Toward Semantic Interoperability between Information Systems ◾ 85
is possible to think about quantity as a property instead of an entity, it is neces-
sary to represent it by a term to follow the minimal encoding bias criterion [14].
Additionally, this Quantity term must be related to the EBDItem term by a formal
relation. Figure3.10 shows a portion of the ontology after making the quantity and
temporal features explicit.
To represent the features of products, three terms are added: Type, Size, and
Trademark. e Trademark term is related to another term, Trademark Dimension,
covering the representation dimension of the feature trademark. is representation
dimension is an enumeration of possible values, not a metric. In the same way, the
Type term that represents the type of material with which the packages are made
is related to the TypeDimension term which is an enumeration of possible values
(such as carton or plastic). Finally, the Size term representing package capacity is
related to the SizeDimension term indicating the representation dimension of fea-
ture size. is dimension is metric, i.e. its possible values are nonnegative numbers
(196, 250, etc.). Since the capacity of a packages is an amount associated with a unit
of measure, the SizeDimension term has a relation with the UnitOfMeasure term
mentioned earlier.
Up to this point, only the features of the Product entity have been represented,
but Product lacks its own representation. us, a Product term must be added
to the ontology and related to the EBDItem, Trademark, Type, and Size terms.
Additionally, the PartNumber and ItemDescription must be properties of the
Product term and not of the EBDItem term.
A product is both an entity and a feature of the Replenishment Plan entity.
us it is a complex feature related to a set of representation dimensions (mul-
tidimension) and represented by the ProductMultiDimension term. e dimen-
sions that compose this set are integral and represented by TrademarkDimension,
TypeDimension, and SizeDimension.
time:CalendarClockInterval EBD
EBDHorizon EBDItemsCollection
EBDItemPeriod
hasPeriod*
hasQuantity*
hasQuantityDim*
hasUnitOfQuantity*
QuantityDimension
UnitOfMeasure
Quantity
EBDItem
isa
isa
hasHorizon* hasItems*
hasItem*
Figure 3.10 Portion of extended EBD ontology representing temporal and quan-
tity features.
86 ◾ Mariela Rico et al.
3.6.5 Process 5: Designate Bridge Term for Each Entity
An important feature that should be made explicit is the intended use of an entity
in the context considered. However, Trading Partners are the roles they assume,
not physical entities. e treatment of entities that represent roles is postponed to
future work. e intended use of the Replenishment Plan entity is to represent the
agreed plan of the trading partners. Since the EBD term refers to the documents
exchanged by the trading partners, particularly the replenishment plan, this term
can be used to designate the intended use of the entity.
e products covered by the replenishment plan can be misunderstood,
depending on their intended use. ey are manufactured by the packaging indus-
try and used for the dairy industry products. us, in an ontology from the col-
laborative relationship context such as the EBD ontology, two bridge terms should
be added: Product and Package to represent the intended use of the entity in the
packaging industry and dairy industry contexts, respectively. Since Product is
already in the ontology, only Package must be added and related to the Product
term. As bridge terms represent contextual features, they must also relate to the
terms encompassing their representation dimension in human cognition. In the
dairy industry context, packages are associated with a representation dimension
that is an enumeration of possible values. Figure3.11 shows a portion of the EBD
ontology with the changes made to adequately represent the feature product.
3.7 Conclusions
is chapter discussed the problem of semantic interoperability between P2P infor-
mation systems that share information from their sources. To solve this problem, we
UnitOfMeasure
hasUnitOfSize*
SizeDimension
definedByTrademarkDim*
definedByTypeDim*
TrademarkDimension
Trademark
TypeDimension
Size
hasProductMultiDim*
ItemDescription
...
Product
EBDItem
hasProduct*
ProductMultiDimension
hasSize*
hasSizeDim* hasTypeDim* hasPackageDim*
hasType*
represents*
Package
Integer*PartNumber
hasTrademark*
String*
Type
PackageDimension
hasTrademarkDim*
definedBySizeDim*
Figure 3.11 Portion of extended EBD ontology representing products.
Toward Semantic Interoperability between Information Systems ◾ 87
proposed improving the results of the matching process between the ontologies that rep-
resent the semantics of the information sources by providing thorough representations
of entities. To this aim, we suggested a method for making the contextual features of
entities explicit. is approach signicantly improves the output of the ontology match-
ing process and facilitates the generation of conversion rules that constitute the core
of information system interoperability. Regardless of the domain in which ontologies
are used, in practice they suer from dierent kinds of modeling errors. e proposed
method can also be applied to existing ontologies to overcome some of these errors.
Acknowledgments
e authors are grateful to Universidad Tecnológica Nacional, Consejo Nacional
de Investigaciones Cientícas y Técnicas, and Agencia Nacional de Promoción
Cientíca y Tecnológica for their nancial support.
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