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authorBoud Roukema <boud@cosmo.torun.pl>2020-04-23 17:36:12 +0200
committerBoud Roukema <boud@cosmo.torun.pl>2020-04-23 17:36:12 +0200
commit6e2ea987a8972b1f0d8f07be47e535e9495d1caf (patch)
treec1f6d5c7c5dd0301012d9584fd2286320f8f2a3e
parent1de931db43851c60a5ebaece053c69cf07bfc66d (diff)
Conclusion
Reduction by about 5 words. Although it's true that the low-level tools - make, bash, gcc - are still being actively developed, only expert users will tend to notice the differences, and in this context, it's probably more useful to point out that these are actively *maintained*. (Comment: I felt that the first sentence in the Conclusion is missing one of the obvious criteria for handling big data - citizen control so that big data could hopefully become less Orwellian than it is right now, with GAFAM having the main big data databases that are used by AI researchers and will tend to affect people's lives more than traditional "scientific" databases. But there's no point adding this here, since the criteria that tend to satisfy the scientific requirements ("principles") and citizens' rights tend to overlap to a fair degree...)
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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.