Linked Data for Transaction Based Enterprise Interoperability

Interoperability is of major importance in B2B environments. Starting with EDI in the ‘80s, currently interoperability relies heavily on XML-based standards. Although having great impact, still issues remain to be solved for improving B2B interoperability. These issues include lack of dynamics, cost of implementations, adoption and cross-industry exchange. Linked Data (part of the Semantic Web) technology, although originally not intended for the B2B domain, holds the promise of overcoming some of these issues. This paper explores the potential of linked data technology within a B2B context by introducing and studying six scenarios for combining from light to heavy weight ‘traditional’ standards with Linked Data technology. This research shows that using Linked Data technology has most potential for specifying semantics formally. This provides the ‘best of both worlds’ solution, in which legacy systems remain unaltered, and developers are supported in (semi) automated generation of transformation schema’s to overcome different standards

Semantic web implementation model in enterprises

The Semantic Web is an important challenge for today's Web usage. The progressive transformation of the Web based on documents into the Web based on data will bring up a Web scale database. Given that the Enterprise Semantic Web is still a less explored subject, this article proposes an Implementation Model that helps the introduction of the technology and the evaluation of its' impact in the applications used and tasks performed

Big Data Computing for Geospatial Applications

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms

Spatial and temporal resolution of sensor observations

Beobachtung ist ein Kernkonzept der Geoinformatik. Beobachtungen dienen bei Phänomenen wie Klimawandel, Massenbewegungen (z. B. Hangbewegungen) und demographischer Wandel zur Überwachung, Entwicklung von Modellen und Simulation dieser Erscheinungen. Auflösung ist eine zentrale Eigenschaft von Beobachtungen. Der Gebrauch von Beobachtungen unterschiedlicher Auflösung führt zu (potenziell) unterschiedlichen Entscheidungen, da die Auflösung der Beobachtungen das Erkennen von Strukturen während der Phase der Datenanalyse beeinflusst. Der Hauptbeitrag dieser Arbeit ist eine entwickelte Theorie der raum- und zeitlichen Auflösung von Beobachtungen, die sowohl auf technische Sensoren (z. B. Fotoapparat) als auch auf menschliche Sensoren anwendbar ist. Die Konsistenz der Theorie wurde anhand der Sprache Haskell evaluiert, und ihre praktische Anwendbarkeit wurde unter Einsatz von Beobachtungen des Webportals Flickr illustriert