As data becomes more ubiquitous, and datasets become larger and more complex, processing by computers becomes ever more crucial. Posting data in a format that is not machine-readable places severe limitations on the continuing usefulness of the data. Data becomes useful when it has been processed and transformed into information. Note that there is an important distinction between formats that can be read and edited by humans using a computer and formats that are machine-readable. The latter term implies that the data is readily extracted, transformed and processed by a computer.
Using non-standard data formats is costly and inefficient, and the data may lose meaning as it is transformed. By contrast, standardized data formats enable interoperability as well as future uses, such as remixing or visualization, many of which cannot be anticipated when the data is first published. It is also important to note that most machine-readable standardized formats are also locale-neutral.
Intended Outcome
Machines will easily be able to read and process data published on the Web and humans will be able to use computational tools typically available in the relevant domain to work with the data.
Possible Approach to Implementation
Make data available in a machine-readable standardized data format that is easily parseable including but not limited to CSV, XML, HDF5, JSON and RDF serialization syntaxes like RDF/XML, JSON-LD, or Turtle.
jmaitra
commented
7 years ago
from https://www.w3.org/TR/dwbp/#dataFormats