Deriving Semantic Description Using Conceptual Schemas Embedded into a Geographic Context Centre for Computing Research, IPN Geoprocessing Laboratory Miguel.

Slides:



Advertisements
Similar presentations
2 Introduction A central issue in supporting interoperability is achieving type compatibility. Type compatibility allows (a) entities developed by various.
Advertisements

ARCHITECTURES FOR ARTIFICIAL INTELLIGENCE SYSTEMS
Copyright Irwin/McGraw-Hill Data Modeling Prepared by Kevin C. Dittman for Systems Analysis & Design Methods 4ed by J. L. Whitten & L. D. Bentley.
So What Does it All Mean? Geospatial Semantics and Ontologies Dr Kristin Stock.
OASIS Reference Model for Service Oriented Architecture 1.0
Object-Oriented Analysis and Design
A First Attempt towards a Logical Model for the PBMS PANDA Meeting, Milano, 18 April 2002 National Technical University of Athens Patterns for Next-Generation.
Knowledge Acquisitioning. Definition The transfer and transformation of potential problem solving expertise from some knowledge source to a program.
Software Requirements
Creating Architectural Descriptions. Outline Standardizing architectural descriptions: The IEEE has published, “Recommended Practice for Architectural.
1 Spatial Databases as Models of Reality Geog 495: GIS database design Reading: NCGIA CC ’90 Unit #10.
Knowledge Representation Reading: Chapter
Foundations This chapter lays down the fundamental ideas and choices on which our approach is based. First, it identifies the needs of architects in the.
OIL: An Ontology Infrastructure for the Semantic Web D. Fensel, F. van Harmelen, I. Horrocks, D. L. McGuinness, P. F. Patel-Schneider Presenter: Cristina.
Domain-Specific Software Engineering Alex Adamec.
Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA.
Chapter 8 Architecture Analysis. 8 – Architecture Analysis 8.1 Analysis Techniques 8.2 Quantitative Analysis  Performance Views  Performance.
Knowledge representation
Clément Troprès - Damien Coppéré1 Semantic Web Based on: -The semantic web -Ontologies Come of Age.
Of 39 lecture 2: ontology - basics. of 39 ontology a branch of metaphysics relating to the nature and relations of being a particular theory about the.
Semantic data model
UNIVERSITÉ LAVAL Centre for Research in Geomatics, Université Laval, Cité universitaire, Quebec, QC Canada G1K 7P4 Semantic Interoperability of Geospatial.
Metadata Models in Survey Computing Some Results of MetaNet – WG 2 METIS 2004, Geneva W. Grossmann University of Vienna.
RCDL Conference, Petrozavodsk, Russia Context-Based Retrieval in Digital Libraries: Approach and Technological Framework Kurt Sandkuhl, Alexander Smirnov,
Lecture2: Database Environment Prepared by L. Nouf Almujally & Aisha AlArfaj 1 Ref. Chapter2 College of Computer and Information Sciences - Information.
UNIT 2.
Metadata. Generally speaking, metadata are data and information that describe and model data and information For example, a database schema is the metadata.
1 A Conceptual Framework of Data Mining Y.Y. Yao Department of Computer Science, University of Regina Regina, Sask., Canada S4S 0A2
LOGIC AND ONTOLOGY Both logic and ontology are important areas of philosophy covering large, diverse, and active research projects. These two areas overlap.
Sommerville 2004,Mejia-Alvarez 2009Software Engineering, 7th edition. Chapter 8 Slide 1 System models.
Requirements as Usecases Capturing the REQUIREMENT ANALYSIS DESIGN IMPLEMENTATION TEST.
An Ontological Framework for Web Service Processes By Claus Pahl and Ronan Barrett.
Knowledge Representation of Statistic Domain For CBR Application Supervisor : Dr. Aslina Saad Dr. Mashitoh Hashim PM Dr. Nor Hasbiah Ubaidullah.
A Context Model based on Ontological Languages: a Proposal for Information Visualization School of Informatics Castilla-La Mancha University Ramón Hervás.
Interoperability & Knowledge Sharing Advisor: Dr. Sudha Ram Dr. Jinsoo Park Kangsuk Kim (former MS Student) Yousub Hwang (Ph.D. Student)
1 A Historical Perspective on Conceptual Modelling (Based on an article and presentation by Janis Bubenko jr., Royal Institute of Technology, Sweden. June.
OOAD Unit – I OBJECT-ORIENTED ANALYSIS AND DESIGN With applications
1 The Theoretical Framework. A theoretical framework is similar to the frame of the house. Just as the foundation supports a house, a theoretical framework.
SKOS. Ontologies Metadata –Resources marked-up with descriptions of their content. No good unless everyone speaks the same language; Terminologies –Provide.
Metadata Common Vocabulary a journey from a glossary to an ontology of statistical metadata, and back Sérgio Bacelar
ESDI Workshop on Conceptual Schema Languages and Tools
Of 33 lecture 1: introduction. of 33 the semantic web vision today’s web (1) web content – for human consumption (no structural information) people search.
Developing the theoretical and conceptual framework From R.E.Khan ( J199 lecture)
WIGOS Data model – standards introduction.
Issues in Ontology-based Information integration By Zhan Cui, Dean Jones and Paul O’Brien.
MDA & RM-ODP. Why? Warehouses, factories, and supply chains are examples of distributed systems that can be thought of in terms of objects They are all.
Object storage and object interoperability
Lecture №1 Role of science in modern society. Role of science in modern society.
® Using (testing?) the HY_Features model, 95th OGC Technical Committee Boulder, Colorado USA Rob Atkinson 3 June 2015 Copyright © 2015 Open Geospatial.
Converting an Existing Taxonomic Data Resource to Employ an Ontology and LSIDS Jessie Kennedy Rob Gales, Robert Kukla.
 To explain why the context of a system should be modelled as part of the RE process  To describe behavioural modelling, data modelling and object modelling.
OWL Web Ontology Language Summary IHan HSIAO (Sharon)
Presented by Kyumars Sheykh Esmaili Description Logics for Data Bases (DLHB,Chapter 16) Semantic Web Seminar.
Some Thoughts to Consider 5 Take a look at some of the sophisticated toys being offered in stores, in catalogs, or in Sunday newspaper ads. Which ones.
Background-assumptions in knowledge representation systems Center for Cultural Informatics, Institute of Computer Science Foundation for Research and Technology.
November 2001, Slide 1 P.Habela, K.Subieta: Standard Metamodel for Object Databases (2) Standard Metamodel for Object Databases (2): Proposed Improvements.
Data Models. 2 The Importance of Data Models Data models –Relatively simple representations, usually graphical, of complex real-world data structures.
Introduction: Databases and Database Systems Lecture # 1 June 19,2012 National University of Computer and Emerging Sciences.
ACCOUNTING THEORY AND STANDARDS
A Generic Model for Software Architecture Yun Sang-hyun Rossak. W. / Kirova. V. / Jolian. L. / Lawson. H. / Zemel. T. Software, IEEE Jul/Aug.
MDD-Kurs / MDA Cortex Brainware Consulting & Training GmbH Copyright © 2007 Cortex Brainware GmbH Bild 1Ver.: 1.0 How does intelligent functionality implemented.
Semantic metadata in the Catalogue Frédéric Houbie.
COP Introduction to Database Structures
The Semantic Web By: Maulik Parikh.
Object-Oriented Software Engineering Using UML, Patterns, and Java,
SysML v2 Formalism: Requirements & Benefits
ece 627 intelligent web: ontology and beyond
Introduction Artificial Intelligent.
Ontology-Based Approaches to Data Integration
Schema translation and data quality Sven Schade
Presentation transcript:

Deriving Semantic Description Using Conceptual Schemas Embedded into a Geographic Context Centre for Computing Research, IPN Geoprocessing Laboratory Miguel Torres November, 2006

Presentation Overview Introduction Goals Related works Geospatial domain conceptualization Case study Conclusion and future works

Introduction (1) Ontology has gained increased attention among researchers in GIScience. –This notion plays an important role in establishing robust theoretical foundation for GIScience. It is possible to unify several interrelated research subfields, each of which deals with different perspectives on geospatial ontologies and their roles in GIScience

Introduction (2) Three broad sets of foundational issues need to be resolved: –Conceptual issues concerning what would be required to establish an exhaustive ontology of the geospatial domain –Representational and logical issues relating to the choice of appropriate methods for formalizing ontologies –Issues of implementation regarding the ways in which ontology ought to influence the design of information systems

Introduction (3) Up-to-date geospatial information can not be sometimes represented in “adequate” way –It presents ambiguities: Several meanings Imprecision of information Heterogeneity and isolation sources –Whereby, it’s difficult to develop interoperable applications that allow us to share, integrate and represent geospatial information

Introduction (4) These facts bear with searching solutions oriented to: –Geospatial data representation and integration –Semantic heterogeneity and, –Imprecise geographic objects issues Consequently, commercial GISs don’t have tools to extensibly explore the essential properties and relations of geographic objects –Therefore, by means of these GIS applications, it’s difficult to explore the semantics of a set of geographic objects

Introduction (5) Ontologies are essential for the knowledge representation, they allow to solve problems associated to: –Heterogeneity, interoperability, representation, integration and exchange of geospatial data These problems imply incompatibility between diverse geographic objects, as well as different conceptualizations according to a specific context

Introduction (6) The conceptualization of geospatial domain is diverse –Geospatial data are often imprecise or many subjects have different points of view It’s important to consider alternative object representations, which are independent of the imprecise nature of the geospatial data

Goals (1) Our research is mainly oriented to propose: –An approach related to conceptual issues concerning what would be required to establish ontologies of the geospatial domain We propose an approach to make a conceptualization of the real world based on conceptual schemas, which are used to generate a semantic description of the geospatial domain –This description can provide the guidelines to formalize this domain in form of geospatial ontologies according to specific contexts

Related works (1) Guarino coined the term “ontology-driven information systems” and provided a broad discussion on their place in the computer and information science. Gruber, one of the pioneers of the use of ontological methods in information science, defines an ontology as “a specification of a conceptualization” Smith reported the results of a series of experiments designed to establish how non-expert subjects conceptualize geospatial phenomena. The results yield an ontology of geographical categories – a catalogue of the prime geospatial concepts and categories

Related works (2) Bishr argued that information modeling requires to be controlled to allow successful sharing of information. Also, he suggest that any coherent information model need to be based on accepted ontological foundation to guarantee unambiguous interpretation. Fonseca proposed a framework to link the formal representation of semantics (i.e., ontologies) to conceptual schemas describing information stored in databases. The main result is a formal framework that explains the mapping between a spatial ontology and a geographic conceptual schema.

Geospatial Domain Conceptualization (1) In the modeling approach, the modeler is required to capture a user’s view of the real world in a formal conceptual model Such an approach forces the modeler to mentally map concepts acquired from the real world to instances of abstractions available in his paradigm choice Consolidation of concepts and knowledge represented by a conceptual schema can be useful in the initial steps of ontology construction. To adequately represent the geographic world, we must have computer representations capable not only of capturing descriptive attributes about its concepts, but also of describing the relations and properties of these concepts.

Geospatial Domain Conceptualization (2) We propose conceptual schemas to describe the contents of the real world abstraction in order to specify the behavior of the geospatial entities Conceptual schemas certainly correspond to a level of knowledge formalization Conceptual schemas are built to abstract specific parts of the geospatial domain and to represent schematically which geographic entities should be collected and how they must be organized

Geospatial Domain Conceptualization (3) The proposed conceptual schemas are composed of two types of concepts (C): –Terminal concepts (C T ) C T are concepts that don’t use other concepts to define their meaning (simple values). –Non-terminal concept (C N ) The meaning of C N is defined by other concepts (C T or C N ), which can be terminal or non-terminal

Geospatial Domain Conceptualization (4) Each concept has a set of aspects –They are characteristics that describe the properties, relations and instances that involve the geospatial objects All aspects of a terminal concept are single –e.g. the type of all aspects that belong to the set of primitive types (punctual, linear and areal objects )

Geospatial Domain Conceptualization (5) According to these definitions: –It’s necessary to express the semantics that can provide a conceptual schema by means of a description D –Therefore, we consider the concepts C embedded into the conceptual schemas through geospatial objects, which are represented by primitive types as well as the set of relations R involved among geospatial objects

Geospatial Domain Conceptualization (6)

Geospatial Domain Conceptualization (7) This schema is adaptive for any context It attempts to reflect the main features involved in this domain The main features involved into geospatial domain have been abstracted of the real world in order to obtain a conceptualization This conceptualization provides us explicit vocabulary that represents the ontological commitment of the cognitive and intuitive perception of the subjects We are looking for a compact conceptual schema-based abstraction that drives the cognitive process of phenomenon semantic description under specific context

Case Study (1) We will describe two scenarios, which are focused on showing how to conceptualize the geospatial domain, by means of conceptual schemas in order to obtain a semantic description regarding specific context The goal is to depict how these scenarios converge in the same semantic description –Although their representations are different, they belong to the same context; thereby their semantic description is the same as well as their conceptualization.

Case Study (2) Scenario 1: Imagining the real world. Suppose that we are looking at a landscape, which depicts several entities such as a forest that has a lake and a river. Moreover, the freeway F25 crosses the highway I37. F25 is used to arrive to Santa Cruz that is the main town of the surroundings It’s important to make a conceptualization about our observations. –In other words, we are making and abstraction process that is used to conceptualize the landscape –Then this kind of conceptualization can be represented in a conceptual schema and restricted by a context

Case Study (3) Scenario 2: Vector map. Suppose that we are looking at a map –It depicts different thematics that consist of different layers, in which each layer contains geographic objects represented by geospatial primitives. The map has Populations (POP), Hydrologic Features (HYF), Roads (ROD) and Soils (SOL). –Additionally, each thematic and its layers are denoted by a legend. The map is composed of 2 areal objects, 3 linear objects and 1 punctual object

Case Study (4) Thereinafter, we use the conceptual schema (Slide 17) to describe both scenarios. To obtain a semantic description from conceptual schema, it is necessary to map the geospatial entities into the conceptual schema Once concepts have been defined into the conceptual schema –we choose the non-terminal concept to be described (this means to select the aspect to be pointed out). The process continues until we find a terminal concept

Case Study (5)

Conclusions and future works (1) We propose an approach to make a conceptualization of the real world based on conceptual schemas, which are used to generate a semantic description of the geospatial domain. This description attempts to provide the guidelines to formalize the geographic domain in form of geospatial ontologies according to specific contexts. We perceive that geographic data modeling requires models that are more specific and capable of capturing the semantics of geospatial data, offering higher abstraction mechanisms and implementation independence

Conclusions and future works (2) This approach allows us to process imprecise data and aid to information integration and semantic heterogeneity tasks –Thus, the method is focused on describing the semantic content based on conceptual schemas embedded into geographic context We have introduced two types of concepts: “terminal” and “non-terminal” as well as two kinds of relations: “has” and “is-a” to build the conceptual schema

Conclusions and future works (3) We approach conceptual schemas to describe –The contents of the real world abstraction to specify the behavior of the geospatial entities, in which context plays an important role to guarantee shared and explicit conceptualizations Future works are mainly oriented to propose: –Conceptual issues related to translate semantic descriptions into geospatial ontologies, as well as what would be required to establish these kinds of ontologies In addition, our work is led to formalize: –Appropriate methods to represent ontologies of the geospatial domain and to measure semantic contents between geospatial ontologies

Thank you ! Miguel Torres