Consistent updating of databases with marked nulls

Abstract

Efficient consistency maintenance of incomplete and dynamic real-life databases is a quality label for further data analysis. In prior work, we tackled the generic problem of database updating in the presence of tuple generating constraints from a theoretical viewpoint. The current paper considers the usability of our approach by (a) introducing incremental update routines (instead of the previous from-scratch versions) and (b) removing the restriction that limits the contents of the database to fit in the main memory. In doing so, this paper offers new algorithms, proposes queries and data models inviting discussions on the representation of incompleteness on databases. We also propose implementations under a graph database model and the traditional relational database model. Our experiments show that computation times are similar globally but point to discrepancies in some steps.

Graph rewriting rules for RDF database evolution: optimizing side-effect processing

“…To generalize and abstract consistent updating methods, different works have used formalisms such as tree automata or grammars for XML (Schwentick, 2007 as a survey) or first-order logic for relational (such as Winslett, 1990) and, currently, graph databases (Chabin et al , 2019b; Flouris et al , 2013). In spite of the importance of graphs in RDF and ontology representation, the use of formal graph rewriting techniques to model RDF evolutions is still mildly studied in this context.…”

“…As in Chabin et al (2019b), we consider updates as changes in the world rather than as a revision in our knowledge of the world (Hansson, 2016, as an overview for revision). In such update context, the chase procedure is usually associated to the generation of side effects imposing extra insertions or deletions (w.r.t.…”

“…The approach in Maillot et al (2014) differs from ours, by proposing a semantic measure based on the difference between original and updated RDF sub-graph. Both Chabin et al (2019b) and Goasdoué et al (2013) consider RDF updating methods, but the former goes deeper in the study of null values. A parallel can be done between saturation in Goasdoué et al (2013), the chase in Chabin et al (2019b) and Flouris et al (2013) and SetUp .…”

“…Both Chabin et al (2019b) and Goasdoué et al (2013) consider RDF updating methods, but the former goes deeper in the study of null values. A parallel can be done between saturation in Goasdoué et al (2013), the chase in Chabin et al (2019b) and Flouris et al (2013) and SetUp . Chabin et al (2019b); Flouris et al (2013); and Goasdoué et al (2013) offer home-made procedures to implement their methods: Goasdoué et al (2013) deals only with the RDF instance constraints (Figure 2); in Chabin et al (2019b) and Flouris et al (2013), constraints are user’s tuple-generating dependencies.…”

“…Chabin et al (2019b); Flouris et al (2013); and Goasdoué et al (2013) offer home-made procedures to implement their methods: Goasdoué et al (2013) deals only with the RDF instance constraints (Figure 2); in Chabin et al (2019b) and Flouris et al (2013), constraints are user’s tuple-generating dependencies. Incomplete information and updates are the focus of Chabin et al (2019b). Schema evolution is mentioned in Flouris et al (2013) and Goasdoué et al (2013).…”