Descriptions of Spatial Operations – Recent Approaches and Community Feedback

Progress in the technical provision of spatial operations as loosely-coupled interoperable web services requires a corresponding development of standardisation in their description. Operation discovery, usage and interpretation of results require more information on what a spatial operation does than just their input and output interface specifications. Geooperators and WPS profiles have been proposed for addressing operation descriptions for different operational perspectives. Geooperators have been developed mostly for supporting operation discovery through defining alternative perspectives such as a geodata, legacy GIS, formal or technical perspective. These act as filters in the discovery process. WPS profiles provide a hierarchical approach to define the concept underlying an operation and, in more specific profiles, the syntactic interface of the operation. Both approaches require community engagement for reaching an agreed set of documented operations. We report on a discussion of these approaches and the larger framework of a geoprocessing community platform from a workshop held at the AGILE International Conference on Geographic Information Science in Lisbon in 2015. At the workshop two presentations provided insights in different contexts of use of online geoprocessing. After detailed introductions to the two operation descriptions approaches, two breakout sessions were held. In the breakout sessions operation descriptions and technical developments in the field were discussed. This article summarizes the discussion that took place at the workshop with the intention to involve the extended community in the discourse on operation descriptions

Bridging the Gap Between Traditional Metadata and the Requirements of an Academic SDI for Interdisciplinary Research

Metadata has long been understood as a fundamental component of any Spatial Data Infrastructure, providing information relating to discovery, evaluation and use of datasets and describing their quality. Having good metadata about a dataset is fundamental to using it correctly and to understanding the implications of issues such as missing data or incorrect attribution on the results obtained for any analysis carried out. Traditionally, spatial data was created by expert users (e.g. national mapping agencies), who created metadata for the data. Increasingly, however, data used in spatial analysis comes from multiple sources and could be captured or used by nonexpert users – for example academic researchers ‐ many of whom are from non‐GIS disciplinary backgrounds, not familiar with metadata and perhaps working in geographically dispersed teams. This paper examines the applicability of metadata in this academic context, using a multi‐national coastal/environmental project as a case study. The work to date highlights a number of suggestions for good practice, issues and research questions relevant to Academic SDI, particularly given the increased levels of research data sharing and reuse required by UK and EU funders

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- that of automatically learning problem-specific features. With this new paradigm, every problem in computer vision is now being re-examined from a deep learning perspective. Therefore, it has become important to understand what kind of deep networks are suitable for a given problem. Although general surveys of this fast-moving paradigm (i.e. deep-networks) exist, a survey specific to computer vision is missing. We specifically consider one form of deep networks widely used in computer vision - convolutional neural networks (CNNs). We start with "AlexNet" as our base CNN and then examine the broad variations proposed over time to suit different applications. We hope that our recipe-style survey will serve as a guide, particularly for novice practitioners intending to use deep-learning techniques for computer vision.Comment: Published in Frontiers in Robotics and AI (http://goo.gl/6691Bm

Object-Oriented Paradigms for Modelling Vascular\ud Tumour Growth: a Case Study

Motivated by a family of related hybrid multiscale models, we have built an object-oriented framework for developing and implementing multiscale models of vascular tumour growth. The models are implemented in our framework as a case study to highlight how object-oriented programming techniques and good object-oriented design may be used effectively to develop hybrid multiscale models of vascular tumour growth. The intention is that this paper will serve as a useful reference for researchers modelling complex biological systems and that these researchers will employ some of the techniques presented herein in their own projects

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

ISML: an interface specification meta-language

In this paper we present an abstract metaphor model situated within a model-based user interface framework. The inclusion of metaphors in graphical user interfaces is a well established, but mostly craft-based strategy to design. A substantial body of notations and tools can be found within the model-based user interface design literature, however an explicit treatment of metaphor and its mappings to other design views has yet to be addressed. We introduce the Interface Specification Meta-Language (ISML) framework and demonstrate its use in comparing the semantic and syntactic features of an interactive system. Challenges facing this research are outlined and further work proposed