Exploring Cultural Heritage Resources in a 3D Collaborative Environment

Cultural heritage is a complex and diverse concept, which brings together a wide domain of information. Resources linked to a cultural heritage site may consist of physical artefacts, books, works of art, pictures, historical maps, aerial photographs, archaeological surveys and 3D models. Moreover, all these resources are listed and described by a set of a variety of metadata specifications that allow their online search and consultation on the most basic characteristics of them. Some examples include Norma ISO 19115, Dublin Core, AAT, CDWA, CCO, DACS, MARC, MoReq, MODS, MuseumDat, TGN, SPECTRUM, VRA Core and Z39.50. Gateways are in place to fit in these metadata standards into those used in a SDI (ISO 19115 or INSPIRE), but substantial work still remains to be done for the complete incorporation of cultural heritage information. Therefore, the aim of this paper is to demonstrate how the complexity of cultural heritage resources can be dealt with by a visual exploration of their metadata within a 3D collaborative environment. The 3D collaborative environments are promising tools that represent the new frontier of our capacity of learning, understanding, communicating and transmitting culture

Improving the performance of GIS/spatial analysts though novel applications of the Emotiv EPOC EEG headset

Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow

Usability dimensions in collaborative GIS

Collaborative GIS requires careful consideration of the Human-Computer Interaction (HCI) and Usability aspects, given the variety of users that are expected to use these systems, and the need to ensure that users will find the system effective, efficient, and enjoyable. The chapter explains the link between collaborative GIS and usability engineering/HCI studies. The integration of usability considerations into collaborative GIS is demonstrated in two case studies of Web-based GIS implementation. In the first, the process of digitising an area on Web-based GIS is improved to enhance the user's experience, and to allow interaction over narrowband Internet connections. In the second, server-side rendering of 3D scenes allows users who are not equipped with powerful computers to request sophisticated visualisation without the need to download complex software. The chapter concludes by emphasising the need to understand the users' context and conditions within any collaborative GIS project. © 2006, Idea Group Inc

Collaborative geographic visualization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe present document is a revision of essential references to take into account when developing ubiquitous Geographical Information Systems (GIS) with collaborative visualization purposes. Its chapters focus, respectively, on general principles of GIS, its multimedia components and ubiquitous practices; geo-referenced information visualization and its graphical components of virtual and augmented reality; collaborative environments, its technological requirements, architectural specificities, and models for collective information management; and some final considerations about the future and challenges of collaborative visualization of GIS in ubiquitous environment

Multimodal and multidimensional geodata interaction and visualization

This PhD proposes the development of a Science Data Visualization System, SdVS, that analyzes and presents different kinds of visualizing and interacting techniques with Geo-data, in order to deal with knowledge about Geo-data using GoogleEarth. After that, we apply the archaeological data as a case study, and, as a result, we develop the Archaeological Visualization System, ArVS, using new visualization paradigms and Human-Computer-Interaction techniques based on SdVS. Furthermore, SdVS provides guidelines for developing any other visualization and interacting applications in the future, and how the users can use SdVS system to enhance the understanding and dissemination of knowledge

Integrating Decision-Making Support in Geocollaboration Tools

info:eu-repo/semantics/publishedVersio

Social media mining under the COVID-19 context: Progress, challenges, and opportunities

Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and repro�ducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies

A collaborative, semantic and context-aware search engine

Search engines help people to find information in the largest public knowledge system of the world: the Web. Unfortunately its size makes very complex to discover the right information. The users are faced lots of useless results forcing them to select one by one the most suitable. The new generation of search engines evolve from keyword-based indexing and classification to more sophisticated techniques considering the meaning, the context and the usage of information. We argue about the three key aspects: collaboration, geo-referencing and semantics. Collaboration distributes storage, processing and trust on a world-wide network of nodes running on users’ computers, getting rid of bottlenecks and central points of failures. The geo-referencing of catalogued resources allows contextualisation based on user position. Semantic analysis lets to increase the results relevance. In this paper, we expose the studies, the concepts and the solutions of a research project to introduce these three key features in a novel search engine architecture.213-21

DART: the distributed agent based retrieval toolkit

The technology of search engines is evolving from indexing and classification of web resources based on keywords to more sophisticated techniques which take into account the meaning and the context of textual information and usage. Replying to query, commercial search engines face the user requests with a large amount of results, mostly useless or only partially related to the request; the subsequent refinement, operated downloading and examining as much pages as possible and simply ignoring whatever stays behind the first few pages, is left up to the user. Furthermore, architectures based on centralized indexes, allow commercial search engines to control the advertisement of online information, in contrast to P2P architectures that focus the attention on user requirements involving the end user in search engine maintenance and operation. To address such wishes, new search engines should focus on three key aspects: semantics, geo-referencing, collaboration/distribution. Semantic analysis lets to increase the results relevance. The geo-referencing of catalogued resources allows contextualisation based on user position. Collaboration distributes storage, processing, and trust on a world-wide network of nodes running on users’ computers, getting rid of bottlenecks and central points of failures. In this paper, we describe the studies, the concepts and the solutions developed in the DART project to introduce these three key features in a novel search engine architecture