demonstrate how your algorithm works.
Do you want to want to join the project?
I strongly encourage you to join the reproducible research movement. Although, this is mostly a personal platform, if you use the mat2doc system to build your documentation, I'll be glad to add some web pages for you. Just send me an email.