Knowledge—An Open Access Science and Technology Journal
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Knowledge 2021, 1(1), 1; https://0-doi-org.brum.beds.ac.uk/10.3390/knowledge1010001
Submission received: 19 May 2021
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Accepted: 21 May 2021
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Published: 31 May 2021
In 2021, the 12th volume of Information [1] will be published. Information was first launched in 2010 as a scientific journal with a broad scope, covering information science, information technology, data, knowledge and communication [2].
In 2016, MDPI launched a related journal, Data [3]. Following on from this, we will shortly introduce Knowledge (ISSN 2673-9585), another open access science and technology journal. The three related terms—data, information and knowledge—may encompass various aspects, though some will undoubtedly overlap. Upon serious consideration of these terms, I discovered one important difference: regarding a system, the amount in bit or GB will be smaller from data to information and to knowledge, as I define information as the amount of data present after data compression, while knowledge is the further reduction of information, amounting to the more essential data [4]. This is one of the reasons behind our decision to launch an additional journal, Knowledge, completing this three-part series of journals focusing on these three topics of immense interest.
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Funding
This research received no external funding.
Data Availability Statement
Not applicable.
Acknowledgments
The author is grateful to the English editor Lisa Patel for providing extensive editing of this Editorial.
Conflicts of Interest
The author declares no conflict of interest.
References
- Information Home Page. Available online: https://0-www-mdpi-com.brum.beds.ac.uk/journal/information (accessed on 19 May 2021).
- Lin, S.-K. Information—A New Open Access Scientific Journal on Information Science, Information Technology, Data, Knowledge and Communication. Information 2010, 1, 1–2. [Google Scholar] [CrossRef] [Green Version]
- Data Home Page. Available online: https://0-www-mdpi-com.brum.beds.ac.uk/journal/data (accessed on 19 May 2021).
- Lin, S.-K. Gibbs Paradox and Similarity Principle. In Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Proceedings of the MaxEnt2008, Sao Sebastiao, Sao Paulo, Brazil, 6–11 July 2008; American Institute Physics: College Park, MD, USA, 2008; Volume 1073, pp. 49–60. [Google Scholar] [CrossRef]
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MDPI and ACS Style
Lin, S.-K. Knowledge—An Open Access Science and Technology Journal. Knowledge 2021, 1, 1. https://0-doi-org.brum.beds.ac.uk/10.3390/knowledge1010001
AMA Style
Lin S-K. Knowledge—An Open Access Science and Technology Journal. Knowledge. 2021; 1(1):1. https://0-doi-org.brum.beds.ac.uk/10.3390/knowledge1010001
Chicago/Turabian StyleLin, Shu-Kun. 2021. "Knowledge—An Open Access Science and Technology Journal" Knowledge 1, no. 1: 1. https://0-doi-org.brum.beds.ac.uk/10.3390/knowledge1010001
