A semantic trajectory data warehouse for improving nursing productivity
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RESEARCH
A semantic trajectory data warehouse for improving nursing productivity Georgia Garani* and George K. Adam
Abstract A Trajectory Data Warehouse is a central repository of large amount of data focusing on moving objects, which have been collected and integrated from multiple sources with spatial and temporal dimensions as the main metrics of analysis. By adding semantic-related contextual information, it is converted to a Semantic Trajectory Data Warehouse. It transforms raw trajectories to valuable information that can be utilized for decision-making purposes in ubiquitous applications. Human recourses management is a domain that may benefit significantly from semantic trajectory data warehouses. In particular, employees working shifts can be considered as trajectories. In this work, standard data warehousing tools are used to store data about nursing personnel shifts as trajectories of moving persons. The conceptual and logical modelling of the semantic trajectory data warehouse is developed. The objective is the observation, management and scheduling of nurses’ shifts data by the computation of OLAP operations over them. A prototype implementation has also been realized to illustrate the functionality of the proposed model. The produced results prove the efficiency in improving nursing productivity. Keywords: Data warehouse, Conceptual modelling, Logical modelling, Moving object, Trajectory Introduction Traditional database techniques are not capable of dealing with vast amount of spatiotemporal data produced constantly by various GPS-enabled devices such as smartphones, watches, and laptops. Towards this direction, new database models have been emerged for the management, maintenance and querying of mobility data, often called trajectory data. Trajectory data express the evolution of the position of a moving object. A moving object is an object whose position changes frequently over a period of time in order to achieve a given goal. This position is perceived as a point in geometry. Modelling and analysing trajectory data are still challenging due to their semantics heterogeneity. However, the analysis of this kind of data is essential for providing useful insights concerning different real-application subjects, for instance human behavior and activity. The first semantic conceptual model to deal with trajectory data is introduced in [1]. Trajectory data warehouses (TDWs) have been introduced relatively recently for the *Correspondence: [email protected] University of Thessaly, Gaiopolis, 41500 Larissa, Greece © Springer Nature Switzerland AG 2020.
support of mobility analysis [2, 3]. A semantic TDW is a data warehouse specially design for storing the semantic information of a trajectory object within a temporal period for a particular purpose. In this paper, a semantic TDW is used for monitoring nursing productivity. Nursing productivity is an essential component of successful health care systems. Productivity is defined as staff perception of effectiveness, eff
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