Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής

Πολυτεχνική Σχολή - Πανεπιστήμιο Ιωαννίνων

Σεμινάριο Τμήματος με τίτλο “The Context Model: A graph database model”

Περιγραφή

Στο πλαίσιο της διοργάνωσης των σεμιναρίων του τμήματος θα πραγματοποιηθεί την Τρίτη 25/6/2024 και ώρα 12:00, ομιλία με τίτλο «The Context Model: A graph database model» στην αίθουσα Σεμιναρίων του ΤΜΗΥΠ. Ομιλητής θα είναι ο  κ. Nicolas Spyratos, Prof. Emeritus, University Paris-Saclay, France.

ΠΕΡΙΛΗΨΗ

We propose a novel database model whose basic structure is a labeled, directed, acyclic graph with a single root, in which the nodes represent the data sets of an application, and the edges represent functional relationships among the data sets. We call such a graph an application context or simply context. The query language of a context consists of two types of queries, traversal queries and analytic queries. Both types of queries are defined using a simple functional algebra whose operations are functional restriction, composition of functions, pairing of functions and Cartesian product. Roughly speaking, traversal queries parallel relational algebra queries, whereas analytic queries parallel SQL Group-by queries. In other words, in our model, traversal queries and analytic queries are both defined in the same formal framework – in contrast to the relational model, where analytic queries are defined outside the relational algebra. Therefore, a distinctive feature of our model is that it is a model for data management and data analytics within the same formal framework.  We demonstrate the expressive power of our model by showing: (a) how a relational database can be defined as a view over a context, with the context playing the role of an underlying semantic layer; (b) how an analytic query over a context can be rewritten at two orthogonal levels: at the level of the traversal queries that do the grouping and measuring, and at the level of the analytic query itself; and (c) how a context can be used as a user-friendly interface for querying relations and analyzing relational data.

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