An Architecture and a Metamodel for Processing Analytic and Geographic Multilevel Queries - Diego...

Diego Barros & Robson FidalgoICCSA 2010

An Architecture and a Metamodel for ProcessingAnalytic and Geographic Multilevel Queries

Diego Martins Vieira Barros1,2 & Robson do Nascimento Fidalgo1

1 - Center of Informatics - Federal University of Pernambuco (UFPE), Recife, Brazil

2 - São Francisco’s Hydroelectric Company (CHESF), Recife, Brazil


Outline

• Introduction

– Motivation and Basic Concepts

• AGIS

– Basic Concepts, Architecture and Metamodel

• Case Study

• Related Work

• Conclusion

2


Introduction (Motivation)

• SOLAP tools are dependent on specific OLAP

languages and servers

• Queries for spatial analysis are typically large

and complex

– involve selections, projections, aggregations and joins

– the effort to write these queries manually is not a

trivial task for a non-specialist user

3


Introduction (Basic Concepts)

• OLAP– Multidimensional and multilevel processing

• Multidimensional: What is the total sales by product category, store name and year?”

• Multilevel: What is the total sales by product category, store name and year, semester, quarter, month and day?”

4

Pro

du

ct

Store

Time

+Year+Semester+Quarter+Month +Day



• OLAP– Analytic queries are typically large and complex for

non-specialist users (joins, group by, etc.)

5

“What is the total sales by product category, store name and year?”


• GIS

– Geographic processing

• Topological: Touches, Within, Crosses, Disjoint, Overlaps, etc.

• Metric: Area, Length, Distance, etc.

– Theme overlapping

6

Source: www.vigeocities.com



• GIS– Analytic and geographic queries are also typically

large and complex for non-specialist users (joins, group by, spatial operations, etc.)

7

“What is the average sales by store for stores located in cities adjacent to Recife city?”



• SOLAP

– Multidimensional/multilevel and geographic processing

– Dependent on specific OLAP languages and servers• There is no de jure standard language for OLAP yet, like

ISO/IEC SQL is to Relational DBMS or ISO/OGC SQL is to

Spatial DBMS

8



AGIS (Basic Concepts)

9

• AGIS = Analytic and Geographic Information Service

• Provide a service for analytic and geographic multilevel processing that:

– Abstracts the complexity of writing these queries

– Uses consolidated and non-proprietary standards


AGIS (Architecture)

10


AGIS (Architecture)

11

- Component that corresponds to an application for requesting the service provided by the AGIS Engine- It can be a graphical interface implemented as a Web client , desktop or another application


AGIS (Architecture)

12

- Responsible for 1) generating queries for analytic and geographic multilevel processing 2) sending these queries to the SDBMS that executes them-Receives, through its programming interface, a set of query parameters sent form an AGIS Application and returns the query result to it.- Consists of two subcomponents


AGIS (Architecture)

13

-Component to access and provide AGIS metadata


AGIS (Architecture)

14

-Component that generates SQL queries with multilevel aggregations (GROUP BY clause) and geographic restrictions (spatial operators)


AGIS (Architecture)

15

- Component that corresponds to the XML repository of metadata, which defines the metadata needed to generate queries for analytic and geographic multilevel processing- Defines the metadata that describes how the geographic database must be organized to allow the generation of queries


AGIS (Architecture)

16

- Component that processes queries generated and submitted by AGIS Engine


AGIS (Architecture)

17

- Component that corresponds to the tables (schema and data) of AGIS architecture- It can be a transactional GDB or a Spatial Data Warehouse


AGIS (Metamodel)

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AGIS (Metamodel)

19

- The root of the proposed metamodel


AGIS (Metamodel)

20

- Each feature type represents a geographic layer/theme that can be analyzed- Country, Region, State and City


AGIS (Metamodel)

21

- Each geographic hierarchy defines the position in which the feature types should be processed in an aggregation operation

- H1: Region→ State → City- H2: Country → State → City- H3: Region→ City- H4: State → City


AGIS (Metamodel)

22

- Each geographic level is associated with a feature type and represents the position of the feature type in the hierarchy


AGIS (Metamodel)

23

- Each measure represents a fact (measurable value that varies over time) to be analyzed

- Area- Rainfall


AGIS (Metamodel)

24

- Each geographic context corresponds to an analysis view- Denomination given to an analysis scope that corresponds to an abstract container

- C1: H1; Area and Rainfall


AGIS (Metamodel)

25

- Each filter corresponds to a set of fields from a table of the GDB that can be used as a selection/restriction criterion

- Vegetation type- Climate type

- Specialized in two types

*Only used on WHERE clause


AGIS (Metamodel)

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- Corresponds to conventional restriction operations of SQL

- Vegetation type- Climate type

What is the average power produced by power stations built since 1995?


AGIS (Metamodel)

27

- Corresponds to conventional and/or spatial operations of SQL

- Vegetation type and its geometry- Climate geometry

What is the total power produced by power stations located in states that intersects the tropical wet climate?


AGIS (Metamodel)

28

- Occurs between a pair of columns of the tables to be joined- Conventional filter

-Defined from fields that are not on the same table that contains the measures

- Geographic level- Between two levels of a geographic hierarchy defined from normalized tables-Connect the table containing the geographic level with the lowest granularity and the table containing the measures


AGIS (Metamodel)

29

- Additional information about a particular theme/layer that can be returned in query results- Political party and name of the Mayor of a City feature type- Not part of geographic hierarchies- The same column can be defined as a filter and as a property

*Only used on SELECT clause


AGIS (Metamodel)

• AGIS XML Schema

– Metamodel implementation

30

…


Case Study

• Proof of concept

– Analyze the electrical energy situation in Brazil, in

terms of generation and transmission

– Data from the Brazilian Agency of Electric Energy

– Simple Java client – AGIS WEB

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Case Study

• Geographic Database - Brazilian Agency of Electric Energy

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Case Study

• Metadata– Feature type

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Case Study

• Metadata– Geographic hierarchy– Measure

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Case Study

• Metadata– Conventional filter

35


Case Study

• Metadata– Spatial filter

36


Case Study

• Metadata– Geographic context

37


Case Study

• AGIS WEB graphical interface

38


Case Study

• Analytic and Geographic Multilevel Query

39


Related Work

• GOLAPA [1]

• GeoMondrian [12]

• JMap [13,14]

• GeWOlap [2]

• OLAP for ArcGIS [15]

40


Related Work

• As there is no de jure standard language for OLAP yet, these

works are dependent on specific OLAP languages and servers

• On the other hand, AGIS proposal aims to provide a service to

perform analytic and geographic multilevel processing without

dependence on an OLAP server

• AGIS should not be considered a SOLAP solution, because it is

a service that aims to enrich the set of functionalities of GIS

applications (AGIS is not based on an OLAP server)

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Conclusion

• Contributions

– Definition of a three-tiered architecture (AGIS Architecture)

– Specification of AGIS Metamodel using UML and XML

– Possibility of performing analytic and geographic multilevel

queries, without needing to write manually these queries

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Conclusion

• Future work

– Implementation of a geographic hierarchy among

spatial objects (i.e. using contains spatial relationship)

– Use of AGIS with huge databases

– Improve AGIS graphical interface

43


References

1. Fidalgo, R.N.: Uma Infra-estrutura para Integração de Modelos, Esquemas e Serviços

Multidimensionais e Geográficos. Doctorate Thesis, Federal University of Pernambuco,

Recife, PE (2005)

2. Bimonte, S., Tchounikine, A., Miquel, M.: Spatial OLAP: Open Issues and a Web Based

Prototype. In: 10th AGILE International Conference on Geographic Information Science, p.

11 (2007)

3. GeoMondrian Project, http://www.geo-mondrian.org

4. Kheops JMap, http://www.kheops-tech.com/en/jmap

5. Kheops JMap Spatial OLAP, http://www.kheops-tech.com/en/jmap/solap.jsp

6. ESRI OLAP for ArcGIS,

http://www.esri.com/software/arcgis/extensions/olap

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An Architecture and a Metamodel for ProcessingAnalytic and Geographic Multilevel Queries

Diego Martins Vieira Barros1,2 & Robson do Nascimento Fidalgo1

1 - Center of Informatics - Federal University of Pernambuco (UFPE), Recife, Brazil

2 - São Francisco’s Hydroelectric Company (CHESF), Recife, Brazil

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