1. Tarek Sboui Yvan Bédard Jean Brodeur Thierry Badard Presented by: Yvan Bédard A Conceptual Framework to Support Semantic Interoperability of Geospatial Datacubes

2. 2 Presentation outline Introduction Challenges Proposed approach –Semantic heterogeneity conflicts in geospatial datacubes –Framework to support semantic interoperability between geospatial datacubes –Semantic Model Conclusion

3. 3 Data Warehouses Extract Transform Load Metadata Data Sources Clients (Front-End Tools) Used by Datacube Data Marts transactional BD other sources DBMS OLAP server Datacubes Introduction: needs to satisfy Used by OLAP Datacube

4. 4 Interoperability Application, System, User A simultaneous and rapid navigation through different datacubes Insertion of data in a datacube Introduction: needs to satisfy -N heterogeneous cubes must look as only 1 homogeneous cube -N heterogeneous cubes must facilitate feeding one homogeneous cube

5. 5 Challenge: combine 3 bodies of knowledge GIS Enhance decision making process. Detailed data vs. Aggregated data Multiples data sources Decision Support Systems (DSS) Decision Support Systems (DSS) Geospatial data (thematic, spatial and temporal) Transaction oriented. Not developed for strategic decision making. Interoperability of geospatial datacubes Promotes data reuse  gain time and money Deals with standards, metadata, ontologies, etc. Interoperability Several Datacubes Datacube

6. 6 Geospatial Datacubes Both dimensions and measures may contain geospatial components. CB … Non-geometric spatial dimension Canada Québec MontréalQuébec NB … Mixed spatial dimension … Canada … Geometric spatial dimension … … Example:

7. Drill-Down Challenge: Newell’s 10 second cognitive band Supports Spatial On-Line Analytical Processing (SOLAP) –Operations such as drill-down, drill-up and drill-across. Select regions -> Roll-up levels-> drill-down : 4 clicks, 2 seconds Select 1 year -> Select all years -> Select 4 years -> Multimap View: 7 clicks, 5 seconds Drill down level -> Change measure -> roll-up -> Roll-up -> Pivot … : 8 click, 6 seconds

8. 8 - The content of geospatial datacubes are usually heterogeneous * Organisational heterogeneities * technical heterogeneities * Semantic heterogeneities - Today’s interoperability concepts and standards are for transactional systems (they do not support multidimensional concepts) - No work on semantic interoperability of geospatial datacubes !! Challenges

9. 9 Defining the semantic interoperability between geospatial datacubes Categorizing the semantic conflicts that may occur between the content of geospatial datacubes. Defining a framework for interoperating geospatial datacubes (based on human communication, ontology and context) Developing a semantic model that can be used by human and machine to: –explicitly represent the elements of datacubes semantics. –interpret datacubes content and reason about their semantics. Developing a method to reason about the semantics of datacubes. Developing a method to convert some elements of these semantics from source datacube to target datacube. Proposed approach

10. 10 Defining the Interoperability of Geospatial Datacubes The interoperability among two geospatial datacubes C1 and C2 is the ability of C1 to request a service in a manner that can be understood by C2, and the ability of C2 to respond to that request in a manner that can be understood by C1. The request and response are conducted automatically. Services could include: –importing/exporting data contained in dimensions or facts; Ex. combining forest data from C1 and population density from C2 for a risk analysis –getting information about the dimensions or the facts (e.g. language used); Ex. Canada national C1 getting data from provincial C2s using English or French data –comparing a dimension/fact against other dimension/fact; Ex. 2004 census C1 with 1999 census C2 –taking into account a concept evolution (e.g. meaning or format changes); or Ex. 2004 forest inventory C1 combined with 1984 forest inventory C2 (practices have changed for ecological reasons) –adapting the meaning of a concept when the context changes. Ex. Fine-grained land use categories in C1 with coarse-grained land-use categories in C2

11. 11 Semantic interoperability of datacubesSemantic interoperability of transactional DBs Similarities Semantic Interoperability of Datacubes VS Semantic Interoperability of transactional DBs Differences Deals with datacubes concepts (facts, measures, dimensions, levels) Deals with the semantic heterogeneities of of aggregation and summarizing methods and algorithms, including summarizability conditions. Reusing data Facilitates an efficient exchange of information Deals with the heterogeneities of DB concepts (i.e. tables, attributes, relations, etc.).

12. 12 Semantic heterogeneity in spatial datacubes Cube-to-Cube heterogeneity Dimension-to-Dimension heterogeneity Measure-to-Measure heterogeneity Dimension- to- Dimension meaning conflicts Dimension- to- Dimension context conflicts Cube-to- Cube context conflicts Dimension- to- Dimension hierarchy conflicts Measure - to- Measure context conflicts Measure- to- Measure meaning conflicts Categorizing the semantic heterogeneities

13. 13 An ontology is a set of related concepts and a set of assumptions about the intended meaning of these concepts in a given domain or application. Context is any information that surrounds and facilitates the interpretation of concepts. Ontologies contain only certain elements of context. Human Communication, Ontology and Context Field of experience Signal SourceDestination EncoderDecoder

14. 14 We identify four context levels : –Concept Context level: includes the characteristics of dimensions or measures of datacubes (role, properties, etc). –Dataset Context level: consists of elements related to dataset of geospatial datacubes (such as the specifications used to describe concepts), –Domain Context level: contains the context elements of the domain (such as forestry), –Goal Context level: defines the purpose for which the geospatial datacubes will be used (such as the evolution of the wood volume), Human Communication, Ontology and Context

15. 15 Interoperability Framework Datacube A Datacube B Agent B (Datacube B) Context ontology Datacube A ontology Context Agent Agent A (Datacube A) Datacube B ontology Inferred contexts Metadata AMetadata B

16. 16 Fact: Context Fact: Ontology Context of concepts Constraints Domain Context C1C2 1K C Global Context Data Source Context UML Spatial Context Prosperities Definition Geometry DD11 scale Colour Graphic 1/5000 blue red GD2 DD12DD21DD22 House: Construction for living O1O2 1K O Semantic (SemEL) Ontology Context Assertion Description Technique Graph NL E/R Assertion 1/1250 Polygonlinepoint Time Year Month Application Domain SemEL – A Semantic Model for Interoperating Geospatial Datacubes

17. 17 Conclusion Our approach is based on human communication, ontology, context, and the multidimensional structure. We defined a communication model which is based on Datacubes Agents and a Context Agent. The SemEL model represents a new concept that: –is based on the multidimensional paradigm. –explicitly represents the semantics of geospatial datacubes contents. –allows to reason about semantics. –can be implemented on a relational platform.

18. 18 Current Future Works Current works SemEL Refined Definining a method to reason about the semantics of geospatial datacubes –Based on SemEL –Require human intervention Future works Define a mapping method between the content of the geospatial datacubes contents. Develop a SOLAP application based on SemEL. Develop a web-based system that supports the mapping between datacubes contents.

19. 19 Thanks !

20. 20 Geospatial Datacubes Dimension Time Datacubes «Roads and Lakes» Dimension Lake Lac Beauport Lac St-Charles Quebec Ontario Dimension Region Quebec Montreal Toronto Ottawa Fact: relation between roads and lakes Int.Adj. Int.Adj. Disj. Adj. Int. Disj. Adj. In. Disj. 2003 2002 2001 Adj. Members of dimension Dimension Road Level ProvinceLevel City 270 … 180240 The raison d’être of datacubes:  Support strategic decision making