Preserving Queries within Relational Databases

Author: Somaia Suleiman R Alaofe

Alaofe, Somaia Suleiman R, 2018 Preserving Queries within Relational Databases, Flinders University, College of Science and Engineering

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Most scientific research is stored in digital formats; however, with technology obsolescence, important resources for future research can be lost. Relational databases (RDBs), including component tables, relationships, and queries, are an important digital format for preserving research results. Therefore, preserving databases for a long time, regardless of any software or hardware issues, is critical. Previous studies have developed database preservation but have focused on preserving data, relationships, and keys rather than reports, pages, and queries within a database.

Therefore, this study proposes a strategy for long-term digital preservation of queries within RDBs because queries are a major component of providing accurate, relevant data that lead to better insights, better decision making, and improved business. This research surveyed literature on RDB preservation and identified a gap in query preservation. There are a range of challenges in place regarding the variation of manipulation languages between RDBs, and four database management systems were surveyed to determine how queries can be manipulated on each platform.

The proposed solution analyses relational algebra trees to preserve queries and researches eXtensible Markup Language (XML) to present relational algebra trees in XML format. Therefore, this research suggests an optimal approach to query preservation in various RDB platforms. A preservation methodology for queries is proposed based on converting all data manipulation language representation among various RDBs into one format: an XML file. This XML file does not preserve the data manipulation language itself but rather the relational algebra trees of queries. Thus, the logic of queries will be preserved in both human and computer readable formats.

Keywords: Database preservation, Digital preservation, Queries preservation

Subject: Computer Science thesis

Thesis type: Masters
Completed: 2018
School: College of Science and Engineering
Supervisor: Dr Denise de Vries