Data Curation and Optimization Techniques: A Systematic Mapping Study

Abstract

We develop a Systematic Mapping Study to observe trends and research opportunities around the concepts and techniques used in Data Curation for Big Data. Our work investigates scientific publications with the aim of identifying how data curation has been used recently, to organize and publish big data corpora. We are interested in browsing, identifying the mathematical and computational tools used in data curation. We focus on identifying how data curation has been modeled in different scenarios and which computational/mathematical techniques have contributed to improve data curation, with the aim of answering the following questions: (i) What mathematical fields have most contributed in the context of Data Curation? (ii) Which classes of optimization algorithms are used in the context of Data Curation? (iii) What application domains have benefited the most from Data Curation? While our main focus is on the definition of new methods and algorithms, we identified a large number of papers that concentrates just on applying known techniques to specific domains. Our study may be useful to identify challenges and opportunities for further theoretical studies, as well as to show the use of some formal techniques in real-life applications.