Nowadays, many things are referred to as "data" - people may say that when they mean "statistics," or "some factual/numeric information," or even just "something in digital format" - so it will be helpful to draw some boundaries and clarify some definitions first.
The purpose of this guide, then, is to help you with making the data that you generate in the course of your research discoverable and resuable by others, publish or share it, protect it as may necessary or required, and preserve it for posterity.
What we mean by "research data" warrants some deliberation, to delineate it from other types of information, as mentioned above. As the Australian National Data Service puts it: "Providing an authoritative definition of research data is challenging, as any definition is likely to depend on the context in which the question is asked." That is true!
So, what is not research data? Well, we would typically not call a journal article that presents scientific findings, including results from data analyses, "research data." Nor would we refer to a statistical table that summarizes and presents data analyses as "research data." Usually, we think of research data as a bunch of information - numerical datasets, images, sounds, etc. - that is so large and/or complex that it requires computer-aided analysis to make sense of - as opposed to a poster, article, presentation, or podcast that is intended to be comprehended by viewing or hearing it.
And yet, the water gets muddy again ... a whole lot of journal articles, or a whole lot of (or large enough) statistical tables, can themselves become input for (meta-)analysis. So the output of research, in different formats and at different levels of information aggregation, can become the input of other data analysis ... we can therefore think of a lifecycle of research data.