Data Service API Design for Data Analytics
Yun Zhang,Liming Zhu,Xiwei Xu,Shiping Chen,An Binh Tran +4 more
- 25 Jun 2018
- pp 87-102
5
TL;DR: Existing RESTful data services do not serve data analytics well because most of them are designed based on the underlying data schema rather than aligning with the requirements of data analytics.
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Abstract: Data service APIs provide uniform and filtered interfaces for data analysts to retrieve data. However, existing RESTful data services do not serve data analytics well because most of them are designed based on the underlying data schema rather than aligning with the requirements of data analytics. First, the API representations only support one-off communication, which lacks analytic semantics to guide analysts to continuously explore and retrieve data. Second, the current data service design does not support re-usage of data exploration processes and derived data generated from data analysts.
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References
•Book
Research Methodology: Methods and Techniques
C.R. Kothari
- 01 Jan 2004
TL;DR: The book as mentioned in this paper is intended to serve as a textbook for graduate and M.Phil. students ofResearch Methodology in all disciplines of various universities and it is hoped that the book shall provide guidelines to all interested in research studies of one sort or the other.
13.4K
•Book
Software Architecture in Practice
Len Bass,Paul Clements,Rick Kazman +2 more
- 01 Jan 1997
TL;DR: This second edition of this book reflects the new developments in the field and new understanding of the important underpinnings of software architecture with new case studies and the new understanding both through new chapters and through additions to and elaboration of the existing chapters.
Guidelines for conducting and reporting case study research in software engineering
Per Runeson,Martin Höst +1 more
TL;DR: This paper aims at providing an introduction to case study methodology and guidelines for researchers conducting case studies and readers studying reports of such studies, and presents recommended practices and evaluated checklists for researchers and readers of case study research.
Preliminary guidelines for empirical research in software engineering
Barbara Kitchenham,Shari Lawrence Pfleeger,Lesley M. Pickard,Peter W. Jones,D.C. Hoaglin,K. El Emam,J. Rosenberg +6 more
TL;DR: A preliminary set of research guidelines aimed at stimulating discussion among software researchers, intended to assist researchers, reviewers, and meta-analysts in designing, conducting, and evaluating empirical studies.