The Gremlin Graph Traversal Machine and Language

Gremlin is a graph traversal machine and language designed, developed, and distributed by the Apache TinkerPop project. Gremlin, as a graph traversal machine, is composed of three interacting components: a graph $G$, a traversal $\Psi$, and a set of traversers $T$. The traversers move about the graph according to the instructions specified in the traversal, where the result of the computation is the ultimate locations of all halted traversers. A Gremlin machine can be executed over any supporting graph computing system such as an OLTP graph database and/or an OLAP graph processor. Gremlin, as a graph traversal language, is a functional language implemented in the user's native programming language and is used to define the $\Psi$ of a Gremlin machine. This article provides a mathematical description of Gremlin and details its automaton and functional properties. These properties enable Gremlin to naturally support imperative and declarative querying, host language agnosticism, user-defined domain specific languages, an extensible compiler/optimizer, single- and multi-machine execution models, hybrid depth- and breadth-first evaluation, as well as the existence of a Universal Gremlin Machine and its respective entailments.Comment: To appear in the Proceedings of the 2015 ACM Database Programming Languages Conferenc

A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space-Time Cubes

International audienceWe present the generalized space-time cube, a descriptive model for visualizations of temporal data. Visualizations are described as operations on the cube, which transform the cube's 3D shape into readable 2D visualizations. Operations include extracting subparts of the cube, flattening it across space or time or transforming the cubes geometry and content. We introduce a taxonomy of elementary space-time cube operations and explain how these operations can be combined and parameterized. The generalized space-time cube has two properties: (1) it is purely conceptual without the need to be implemented, and (2) it applies to all datasets that can be represented in two dimensions plus time (e.g. geo-spatial, videos, networks, multivariate data). The proper choice of space-time cube operations depends on many factors, for example, density or sparsity of a cube. Hence, we propose a characterization of structures within space-time cubes, which allows us to discuss strengths and limitations of operations. We finally review interactive systems that support multiple operations, allowing a user to customize his view on the data. With this framework, we hope to facilitate the description, criticism and comparison of temporal data visualizations, as well as encourage the exploration of new techniques and systems. This paper is an extension of Bach et al.'s (2014) work

A case study of business intelligence applications for business users

This research is conducted in two parts, with the first part reviewing the standard industry approach to providing organisations with business intelligence (BI) architecture. The discussion begins with a brief history of the evolution of data warehouses and business intelligence (DW/BI) systems. The generic approach to developing a DW/BI is described and the interfaces and features of BI applications are explored as to how they support the various user roles within an organisation e.g. executive, business user and business analyst. The discussion is presented using references to the Zachman Framework. The second part of the research focuses on a case study examining an organisation's implementation of a bespoke BI solution which is supporting its business managers with decision support, reporting and analysis. Where today's business intelligence is about giving business users the tools to get the information they need out of the data warehouse and thus reducing the reliance on IT departments, the bespoke solution studied puts the reliance on IT staff to support their business intelligence requirements. The BI requirements are compared and contrasted against the features of third party BI tools to reach a conclusion as to whether they support the reporting needs of the planning group in the case study or whether their needs are so specific that a bespoke solution is the best option and thus reliance on IT departments is still necessary to support the delivery of business intelligence. The findings from the first part of the research are the view that for the successful development of BI applications the BI user's needs should be addressed from the requirements stage, and the development of BI applications should run as a parallel activity alongside the data warehouse development activities. The BI applications should be developed by BI developers who have knowledge of the business, rather than technical IT staff. This view is supported by leading DW/BI authors such Kimball et al. (2008). The research also found the needs of the BI application users can be analysed by grouping them into one of five classifications of user - Tourists, Farmers, Explorers, Miners and Operators and that different user interfaces are needed to support their needs. The case study in the second part of the research found that the implementation of the DW/BI system in SAP using SAP BEx software fails to provide planning staff with BI applications that meet with all their reporting and analysis needs and has therefore led to the development of bespoke applications. The findings suggest that this may be because the planning staff were not involved at the scoping and planning stage of developing the DW/BI. The investigations found that most of the features in the bespoke BI system could be developed using a third party solution and that they are available in the SAP family of products. The level of expertise needed to develop the features ranged from easy to technical. The adoption of a third party tool could be used to develop the reports by the BI application developers identified by Kimball et al. (2008) and provide the planning managers with an intuitive and flexible user interface that can be easily customised and maintained. It was also found that SAP BusinessObject's Crystal Reports provide a rich user interface that is easy to use to support most of the BI features

Doctor of Philosophy

dissertationRecent advancements in mobile devices - such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID) - have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data mining, which leads to the integration of GVis and KDD. Case studies using three movement datasets (personal travel data survey in Lexington, Kentucky, wild chicken movement data in Thailand, and self-tracking data in Utah) demonstrate the potential of the system to extract meaningful patterns from the otherwise difficult to comprehend collections of space-time trajectories