Semantic Observation Integration
2. Observation Systems and their Integration
2.1. VGI and other Types of User-Generated Content
|Content/Contribution||Explicitly volunteered||Implicitly volunteered|
|Explicitly geographic||Volunteered Geographic Information (VGI), e.g., Open Street Map||User-generated geographic content (UGGC), e.g., place-related Tweets|
|Implicitly geographic||Volunteered information (VI), e.g., geo-coded Wikipedia entries||Generic user-generated content (UGC)|
2.2. Citizen-Based Geo-Sensor Networks
|Nervous System||VGI Sensing||Remote Sensing|
|Sensation||Publicly available VGI is detected, filtered and organized according to the VGI virtual sensor’s specification.||Waves are detected and digitized by a satellite-mounted sensor, i.e. camera and series of remote sensing images are created according to the image sensor’s specifications.|
|Perception||Patterns are found in results, and events and situations are identified thanks to prior knowledge.||Signals with specific characteristics are detected in image series, leading to the identification of events.|
|Attention||Alerting mechanisms are triggered according to context.|
2.3. Example Forest Fire Observation Systems
2.4. Design of the Integration Approach
- • We can only move from the inner layers to the outside.
- • The information becomes more specialized with distance to the center, i.e., application specific context is introduced increasingly.
- • Information can only be integrated on a shared layer.
3. Engineering Formal Systems with Ontologies and Algebras
3.1. Ontologies and Ontological Commitments
3.2. Algebras and Algebraic Specifications
4. Formalization of the Integration Approach
|data||Algebraic data types (which, for the purpose of this work, can be seen as synonyms to ADTs) introduce types by specifying a constructor function. The keyword (data) is followed by a type name, an equal sign and the constructor function. The first element of this function is its name. Constructor functions can be enumerated using the ‘|’ symbol. Lists can be typed using the construct “” (also nested).|
|data Value = Measure Float Unit | … | Image [[Pixel]]|
|type||Type synonyms give previously defined types a new name. They are used for clarifying the meaning of existing types in new contexts.|
|type Hotspot = ObservationResult|
|class||Type classes collect types that share certain behavior. This behavior is defined by a selector function. The keyword is followed by the name of the type class and its parameters. Selection functions are specified after the keyword ‘where’.|
|class STIMULI quality entity agent where|
|perceive :: quality entity → agent → agent|
|instance||Instances connect algebraic data types to type classes. In an instantiation, axioms specify how the algebraic data types implement the behavior specified for the type class. The keyword is followed by the name of the type class and the assignment of its parameters to algebraic data types.|
|instance OBSERVATIONS VGI Volunteer VGISensor where ...|
|… =>||Contexts assert constraints on algebraic data types, may by assigned to the parameters of a type class. Constraints are places after the keyword class and end with the|
|class STIMULI quality entity agent => OBSERVATIONS quality entity agent|
|name:: p1 → p2 …||Functions are introduced by their signature, which consists of a function name, the symbol ‘::’ and the function parameters (at least one), separated by ‘->’. The last parameter specifies the output.|
|tell :: agent -> ObservationResult|
|The behavior of a function is then specified by equations.|
|tell vgiSensor = vsResult vgiSensor|
4.1. Algebraic Specification of the Abstract Data Types for Earth Observation
4.2. Generating Value-Added Information
4.3. Alignment with DOLCE-Ultra-Light
- • Agents: agentive physical objects, including those that can carry out observations, i.e. that serve as sensors, and tell about the results;
- • Stimuli: enabling agents to perceive qualities, i.e., properties of some entity; and
- • Observations: Given an available stimulus, the process of an agent generating an observation result through perception.
- • the CONAVI analyzer finally can observe hotspots out of the data coming from a VGI sensor:
- instance OBSERVATIONS Hotspot VGISensor CONAVIanalyser where …
- • the CONAVI analyzer can observe forest fires out of the previously identified hotspots:
- instance OBSERVATIONS ForestFire CONAVIanalyser CONAVIanalyser …
- • the CONAVI clusterer can observe clusters out of the previously identified forest fires:
- instance OBSERVATIONS Hotspot CONAVIanalyser CONAVIclusterer...
- • the CONAVI clusterer can observe forest fire clusters out of the previously identified clusters:
- instance OBSERVATIONS ForestFire CONAVIclusterer CONAVIclusterer...
- • the earth observation satellite can observe images:
- instance OBSERVATIONS ElectromagneticRadiation EarthSurface EOSatellite …
- • the FFIS can observe hotspots within the data coming from the satellite:
- instance OBSERVATIONS Hotspot EarthObservationSatellite FFIS …
- • the FFIS can observe forest fires out of the previously identified hotspots:
- instance OBSERVATIONS ForestFire FFIS FFIS …
4.4. Common Access to Value-Added Information
5. Discussion of the Integration Approach
5.1. Generalizability of the Overall Approach
5.2. Potential and Future Work
6. Conclusions and Outlook
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Schade, S.; Ostermann, F.; Spinsanti, L.; Kuhn, W. Semantic Observation Integration. Future Internet 2012, 4, 807-829. https://doi.org/10.3390/fi4030807
Schade S, Ostermann F, Spinsanti L, Kuhn W. Semantic Observation Integration. Future Internet. 2012; 4(3):807-829. https://doi.org/10.3390/fi4030807Chicago/Turabian Style
Schade, Sven, Frank Ostermann, Laura Spinsanti, and Werner Kuhn. 2012. "Semantic Observation Integration" Future Internet 4, no. 3: 807-829. https://doi.org/10.3390/fi4030807