Intrinsic and extrinsic quality of data for open data repositories

This work assesses the quality of Internet of Things data not only as an intrinsic quality on how well it represents the related phenomenon but also, on how much information it contains to educate an artificial entity. The quality metrics here proposed are tested with real datasets. Also, they are implemented on OpenCPU, so the open data repositories can use them off-the-shelf to rate their datasets without computational cost and minimum human intervention, making them more attractive to potential users and gaining visibility and impact. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences.