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Data Formats
Published in Praveen Kumar, Jay Alameda, Peter Bajcsy, Mike Folk, Momcilo Markus, Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling, 2005
Proprietary technologies are not without their risks and costs. By definition their usage is restricted, and some users may be scared off from using them for fear of legal ramifications. We have seen this happen with formats in particular, in cases in which a company might wish to use a particular file format for internal purposes, but fear the consequences if the file format, or access software, in advertently leaks out. Even when licensing restrictions are well-understood, the need to accommodate licensing restrictions can significantly impact system architectures that incorporate proprietary technologies. Proprietary software can have the disadvantage that users cannot make small changes necessary to adapt it to local needs, or repair minor flaws in the software.
Data Science with Semantic Technologies: Application to Information Systems Development
Published in Journal of Computer Information Systems, 2023
Data science deals with manipulating, extracting, pre-processing, and generating predictions out of data; it therefore requires a plethora of statistical essential data science tools and programming languages to achieve that goal. Several tools are nowadays available. They may be either commercial (proprietary) or open source. Proprietary software refers to the software which is solely owned by the individual or publisher who developed it in order to profit from it, and hence copyrighted; while open-source software refers to software whose source code is made available for anybody to access, use and modify, distributed under an open-source license.91 Open-source software does not mean that it is free as fees may be collected regarding accompanying services.