dataset for systematic mapping of optimization techniques
We develop a Systematic Mapping Study to observe the fundamentals and techniques used in Data Curation for Big Data. We focus on computational/mathematical techniques, and application scenarios with the aim of answering the following questions: (i) How Mathematics has contributed in the context of Data Curation? (ii) Are there classes of optimization algorithms being used in the context of Data Curation? If yes, which? (iii) In which application scenarios the Data Curation process has presented greater contributions? Our search was performed in some well-known bibliographic sites. Our main study focuses on original contributions to the field of Data Curation. We found that a large number of papers concentrates just on applying known techniques to specific domains. We take these two groups into account. In this context, we perceive the most prominent areas of Mathematics and identify opportunities for further studies in the areas of Mathematics. We observed the most relevant computational elements in the context of this study. We were able to list countries with significant contributions. We have identified the areas that are the most frequent targets for Data Curation.
Supplementary data to the manuscript "Data Curation and Optimization Techniques: A Systematic Mapping Study"
In each database, listed in the main file, we submit the search string “Data curation” AND “Optimization” and retrieve the publications that contain the search string in the titles and abstracts. The recovered materials are contained in the attached file, and arranged in lines. The categories analyzed in the systematic mapping are arranged in columns, and were analyzed for each recovered material. The numbering contained in each category represents adherence of the category to the recovered material articles).