Data integration in a modular and parallel grid-computing workflow

In the past decades a wide range of complex processes have been developed to solve specific geospatial data integration problems. As a drawback these complex processes are often not sufficiently transferable and interoperable. We propose modularisation of the whole data integration process into reusable, exchangeable, and multi-purpose web services to overcome these drawbacks. Both a high-level split of the process into subsequent modules such as pre-processing and feature matching is discussed as well as another fine-granular split within these modules. Thereby complex integration problems can be addressed by chaining selected services as part of a geo-processing workflow. Parallelization is needed for processing massive amounts of data or complex algorithms. In this paper the two concepts of task and data parallelization are compared and examples for their usage are given. The presented work provides vector data integration within grid-computing workflows of the German Spatial Data Infrastructure Grid (SDI-Grid) project.BMB

An Adaptive Approach for Interlinking Georeferenced Data

International audienceThe resources published on the Web of data are often described by spatial references such as coordinates. The common data linking approaches are mainly based on the hypothesis that spatially close resources are more likely to represent the same thing. However, this assumption is valid only when the spatial references that are compared have been produced with the same positional accuracy, and when they actually represent the same spatial characteristic of the resources captured in an unambiguous way. Otherwise, spatial distance-based matching algorithms may produce erroneous links. In this article, we first suggest to formalize and acquire the knowledge about the spatial references, namely their positional accuracy, their geometric modeling, their level of detail, and the vagueness of the spatial entities they represent. We then propose an interlinking approach that dynamically adapts the way spatial references are compared, based on this knowledge

INFORMATION RELATED TO POSTAL FLOWS AND BIG DATA ANALYSIS POTENTIAL. THE CASE OF SPAIN

[EN] National Post Offices manage huge volumes of letters and parcels. Data associated to these flows are growing fast, with a great variety related to the diversity of postal products. The research described in this paper has classified all information flows of Correos, the Spanish National Post Office. In spite of the complexity of the current postal service portfolio, only four categories of matrices allow the classification of all postal information flows. Thanks to the migration towards new products, analyses with simple techniques will provide more and better information in the future, due to the structured nature of existing databases.Martinez Alvaro, O.; Nuñez Gonzalez, A. (2016). INFORMATION RELATED TO POSTAL FLOWS AND BIG DATA ANALYSIS POTENTIAL. THE CASE OF SPAIN. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 2267-2274. https://doi.org/10.4995/CIT2016.2015.4058OCS2267227

GeoCAM: A geovisual analytics workspace to contextualize and interpret statements about movement

This article focuses on integrating computational and visual methods in a system that supports analysts to identify extract map and relate linguistic accounts of movement. We address two objectives: (1) build the conceptual theoretical and empirical framework needed to represent and interpret human-generated directions; and (2) design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled computational methods to identify documents containing movement statements and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract interpret and map geographic movement references in context. Additionally analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface an analyst can explore the results provide feedback to improve those results pose queries against a database of route directions and interactively represent the route on a map

Collaborative business intelligence virtual assistant

The present-day business landscape necessitates novel methodologies that integrate intelligent technologies and tools capable of swiftly providing precise and dependable information for decision-making purposes. Contemporary society is characterized by vast amounts of accumulated data across various domains, which hold considerable potential for informing and guiding decision-making processes. However, these data are typically collected and stored by disparate and unrelated software systems, stored in diverse formats, and offer varying levels of accessibility and security. To address the challenges associated with processing such large volumes of data, organizations often rely on data analysts. Nonetheless, a significant hurdle in harnessing the benefits of accumulated data lies in the lack of direct communication between technical specialists, decision-makers, and business process analysts. To overcome this issue, the application of collaborative business intelligence (CBI) emerges as a viable solution. This research focuses on the applications of data mining and aims to model CBI processes within distributed virtual teams through the interaction of users and a CBI Virtual Assistant. The proposed virtual assistant for CBI endeavors to enhance data exploration accessibility for a wider range of users and streamline the time and effort required for data analysis. The key contributions of this study encompass: 1) a reference model representing collaborative BI, inspired by linguistic theory; 2) an approach that enables the transformation of user queries into executable commands, thereby facilitating their utilization within data exploration software; and 3) the primary workflow of a conversational agent designed for data analytics.Comment: MoMLeT+DS 2023: 5th International Workshop on Modern Machine Learning Technologies and Data Science, June 3, 2023, Lviv, Ukrain

Automatic integration of spatial data in viewing services

Geoportals are increasingly used for searching viewing and downloading spatial data. This study concerns methods to improve the visual presentation in viewing services. When spatial data in a viewing service are taken from more than one source there are often syntactic semantic topological and geometrical conflicts that prevent maps being fully consistent. In this study we extend a standard view service with methods to solve these conflicts. The methods are based on: (1) semantic labels of data in basic services (2) a rule-base in the portal layer and (3) integration methods in the portal layer. To evaluate the methodology we use a case study for adding historical borders on top of a base-map. The results show that the borders are overlaid on top of the map without conflicts and that a consistent map is generated automatically as an output. The methodology can be generalized to add other types of data on top of a base-map

Design, Field Evaluation, and Traffic Analysis of a Competitive Autonomous Driving Model in a Congested Environment

Recently, numerous studies have investigated cooperative traffic systems using the communication among vehicle-to-everything (V2X). Unfortunately, when multiple autonomous vehicles are deployed while exposed to communication failure, there might be a conflict of ideal conditions between various autonomous vehicles leading to adversarial situation on the roads. In South Korea, virtual and real-world urban autonomous multi-vehicle races were held in March and November of 2021, respectively. During the competition, multiple vehicles were involved simultaneously, which required maneuvers such as overtaking low-speed vehicles, negotiating intersections, and obeying traffic laws. In this study, we introduce a fully autonomous driving software stack to deploy a competitive driving model, which enabled us to win the urban autonomous multi-vehicle races. We evaluate module-based systems such as navigation, perception, and planning in real and virtual environments. Additionally, an analysis of traffic is performed after collecting multiple vehicle position data over communication to gain additional insight into a multi-agent autonomous driving scenario. Finally, we propose a method for analyzing traffic in order to compare the spatial distribution of multiple autonomous vehicles. We study the similarity distribution between each team's driving log data to determine the impact of competitive autonomous driving on the traffic environment

Enhancing State Estimator for Autonomous Race Car : Leveraging Multi-modal System and Managing Computing Resources

This paper introduces an innovative approach to enhance the state estimator for high-speed autonomous race cars, addressing challenges related to unreliable measurements, localization failures, and computing resource management. The proposed robust localization system utilizes a Bayesian-based probabilistic approach to evaluate multimodal measurements, ensuring the use of credible data for accurate and reliable localization, even in harsh racing conditions. To tackle potential localization failures during intense racing, we present a resilient navigation system. This system enables the race car to continue track-following by leveraging direct perception information in planning and execution, ensuring continuous performance despite localization disruptions. Efficient computing resource management is critical to avoid overload and system failure. We optimize computing resources using an efficient LiDAR-based state estimation method. Leveraging CUDA programming and GPU acceleration, we perform nearest points search and covariance computation efficiently, overcoming CPU bottlenecks. Real-world and simulation tests validate the system's performance and resilience. The proposed approach successfully recovers from failures, effectively preventing accidents and ensuring race car safety.Comment: arXiv admin note: text overlap with arXiv:2207.1223

A Multi-dimensional framework for adopting Physical Address System in a developing country

A Doctoral thesis submitted in fulfilment of the requirement for the degree of Doctor of Philosophy in Information Systems, Division of Information Systems School of Economic and Business Sciences Faculty of Commerce, Law and Management.Johannesburg, March 2017This thesis is about the adoption of an Information System (IS) at a country level. Information Systems literature addresses adoption of IS at an individual level, organisational level or national/country level. Each level of analysis has its own complexities. However, literature acknowledging these varied complexities has not been forth coming. That is, literature has more studies done at either individual or organisational, and hardly at national or country level. This thesis argues that the adoption of an information system (also referred to as an innovation) at country level is a multi-dimensional and multi-level phenomenon. Existing literature and previous studies have hardily addressed fully, this complexities and multi-dimensionalism, although it has been noted that countries experience and internalise the innovation adoption, as a social process, differently. The study was on a developing country adopting a Physical Address System (PAS), herein seen as an IS innovation. In this thesis, PAS is seen as a social system comprising of artefacts (digital and visual representations), physical world, residents and organisations as stakeholders. The goal of the study was to conceptualise a multi-dimensional framework for adopting a Physical Address System, in the context of a developing country. Since the thesis argument is that the adoption of IS at a country level is even more complex, varied theories were employed as lenses to tackle the various aspect of the study. These lenses are the Diffusion of Innovation, the Stakeholder Theory, Upper Echelon Theory and the Contextualist Approach. Following the interpretivist philosophy, a case study was employed as a research strategy, using Botswana as a developing country case. The research design included semi-structured interviews with stakeholders, observations, policy documents. The data was analysed, discussed, synthesised and interpreted using thematic framework analysis method. Informed by the empirical evidence and the existing literature, this thesis conceptualises that the adoption of the Physical Address System ought to be done sensitive to the developing country as a multi-dimensional social system. This multi-dimensional social system includes the roles of stakeholders, determinants of innovation and context. The contribution of the thesis is in four folds; theoretical, methodological, practical, and contextual. Theoretically, the thesis conceptualised a multi-dimensional framework for the adoption of the Physical Address System in a developing country. Methodologically, the thesis contributed by following an interpretive philosophy and a case study as appropriate for understanding the complexities of adopting an information system, employing a case. Practically, the thesis, through the framework, may inform practitioners with ways to adopt a physical address system. Contextually, the thesis gives insight into the uniqueness of a developing country adopting an information system. Keywords: Developing Country, Adoption, Physical Address System, Stakeholder Theory, Upper Echelon Theory, Diffusion of Innovation, ContextGR201