Krzysztof Janowicz

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The W3C Semantic Sensor Network Incubator group (the SSN-XG), as one of its activities, produced an OWL 2 ontology to describe sensors and observations the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe the capabilities of sensors, the measurement processes used and the resultant observations, and can be aligned(More)
In this paper, we develop a semantic annotation technique for location-based social networks to automatically annotate all places with category tags which are a crucial prerequisite for location search, recommendation services, or data cleaning. Our annotation algorithm learns a binary support vector machine (SVM) classifier for each tag in the tag space to(More)
The Geosciences and Geography are not just yet another application area for semantic technologies. The vast heterogeneity of the involved disciplines ranging from the natural sciences to the social sciences introduces new challenges in terms of interoperability. Moreover, the inherent spatial and temporal information components also require distinct(More)
This paper presents an overview of ongoing work to develop a generic ontology design pattern for observation-based data on the Semantic Web. The core classes and relationships forming the pattern are discussed in detail and are aligned to the DOLCE foundational ontology to improve semantic interoperability and clarify the underlying ontological commitments.(More)
Similarity measurement theories play an increasing role in GIScience and especially in information retrieval and integration. Existing feature and geometric models have proven useful in detecting close but not identical concepts and entities. However, until now none of these theories are able to handle the expressivity of description logics for various(More)
Feature types play a crucial role in understanding and analyzing geographic information. Usually, these types are defined, standardized, and controlled by domain experts and cover geographic features on the mesoscale level, e.g., populated places, forests, or lakes. While feature types also underlie most Location-Based Services (LBS), assigning a consistent(More)
Similarity measures have a long tradition in fields such as information retrieval, artificial intelligence, and cognitive science. Within the last years, these measures have been extended and reused to measure semantic similarity; i.e., for comparing meanings rather than syntactic differences. Various measures for spatial applications have been developed,(More)
Environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent over the past years. As consequence of these technological advancements, sensors are increasingly deployed to monitor our environment. The large variety of available sensor types with often incompatible protocols complicates the integration of sensors into(More)
Big Data, Linked Data, Smart Dust, Digital Earth, and e-Science are just some of the names for research trends that surfaced over the last years. While all of them address different visions and needs, they share a common theme: How do we manage massive amounts of heterogeneous data, derive knowledge out of them instead of drowning in information, and how do(More)