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Benefits of integrating meta data into a context model

12.3.2005, Kauai, Hawai'i, USA. Benefits of integrating meta data into a context model. Nicola Hönle, Uwe-Philipp Käppeler, Daniela Nicklas , Thomas Schwarz, Matthias Grossmann. Nexus Center of Excellence 627: Spatial World Models for Mobile Context-Aware Applications.

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Benefits of integrating meta data into a context model

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  1. 12.3.2005, Kauai, Hawai'i, USA Benefits of integrating meta data into a context model Nicola Hönle, Uwe-Philipp Käppeler, Daniela Nicklas, Thomas Schwarz, Matthias Grossmann Nexus Center of Excellence 627: Spatial World Models for Mobile Context-Aware Applications University of Stuttgart Germany

  2. meta data What is meta data? application application data meta data = data about (operational) data But: distinction is application-specific!

  3. What is meta data? Some opinions ...

  4. Overview • Meta data in context models • The Nexus Platform (short!) • Integrating meta data in the Nexus Platform • Benefits • Data exchange, query processing • Conclusion

  5. Application State Update(id, value) query (filter) Context Models Applications Context Model Sensors (Modeling) Update(id, value) Physical World

  6. Meta data in context models • Operational data: context information • Meta data: • data to instances of data (not to the schema) • characteristics of data • circumstances of data gathering • Types (not disjoint): • system generated • technical restrictions • technically measurable • authorship, data source • cost • ...

  7. Advantages • Hints about the data quality • reliability, precision, consistency, age, ... • Sensor fusion and data cleansing • on the fly calculation • tailored to application needs • Increases flexibility • integration of context models • different application types

  8. The Nexus Vision: Federated Context Models “Smart Factory” VirtualPostIts Multimodal Navigation City Guide context-aware applications ... global context model Federation data from billions of sensors local context models information spaces ... Digital Libraries WWW

  9. The Nexus Platform • Supports various kinds of context aware applications • Object-based data model (objects and attributes) • Local context models are stored on context servers • Context servers support a given interface • Augmented World Query Language (AWQL): • simple spatial object selection and filtering • Augmented World Modeling Language (AWML) • serialization of context data objects

  10. Area Service Register Federation WWW (ext. data) AWQL/AWML Context- Server Context- Server Context- Server Context- Server Context- Server Sensor Sensor Sensor Context- Server Context- Server GeoDB Nexus Platform Architecture Application Application Application federated global context model local context models  Why different context servers? See our PerCom´05 paper.

  11. Benefits of integrating meta data • Finding resources: • meta data about local context models (Area Service Register) • Better data selection: • better specifying kinds of context data (Application, Federation) • Trust and data quality: • optimize results, favor certain data providers (Application, Federation) • Sensor fusion: • higher level sensor fusion across several data providers (Context Servers, Federation) • Implicit usage in data processing: • application profiles simplify application queries (Federation)

  12. meta data about data objects meta data about attribute values accuracy: ±5 Multiple attribute instances measurementTime: 08:00:00 accuracy: ±1 value: 25.0 measurementTime: 08:30:00 accuracy: ±0.5 author: Alice gatheringTime: 2004-08-08 Which meta data do we use? meta data about data providers AreaServiceRegister object identifier value: ID1234 register (AugmentedArea, ObjectTypes) type value: TemperatureSensor position ContextServer value: 49N 9E temperature value: 23.0 local context model

  13. Augmented World Modeling Language (AWML) awml nexusobject attribute value attribute value nexusobject nexusobject nexusobject

  14. AWML: data exchange with meta data <awml> <nexusobject> <NOL> <value> ID1234 </value> </NOL> <type> <value> TemperatureSensor </value> </type> <position> <value> 49N 9E </value> <meta> <accuracy> 5 </accuracy> </meta> </position> ... <meta> <author> Alice </author> <gatheringTime> 2004-08-08 </gatheringTime> </meta> </nexusobject> <nexusobject> ... </nexusobject> </awml> Attribute value with meta data Object meta data

  15. AWML: data exchange with meta data <awml> <nexusobject> <NOL> <value> ID1234 </value> </NOL> ... <temperature> <value> 23.0 </value> <meta> <measurementTime> 08:00:00 </measurementTime> <accuracy> 1 </accuracy> </meta> </temperature> <temperature> <value> 23.0 </value> <meta> <measurementTime> 08:30:00 </measurementTime> <accuracy> 0.5 </accuracy> </meta> </temperature> ... </nexusobject> ... </awml> Multiple attribute instances

  16. Augmented World Query Language (AWQL) awql restriction equal, less, greater and, or, not spatial: within, overlap temporal: before, after, ... filter: include or exclude attribute list

  17. Step 1: provider selection (restrictions on type and position)  context server list Step 2: object selection (restrictions)  result set AWQL: query processing <awql> <restriction> <and> <equal> <target> type.value </target> <referenceValue> TemperaturSensor </referenceValue> </equal> <within> <target> pos.value </target> <referenceValue> SomeArea </referenceValue> </within> <less> <target> temperature.value </target> <referenceValue> 24.0 </referenceValue> </less> <temporalAfter> <target> temperature.meta.measurementTime </target> <referenceValue> 08:12:00 </referenceValue> </temporalAfter> </and> </restriction> <include> ... </include> <awql>

  18. Step 3: Attribute instance selection (include)  return set AWQL: query processing (cont.) <awql> <restriction> ... </restriction> <include> <target> NOL.value </target> </include> <include> <target> temperature </target> <include> <target> value </target> <target> meta.accuracy </target> </include> <restriction> <temporalAfter> <target> meta.measurementTime </target> <referenceValue> 08:12:00 </referenceValue> </temporalAfter> </restriction> </include> </awql>

  19. Implementation Issues • XML: optional elements, multi-elements • Java: generic result set classes (multiple attribute instances, ...) • relational DBMS: decomposed storage model

  20. Conclusion • Extension of data model (AWM), serialization (AWQL) and query language (AWQL) to cope with meta data • Current usage: • selection of data sources (providers) • selection of objects • Future work: further usage of meta data for • sensor fusion algorithms • selection of providers based on trust metrics • assessment of data quality • application profiles • Important question: how trustworthy are the meta data?

  21. Mahalo! Questions?

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