The paper has been further extended and accepted for publication in The Computer Journal Published by Oxford University Press following peer review. The version of record Section A: Computer Science Theory, Methods and Tools: Wassim Derguech, Sami Bhiri, Souleiman Hasan, and Edward Curry, Using Formal Concept Analysis for Organizing and Discovering Sensor Capabilities, The Computer Journal first published online September 11, 2014 doi:10.1093/comjnl/bxu088 is available online at: http://comjnl.oxfordjournals.org/content/early/2014/09/11/comjnl.bxu088.
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Capability: Informal Definition
• Capability = What an action (Program, Business Process, Task)
does from a functional perspective.
• Synonyms: Business Function, Functionality
• Related terms: Business Goal, Consumer Request
• Central concept in (semantic) information systems
• A service is an access mechanism to a certain capability.
• A Business process is a set of ordered activities aiming to achieve a
business goal.
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Problems in SWS description(1/2)
• Service functionalities are described in IOPEs
• Domain-specific functional features cannot be easily defined within
IOPE.
• Example:
“book a package shipping service via telephone”
vs. “book a package shipping service via Internet”
• Cannot define interdependencies between features
• No functionality based service clustering/categorization.
• Clustered based on subsumption relation over IO(PE)s
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Problems in SWS description (2/2)
• Example: find services that “delivers a package” in
Programmable Web service repository.
• results under “shipping” category.
Address check
service
Tracking service
Rate query service
Utility services:
customer identification,
payment processing…
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Goals
• Define a metamodel for describing capabilities featuring
domain properties
• Organizing capabilities in an optimal way for enhancing
their discovery
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Examples of capabilities
• FedexShipment: is a capability for Shipping
• packages under 50 Kg,
• serving certain routes,
• the price depends on the source, destination and the weight of
the package; i.e. different formulas for computing the price based
on other attributes.
• FedexOffer:
• Shipping of a 10Kg Package from Ireland to Singapore on 2013-
06-15 for 200 Dollars.
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Capability modelling challenges
• Attribute dependency
• :From and :To attributes are interdependent.
• The :Price attribute depends on the attributes :From, :To and
:Package.
• Dynamic attributes
• The :Price may depend on the current exchange rate or the
company workload.
➔ make it hard if not impossible to model non static and
attribute-interdependent capabilities.
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Definition of Structured Entity
• Structured Entity: describing concepts with a set of
(property, value) pairs, a.k.a., property entries.
• SE = {(p1,v1),(p2,v2),…}
• A property value can be an rdf class or instance, if the
value has its own property entries, it is also a SE.
• We consider one mandatory attribute: Action Verb.
• The action verb is a concept from a domain ontology.
It represents all the actions performed in a certain
domain with meronymy relations between them.
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Example of capabilities
SensorCap2
ActionVerb = sco:sensing
State =Active
StorageOption =no
DigitalDisplay = sco:LCDScreen
LocationState = Accessible
SensorCap1
ActionVerb = sco:sensing
State =Active
StorageOption = 1Mo
DigitalDisplay = sco:LCDScreen
LocationState = Accessible
SensorCap5
ActionVerb = sco:sensing
State =Active
StorageOption = no
DigitalDisplay = no
LocationState = NotAccessible
SensorCap4
ActionVerb = sco:sensing
State =NotActive
StorageOption =1Mo
DigitalDisplay = sco:LCDScreen
LocationState = Accessible
SensorCap3
ActionVerb = sco:sensing
State =NotActive
StorageOption =1Mo
DigitalDisplay = sco:LCDScreen
LocationState = Accessible
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Goals
• Define a metamodel for describing capabilities featuring
domain properties
• Organizing capabilities in an optimal way for enhancing
their discovery
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Formal Concept Analysis
• FCA is a technique that evolved from mathematical
lattice theory used for data analysis.
• A powerful tool for identifying meaningful relationships
within a set of objects that share common attributes.
• It provides a theoretical model to build from a formal
context a partially ordered structure called concept lattice
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Formal Context
• A formal context FC is a triplet <X,Y,I>, where X and Y are
non-empty sets and I is a binary relation between X and Y.
Active
Storage
Option
Digital
Display
Accessible
SensorCap1 X X X X
SensorCap2 X X X
SensorCap3 X X X
SensorCap4 X X X
SensorCap5 X
X, the
set of
Objects
Y, the set of Attributes
<x,y> ∈ I
denotes
that the
object x
has the
attribute y
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Formal Concept
• A formal concept in <X,Y,I> is a pair <E,I> where E is a
subset of X and I is a subset of Y such that Att(E) = I
and Obj(I) = E.
A formal concept is created by getting objects from E
sharing the same attributes from I.
Active
Storage
Option
Digital
Display
Accessible
SensorCap1 X X X X
SensorCap2 X X X
SensorCap3 X X X
SensorCap4 X X X
SensorCap5 X
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Concept Lattice
• The set of ordered formal concepts derived from a formal
context is called a concept lattice.
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Multivalued Attributes (1/2)
Active
Storage
Option
Digital
Display
Accessible
Observed
Phenomenon
SensorCap1 X X X X Energy
SensorCap2 X X X Energy
SensorCap3 X X X Light
SensorCap4 X X X Temperature
SensorCap5 X Motion
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Multivalued Attributes (2/2)
Observed Phenomenon
Energy Light Temperature Motion
SensorCap1 X
SensorCap2 X
SensorCap3 X
SensorCap4 X
SensorCap5 X
Scaling
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Use Case Application
• Real world sensors deployed within the Linked Energy
Intelligence (LEI) dataspace.
• LEI dataspace is has been realized in Digital Enterprise
Research Institute (DERI).
• Sensors deployed:
• 50 energy consumption
• 20 light and heater energy consumption
• 8 temperature and motion detection
• Attributes: Active, Phenomenon Observed, Protocol,
Electricity Phases and Location
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LEI – DERI Concept Lattice
The set of all Active sensors
The set of all Motion sensors
The set of all Temperature sensors
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Conclusion: Goals
• Define a metamodel for describing capabilities featuring
domain properties
Structured Entity Meta Model
• Organizing capabilities in an optimal way for enhancing
their discovery
Formal Concept Analysis
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Pros and Cons
• Each Formal Concept represents an Equivalence Class
e.g. replacement of sensors
• Explicit links between Equivalence Classes
e.g. Optimise the discovery of a particular sensor
• This approach is not application in case of huge number
of sensors.
• Very difficult to adopt this approach in a highly dynamic
environment.
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Future Work
• Define and implement algorithms for updating this indexing
structure
• Investigate scaling operations in case of complex type
• Describe event patterns for complex events
• Provide automation support for creating capabilities