Einstein could teach us a thing about simplicity. While people today all across the world marvel at his genius, many fail to realise that it was the simplicity of his methodology that gave his findings plausibility to an initially sceptical scientific community.
The same can be said of abstracts. There is no use using an abstract that mimics a technical research paper in a paragraph (or dare I say, a few) decorated with technical jargon. A good abstract always follows a methodological approach, like the tenets of a legal argument but without the flowery verbosity.
The purpose of a good abstract is to delight the reader who wants to understand the scope of data collected. Abstracts are really just forefronts that accurately summarise the content of the research paper, providing a clear enough insight as to what to expect.
Good abstracts rely on clarity and succinctness to allow researchers to understand the scope of the research data and accurately summarise its content. Oftentimes abstracts are signposts for researchers who are searching for data that may be relevant to their search so they will view the titles and abstracts when searching for datasets and choosing whether to explore their content further. Abstracts should be different from the full description for a dataset.