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@@ -734,18 +734,18 @@ This is a long-term goal and requires major changes to academic value systems. \section{Conclusion \& Summary} \label{sec:conclusion} -To effectively leverage the power of big data, we need to have a complete view of its lineage. -Scientists are however rarely trained sufficiently in data management or software development, and the plethora of high-level tools that change every few years does not help. +To effectively leverage the scientific power of big data, we need to have a complete view of its lineage. +Scientists are, however, rarely trained sufficiently in data management or software development, and the plethora of high-level tools that change every few years does not help. Such high-level tools are primarily targetted at software developers, who are paid to learn them and use them effectively for short-term projects. -Scientists on the other hand need to focus on their own research fields, and need to think about longevity. +Scientists, on the other hand, need to focus on their own research fields, and need to think about longevity. -Maneage is designed as a complete template, providing scientists with a built low-level skeleton, using simple and robust tools that have withstood the test of time while being actively developed. -Scientists can customize its existing data management for their own projects, enabling them to learn and master the lower-level tools in the meantime. -This improves their efficiency and the robustness of their scientific result, while also enabling future scientists to reproduce and build-upon their work. +Maneage is designed as a complete template, providing scientists with a pre-built low-level skeleton, using simple and robust tools that have withstood the test of time and are actively maintained. +Scientists can customize Maneage's existing data management for their own projects, enabling them to learn and master the lower-level tools. +This improves their efficiency and the robustness of their scientific results, while also enabling future scientists to reproduce and build upon their work. -We discussed the founding principles of Maneage that are completeness, modularity, minimal complexity, verifiable inputs and outputs, temporal provenance, and free software. -We showed how these principles are implemented in an already built structure, ready for customization and discussed the caveats and advantages of this implementation. -With a larger user-base and wider application in scientific (and hopefully industrial) applications, Maneage will certainly grow and become even more robust, stable and user friendly. +We discussed the founding principles of Maneage that are completeness, modularity, minimal complexity, verifiable inputs and outputs, temporal provenance, scalability, and free software. +We showed how these principles are implemented in an existing structure, ready for customization, and discussed its advantages and disadvantages. +With a larger user-base and wider application in scientific (and hopefully industrial) applications, Maneage will grow and become even more robust, stable and user friendly. |