PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING

ONTOLOGY

Anshuman B. Saxena

1,2

and Alain Wegmann

Systemic Modeling Laboratory, School of Computer and Communication Sciences

EPFL Station 14, CH-1015 Lausanne, Switzerland

TATA Consultancy Services Innovation Labs, Bangalore

EPIP Industrial Area, Whitefield, Bangalore 560 066, India

Keywords: Industry Regulation, Systems Thinking, SEAM.

Abstract: The deregulation of economies has re-created the need for regulation. From a Systems perspective, the

unbundling of large monolithic industrial setups into smaller independent companies results in the

dissolution of high level management structures which, in the pre-deregulated era, had the overall control of

the end-to-end delivery process. In the absence of such holistic oversight mechanisms, deregulated

industries remain vulnerable to systemic failure. Industry regulators need to go beyond the usual concerns of

price, quality, and access, and invest in methods that capture the interactions between the different

stakeholders in an industry. It is the understanding of the individual interactions that can help piece together

a holistic view of the industry; thereby allowing the regulator to devise well informed interventions. In this

paper we model industry interactions as a multi-party value realization process and take a Systems approach

in analyzing them. Every value realization is analyzed both at the industry level and at the level of

stakeholders within the industry. The design patterns that emerge from this whole/composite view of value

realization form the basis for formalizing the concepts required to analyze the working of an industry. An

explicit specification of these concepts is presented as Regulation Enabling Ontology, REGENT.

1 INTRODUCTION

The deregulation of economies has led to the

unbundling of large, vertically integrated,

monolithic, industrial monopolies into lean, efficient

and more focused entities with the freedom to

develop upstream and downstream interconnections

(Baldwin & Cave, 1999). Network Industries (Shy,

2004), such as electricity, telecommunication,

transportation, posts, gas and water supply, are most

representative of such restructuring. From a

management perspective, such unbundling results in

the dissolution of the high level management

structures which, in the pre-deregulated era, were

responsible for the complete end-to-end delivery

process. A deregulated industry is, instead,

composed of multiple smaller management

structures, each restricted in scope to some specific

aspect of the overall industry. For instance, the

deregulation of Electricity Supply Industry

(Zaccour, 1998) led to its restructuring along

functional lines. Separate companies emerged for

generation, transmission and distribution of

electricity. These companies have independent

management structures, each responsible for their

part of the industry and interacting purely on an

economic basis. The absence of a holistic industry

wide management structure makes deregulated

industries vulnerable to systemic failure. Modern

regulatory systems need to go beyond the usual

concerns of price, quality, output and access, and

invest in schemes that capture the interactions

among the stakeholders of the industry.

Understanding these individual interactions help

piece together a holistic view of the industry,

thereby allowing the regulator to devise well

informed interventions that can ensure the

sustainable development of the overall industry.

Industries are composed of multiple stakeholder

groups: the companies that supply certain goods or

services, the individuals that consume them, the

government that facilitates these transactions and the

environment that provides the necessary backdrop

for these interactions. Any interaction within an

B. Saxena A. and Wegmann A..

A SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY.

DOI: 10.5220/0003097000700083

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2010), pages 70-83

ISBN: 978-989-8425-29-4

 2010 SCITEPRESS (Science and Technology Publications, Lda.)

industry can be reduced to an instance of the multi-

party relation that exists between these four

stakeholder groups. The plurality in relationship and

the diversity in stakeholder beliefs that underlie

these relationships make the effort of developing a

holistic understanding of an industry even more

challenging.

To address these challenges, we invoke the

notion of value and model every relationship in an

industry as a set of value realization processes.

Value is a qualitative concept and, thus, well suited

for an interdisciplinary discourse. Taking a Systems

perspective, we analyze the value realization process

both at the industry level and at the level of

individual stakeholders within the industry. Two

important design patterns emerge from this

whole/composite view of value exchange: any value

created in an industry has an associated supplier and

adopter, a supplier of one set of value is an adopter

of some other set of value. These design patterns

form the basis for formalizing the concepts required

to explain multi-party relationships in an industry.

This paper is an attempt to provide an explicit

specification of these concepts as ontology. The

ontology will provide regulators with a standard

representational vocabulary with which they can

document the material and information interplay

between the different stakeholders of an industry. It

is the abstraction of industry specific configuration

details as shared pan-industry concepts that will

facilitate the knowledge-level communication

among the community of regulators, thereby

enabling more effective and speedy sharing of

regulatory best practices. Section 2 provides a brief

overview of Systems thinking approach and presents

a Systems perspective of the de-regulated electricity

supply industry. Section 3 explores the notion of

value in greater detail and introduces the concepts of

resource and feature as building blocks of the value

realization process. Section 4 describes the

Regulation Enabling Ontology, REGENT, in detail,

highlighting the different design choices that were

made during the development of REGENT. Section

5 instantiates REGENT for the Urban Household

Electricity Industry and, as an example,

demonstrates its effectiveness in establishing

regulatory oversight. Section 6 presents some related

work in this field. The paper concludes with future

work directions in Section 7.

2 A SYSTEMS PERSPECTIVE OF

INDUSTRY

A Systems approach to understanding the

relationship between the stakeholders of an industry

allows taking a holistic view of the industry and

analyzing how these relationships influence one

another in the context of the overall well being of

the industry. This is particularly useful for

deregulated industries where management structures

only exhibit knowledge about local relationships and

the relevance of these relationships to the entire

system remains largely unexplored. For a regulator

to act as a true custodian of the industry, it is

important that it has the complete knowledge about

the different interactions that occur in an industry

and the bearing these relationships may have on the

overall working of the industry. To further illustrate

the affect of deregulation on the overall management

of the industry, we use the visual semantics of

SEAM to analyze the evolution of Electricity Supply

Industry.

SEAM is a set of Systemic Enterprise

Architecture Methods (Wegmann, Julia, Regev, &

Rychkova, 2007) that exploit the principles of

General Systems Thinking (GST) (Weinberg, 1975).

GST advocates that the component parts of a system

can be best understood in the context of

relationships with each other and with other systems,

rather than in isolation. An important way to fully

analyze a system is to understand the part in relation

to the whole. SEAM represents any perceived reality

as a hierarchy of systems. Each system can be

analyzed as a whole [W] - showing its externally

visible characteristics or as a composite [C] –

showing its’ constituents as a set of interrelated

parts. When applying SEAM to an industry, two

main aspects are analyzed: (1) How different

stakeholders cooperate together to achieve some

common objective; these groups of stakeholders are

referred to as value network, VN. (2) How these

value networks interact within an industry; these

interactions are referred to as Multi-Party

Relationship, MPR. The visual syntax of SEAM

includes block arrows for systems, annotated ovals

for externally visible properties, diamonds for

relations, simple lines for active participation to a

relation, dashed lines for pseudo participation to a

relation and rounded end-point lines for emphasizing

the identical nature of modelling elements.

Figure 1 presents a SEAM depiction of a pre-

deregulated Electricity Supply industry. The four

prominent entities that engage in the activities of this

industry are the Electricity Supply Company (ESC),

Electricity Consumer VN, Government VN and the

Environment VN. When viewed as a whole, the ESC

[W] exhibits the overall responsibility of

maintaining an end-to-end supply of electricity –

PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY

from generation to distribution. When viewed as a

composite, the ESC [C] reveals its’ constituent

subsystems. ESCs can have different architectures.

Nevertheless, for these subsystems to work as a

viable whole, each ESC has some form of

management subsystem (Beer, 1985) that oversees

the end-to-end delivery process.

Figure 1: Pre-deregulated Electricity Supply Industry.

Figure 2 presents a SEAM depiction of a

deregulated Electricity Supply Industry. The

vertically integrated ESC of the pre-deregulated era

stands unbundled into independent Generation,

Transmission and Distribution Companies. The

presence of multiple such companies constitutes

competition, and provides the Electricity Consumer

VN the choice to buy electricity from one

Generation Company, get it transmitted through

some other Transmission Company and receive the

end supply service from yet another Distribution

Company. These three companies when put together

represent the Electricity Supplier VN. From a

management perspective, each of these companies is

controlled by an independent management sub-

system which is strictly limited to its’ part of

industry operations, e.g. generation, transmission or

distribution. Unlike the pre-deregulated era, there

exists no end-to-end electricity supply management

system that can be held responsible for the overall

delivery of the supply.

Figure 2: Deregulated Electricity Supply Industry.

3 THE

RESOURCE-FEATURE-VALUE

TRIUNE

An industry is a complex composition of diverse

stakeholder groups. Suppliers are primarily

concerned about issues related to market share,

profit and return-on-investment; consumers are

concerned about cost, availability, reliability and

ease-of-use; governments are concerned about

collective welfare, institutional relevance and

political indispensability; and the issues of interest

from an environment point of view include habitat

and climate related ecological concerns. To realize

the benefits of Systems approach in analyzing the

different facets of an industry, it is important to first

identify a unifying concept that can act as a generic

platform for the interdisciplinary discourse required

in an industry. In this paper we exploit the notion of

value as the unifying concept and treat the above

mentioned stakeholder concerns as context specific

manifestations of the value concept.

Based on the analysis presented in (Ramsay,

2005), we define value as the tangible or intangible

effect accrued by a stakeholder through the

consumption or trade of a service or good. The

notion of value is at the heart of MPR modeling.

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

Stakeholders aspiring for a common set of value are

grouped together as a VN. MPR models industry

interactions as a value realization process between

VNs. VNs exchange resources, material and

information. Any resource addition to the VN affects

the stakeholders of the VN either in a favorable way,

realizing positive value, or in an unfavorable way,

realizing negative value. Figure 3 depicts MPR as a

bi-directional value realization process between the

different VNs in an Electricity Supply Industry.

Figure 3: Bi-directional value realization in MPR.

Value is a subjective notion, dependent exclusively

on stakeholder perceptions. An effect welcome by

some stakeholders may be completely rejected by

others. For example, time based electricity pricing

schemes where a consumer can pay less for off peak

electricity usage is perceived by many as a positive

value as it provides an opportunity to reduce

electricity bills by shifting workloads to low cost off

peak durations. For others this may not be a

welcome change as it results in increased night time

activity in the neighbourhood. As a result it is

desirable to explicitly specify the context in which a

value is created, delivered or consumed. We

accomplish this by introducing the concepts of

resource and feature.

We follow the definition given in (Barney, 1991),

where resources are defined as “... assets,

capabilities, processes, and information” in control

of the stakeholder. Thus resource can be considered

as the contribution an individual stakeholder can

bring to a VN. Feature on the other hand is a

composite attribute which exists only at the VN

level. Based on the resources available with the

different stakeholders of a VN, the VN may exhibit

different properties. These properties emerge from

the different combinations between these resources,

and are known as the features of the VN. For a given

industry, an MPR identifies the different resources

available with each VN, the set of possible features

that may emerge from them and the value these

features may bring to the other VNs. The same is

presented in Figure 4. The use of the term enterprise

in the figure is a more formal way of referring to

stakeholders constituting a VN. The resource,

feature and value concepts coupled with the GST

inspired whole-composite view of value exchange

guides our ontology design activity. Two important

design patters emerge from this combination.

D1. For every value created in an industry there

exists a supplier VN and an adopter VN

D2. Each VN in an industry acts as a supplier of one

set of value and an adopter of another set of value

Supplier and adopter are roles assigned to VNs

while analyzing MPRs. The supplier role signifies

ownership of resources required to create/produce

and deliver the services or goods. The adopter role

signifies ownership of resources required to

consume the service or good thereby realizing the

value advertised through the features of the service

or good.

Design Patterns have their genesis in the field of

architecture where they were first proposed as an

architectural concept by Christopher Alexander

(Alexander, 1979). These were later adopted in

software engineering, and are defined as an artifact

in the form of a construct, a model, a method or an

instantiation, which is general enough to be reusable

in solving commonly occurring problems (Gamma,

Helm, Johnson, Vlissides, & John, 1995). In this

paper we use these two design patterns as the basic

constructs for formally specifying the knowledge

required to formulate an overall understanding of

any industry.

Figure 4: The Resource-Feature-Value triune in MPR.

PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY

4 REGENT: A REGULATION

ENABLING ONTOLOGY

As defined in (Gruber, 1993), ontology is an explicit

specification of a shared conceptualization. It is

aimed at formalizing a specific view point that

enables/enriches the discourse on some aspect of

interest in the real world. The purpose of REGENT

is to enable the discourse on industry regulation.

Formalization of the concepts that constitute an

industry and the relationships that hold among these

concepts provides a common vocabulary with which

regulators can represent their understanding of the

industry. Such a standardized way of documenting

information is particularly useful in promoting

knowledge-level communication between the

different industry regulators.

Various ontology languages exist to represent

these concepts and relationships. The most

prominent of these is OWL (W3C, 2004). It is

developed by the World Wide Web Consortium and

consists of individuals, properties, and classes.

Individuals represent the objects in the domain of

interest, properties are binary relations

on these

individuals, and classes are interpreted as sets that

contain these individuals. Our reference to concept

and relationship maps to the notion of class and

property in OWL. Individuals are instantiation of

concept. OWL has three sub-languages: OWL-Lite,

OWL-DL and OWL-Full. The expressiveness of

OWL-DL falls between that of OWL-Lite and

OWL-Full. It is based on Description Logics

(Baader, Calvanese, McGuinness, Nardi, & Patel-

Schneider, 2003) which are a decidable fragment of

First Order Logic and are thus conducive for

automated reasoning. For this purpose we use OWL-

DL as the language for specifying REGENT. The

development of REGENT was done using the

ontology development tool, Protégé (Stanford

Center for Biomedical Informatics Research, 2010).

The visualizations presented in this paper have been

created using the OntoViz graphical plug-in in

Protégé. In the following, we present our design

choices for REGENT.

REGENT has two top level classes:

IndustryConcept class and

ConceptSpacePartition class.

IndustryConcept

is the foundational class for all

the concepts in an industry. It is based on the

Resource-Feature-Value triune detailed in sub-

section 2.3.

ConceptSpacePartition is the class

which subsumes the different viewpoints that can be

useful in analyzing the set of concepts detailed in the

IndustryConcept class.

4.1 The IndustryConcept Class

The IndustryConcept class formalizes the

concepts of resource, feature and value. Figure 5

presents the taxonomy of the

Resource class. The

Resource class has two subclasses: Commercial

and

Operational. This refinement of the

Resource class is a manifestation of the design

pattern D2. As depicted in Figure 3, every value

realization is a bi-directional process. We exploit the

dual nature of VN, i.e. the simultaneous role of a

supplier of one value and an adopter of some other

value, to classify the resources available with a VN.

From an industry perspective, a product or service

creation process has two parts – the operational

process of bringing the service or good into

existence and the commercial process of making it

tradable (Smith, 1904). The operational process is

related to the supplier role of VN; the supplier has

complete control over this process. On the other

hand, the commercial process is related to the

adopter role of VN. It is aimed at making the service

or good conducive for consumption and, thus,

requires taking an adopter perspective. Accordingly,

the set of resources in an industry can be divided

into two – the ones required to realize the

operational process, the

RS_Operational class,

and the others required to realize the commercial

process, defined as the

RS_Commercial class.

We can further refine this classification by

exploiting the insights of the supplier and adopter

process. At the supplier end, bringing a service or

good into existence entails two aspects – production

and delivery. For instance, in the Electricity Supply

Industry it is not sufficient for the electricity to be

generated at the generation units, it is equally

important that it is available at the prospective

location of consumption. Operational resources that

contribute towards the production of the industry

offering are categorized as the

RS_OP_Production

class while the ones that contribute towards the

delivery of the industry offering are categorized as

the

RS_OP_Delivery class. At the adopter end,

realizing the benefits of the offering entails two

aspects – reception and consumption. For instance,

the complementary nature of electricity requires the

availability of electrical appliances to consume

electricity. Commercial resources that contribute

towards the consumption of the industry offering are

categorized as the

RS_CM_Consumption class while

the ones that contribute towards the reception of the

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

Figure 5: Taxonomy of the Resource class.

Figure 6: Taxonomy of the Feature class.

industry offering are categorized as the

RS_CM_Reception

class. Finally, based on their

cognitive orientation a resource can be further

classified as tangible and intangible. The leaf nodes

of the taxonomy presented in Figure 6 refine the

higher level

RS_CM_*

and

RS_OP_*

classes as

RS_*_*_Tangible

and

RS_*_*_Intangible

subclasses.

Figure 6 presents the taxonomy of the

Feature

class. The

Feature

class is a manifestation of the

design pattern D1. As argued in (Ramsay, 2005), we

do not treat value as an intrinsic characteristic of a

product or service, and hence do not subscribe to the

value chain metaphor (Porter, 1985) which is often

interpreted to suggest that a value can be moved

from the supplier to the adopter. The notion of

supplier and adopter in D1 is to highlight the role of

VNs in supplying resources that lead to the

realization of some value at the adopter VN.

Nevertheless, connecting resources directly to value

will bypass an intermediate composition level where

resources from different enterprises within a VN

come together to define artifacts with some potential

value content. This concept of composition is

concretized in the

Feature

class. Features can,

thus, be viewed as the potential value of a

combination of one or more resources of a supplier

VN. This potential value gets transformed into

realized value when the adopter VN consumes the

underlying artifact i.e. the industry offering. Thus

feature and value differ only in the context of the

observer. Feature expresses the view of the supplier

of his product or service and value is the view of the

adopter of the consumed product or service. This

difference is captured as property constraints and is

further detailed in Section 4.3.

From a taxonomy point of view, interpretation of

features as potential value results in similar

refinements of the

Feature

and

Value

classes. The

taxonomy of the

Feature

class is presented in

Figure 6. We posit that the

Value

class has a similar

taxonomy tree hence do not present it separately.

The following discussion on the specificities of

feature refinement applies equally to the value

concept.

The

Feature

class has two subclasses:

FT_Utility

and

FT_Warranty

. Utility and

warranty are two concepts publicized as part of the

Information Technology Infrastructure

Library (ITIL) (OGC, 2007), developed by the

UK's Office of Government Commerce (OGC)

for Information Technology Services Management.

Utility captures the functionality offered by a

product or service and is informally interpreted as

‘what the industry offering does’. On the other hand,

warranty is the promise that a product or service will

meet its’ agreed requirements, informally interpreted

as ‘how the industry offering is done’. In the

PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY

Requirements Engineering field, these are often

termed as the function and non-functional

requirements (Gause & Weinberg, 1989).

The utility of a service or good is usually well

understood. It is the warranty aspect that is open to

interpretation and is hence further refined. A

warranty can be related to the availability, reliability,

ease of use and cost of the service or good. The

FT_WR_Availability

class represents the

attributes that capture the readiness of the service or

good to be consumed by the adopter. The readiness

can be both temporal

, FT_WR_AV_Temporal

class,

and spatial,

FT_WR_AV_Spatial

class. The

presence of electricity supply at the time and place

of consumption will constitute the temporal and

spatial availability of the service provided by the

ECN. The objects of the

FT_WR_Reliability

class represent the appropriateness of the service or

good for consumption. Appropriateness can be

achieved by ensuring safeguards against disruptive

failures, the

FT_WR_RL_DisruptionProtecting

class, and damaging failures, the

FT_WR_RL_DamageProtecting

class. For

instance, the use of surge protector equipment can

protect against slight variations in electricity supply

but a line breaker would be required to stop the

supply in the event of very high variations in supply.

The

FT_WR_EaseOfUse

class represents the (in)

convenience of evaluating –

FT_WR_EU_Evaluation

, procuring -

FT_WR_EU_Procurement

, and consuming -

FT_WR_EU_Consumption

, a product or service.

The

FT_WR_Cost

class captures the attributes that

define the cost of the service or good. The cost can

be interpreted both in monetary,

FT_WR_CT_Monetary

, and in non-monetary terms,

FT_WR_CT_NonMonetary

4.2 The ConceptSpacePartition Class

The taxonomy of the

ConceptSpacePartition

class is presented in Figure 7. As the name suggests,

this class creates a partition on the set of concepts

represented in the

IndustryConcept

Class. A

partition imposes a certain view of the industry. The

Enterprise

subclass partitions the various

concepts in an Industry along the well established

boundaries of legal ownership and undertaking. For

instance every resource in an industry is owned by

some enterprise.

Enterprise

subclass is the default

partition of the objects represented by

IndustryConcept

class.

The

ValueNetworkPartition

subclass is a

manifestation of the Value Network concept in

SEAM. It relies on the default

Enterprise

class

imposed partition on industry concepts. More

specifically, the

ValueNetworkPartition

subclass partitions the various concepts in an

industry along the common intent of the enterprises

where these concepts originate. It is important to

note that the absence of an explicit intent is also a

commonality and, hence, can form a valid partition

of the Industry concepts. As a result, the

ValueNetworkPartition

class is further sub-

divided into

VNP_Strategic

and

VNP_NonStrategic.

The strategic subclass refers

to a partition that is based on some maximizing

something – profit, welfare, power, etc. By contrast,

the non-strategic subclass is blind and has no

objective, no preferences, and no foresight, for

instance the Environment (Birchler & Bütler, 2007).

Figure 7: The Taxonomy for ConceptSpacePartition Class.

4.3 Property Constraints

The properties that bind the different concepts in

REGENT are depicted in Figure 8. Properties in

OWL are binary relations constraining the

interaction between any two classes. For any

property connecting an object o1 to object o2 an

inverse property can also be specified which

connects object o2 with o1. In the following, we

discuss these properties on a class by class basis. For

the sake of clarity, words starting with upper case

alphabet are class names and the same when written

in lowercase represent objects of that class.

The objects in the Resource class are constrained

through two properties. 1) The hasOwner property

mandates that each resource is connected to some

enterprise. To ensure the uniqueness of this relation

we limit the property to have a single value i.e. each

resource has only one owner. In OWL this is

accomplished by setting the property characteristics

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

Figure 8: A visual representation of properties constraining REGENT concepts.

as functional. The corresponding inverse property

that connects an enterprise to its resources is the

isOwnerOf property. The one-to-many nature of this

relation is visually represented with an asterisk (*).

An enterprise can own more than one resource. 2)

The isProviderOf property links a resource to the

feature it contributes. The corresponding inverse

property that connects a feature to its constituent

resources is the hasProvider property. Both of these

properties represent a one-to-many relation – a

resource can enable more than one feature and a

feature can be enabled by more than one resource.

The objects in the Feature class are constrained

through four properties. 1) The

hasTransformationTo relation specifies the values

that are realization of the features. The

corresponding inverse property

isTransformationFrom specifies the features that

constitute the value. Both of these relations exhibit

multiplicity – multiple features can aid a value

creation and multiple values can be enabled by a

feature. 2) The hasSupplier relation specifies the

supplier value network for a feature. This is a single

value relation which restricts each feature to have a

unique supplier. The same is imposed by setting the

functional characteristic of this property. The

corresponding inverse property, isSupplierOf, is a

multi-valued relation. A value network can be a

supplier of more than one feature. 3) The

hasProvider relation is already discussed above. 4)

The hasAdopter relation specifies the adopter value

network for a feature. The corresponding inverse

property, isAdopterOf, specifies the set of features

that a value network adopts. Both of these are multi-

valued properties – a value network can adopt

multiple features and a feature can be adopted by

multiple VNs.

The objects in the

Value

class are constrained

through three properties. 1) The isDeliveredTo

property specifies the value network where a value

is realized. This is a single value property; a value is

closely associated to the perception of the consumer

and, is hence, unique to the value network. We do

this by setting the functional characteristic of the

property. The corresponding inverse property,

hasDeliveryO, specifies the value that a value

network consumes. 2) The hasPointOfCreationAs

property specifies the precise enterprise which

consumes this value. Again, consumption is unique

to an enterprise; hence, this property is a single-

valued function. The corresponding inverse

property, isCreationPointFor, identifies all the

values that are consumed by an enterprise. This is a

multi-valued property. 3) The

isTransformationFrom property has been detailed

earlier.

In addition to the properties exhibited by the

Feature, Resource and Value class. There exists an

additional relation between the objects of the

Enterprise class and the objects of the

ValueNetworkPartition class. The property

isParticipantOf identifies the value network to

which the enterprise participates. To highlight the

fact that an enterprise when part of two value

networks does so in different roles, we model this

relation as a single-value property – setting its

PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY

functional characteristic. The corresponding inverse

property, hasParticipant, is a multi-valued property

and identifies all the enterprises that are members of

a VN.

5 THE CASE OF URBAN

RESIDENTIAL ELECTRICITY

SUPPLY

In this section, we use REGENT to provide a

systematic view of the Urban Residential Electricity

Supply Industry (URESI). Details about the URESI

were gathered from various reports (US Aid, 2007)

(Malaman, April, 2001), best practices (OECD,

1997), guidelines (Queensland Competition

Authority, 2001), national regulations (GOI, 2002)

and personal communication with Industry

representatives. The later was done through a

consultation meeting, ‘The Role of IT in Regulatory

Governance’, held on December 05, 2009 at TATA

Consultancy Services Ltd., Lucknow India.

We begin by identifying the different

stakeholders in a URESI. Stakeholders with

common objectives, or lack of objective, are

grouped into same Value Network. Four VNs

emerge from this exercise: The Economic Value

Network (ECN) that represents enterprises with

primarily economic motivation, Social Value

Network (SCN) that represents enterprises with

primarily social motivation, Environmental Value

Network (EVN) that represents non strategic

enterprises and Government Value Network (GVN)

that represents the collective welfare as the

overriding motivation. The enterprises constituting

the ECN are Generation Company, Transmission

Company and the Distribution Company. The

enterprise constituting the SCN is the Urban

Household. The enterprises constituting the ENV are

Climate and Habitat. Climate represents the macro

level aspects of the environment while habitat

represents the micro level aspects of our immediate

surroundings. ECN and SCN are generalizations of

the Electricity Supplier Value Network and the

Electricity Consumer Value Network mentioned in

the Sections 2 and 4.

5.1 Resource Identification

For each of these VN, we take a commercial and

operational view of the value exchange and identify

the tangible/intangible resources that aid the

production/delivery of the VN offering and the

reception/consumption of the counter offering from

other VNs. These resources along with the related

Enterprise and Value Network are listed in Table 1.

In the case of ECN, the Generation Company

provides fuel specific generation plants (r73-83) as

tangible resources for the production process. The

Distribution and Transmission Companies provide

the necessary network, both large area and local

area, to transport the generated electricity to the

prospective place of consumption. The elements of

these networks (r51-63) represent the tangible,

delivery related operational resources in ECN. To

enable the return path, the Distribution Company

makes available different Billing plans (r27-31),

Collection modes (r32-35), Communication

channels (r38-40) and Maintenance Equipments

(r36, 37) as tangible resources for receiving the

revenue and information (feedback) flow. The

accompanying intangible resources for this purpose

include billing, repair and support related

capabilities (r21-25). The information resulting from

this feedback is consumed by Generation Companies

in fine tuning their generation strategies, for instance

operate the generation units in the increasing order

of marginal production cost or in the increasing

order of marginal emission (r1, 2).

In the case of EVN, the Habitat provides the

different kind of fuels such as Gas, Coal, Nuclear,

etc. (r88-96), as tangible resources for the

production process. On the delivery front, EVN

provides an intangible resource in the form of ease

of procurement of natural resources. It is the

procurement feasibility (r47) that allows a natural

resource to be available as a fuel in the electricity

production process. To enable the return path, the

Climate makes available air, land and water (r41-43)

as tangible resources for receiving the pollution that

results from the electricity production process. The

pollution is finally consumed as a displeasing benefit

through the five human senses (r3-7), which act as

the intangible consumption resource.

In the case of GVN, policy making exploits the

following four resources available with any

government institution: information (Nodal), power

(Authority), money (Treasure) and management

(Organization). The NATO concept was introduced

by (Hood & Margetts, 2007) and has since been

widely used to study the working of governments.

The information, power and management (r68-70)

represent intangible and money (r97) represents

tangible, operational resources for producing high

level policies.

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

Table 1: List of Resource identified in URESI.

To deliver its policies the government uses various

social and economic instruments (r48-50, 64-67). It

receives the benefits of policy making through

election, nominations and public opinion formation

(r26, 44, 45). Any political capital thus accrued is

encashed by reinforcing (r8-10, 12) it resources for

further policy making.

In the case of SCN, the demand for electricity at an

Urban Household is a combination of its load

requirements and the willingness/capability to pay.

The tangible resources that produce this demand

include the household monthly budget and monthly

load (r98, 99). The corresponding intangible

resources include the spending strategy and the

consumption characteristic (r71, 72). In an urban

setting, there are no extra resources required to make

this demand visible to the ECN, as a result there are

no delivery related resources listed for SCN.

Nevertheless, this is not always the case. In a rural

setting, the economic prospects of serving an

isolated demand may not be too attractive. Very

often, in these situations, the GVN lends its

resources to deliver such demands, aka Universal

Service Obligation. On the commercial front, the

SCN obtains a connection using its identity as the

resource to guarantee the intent of upholding the

terms and conditions. The household identity (r46) is

thus the tangible, reception oriented commercial

resource of SCN. Finally, the different kind of

electrical appliances (r13-20) in the household and

the usage behaviour (r11) of household members act

as the tangible and the intangible resources required

to consume electricity.

Table 2: List of Feature identified in URESI.

PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY

5.2 Feature Identification

Every VN in an industry contributes some service or

good to other VNs in the industry. As described in

Section 2.4.1, a VN offering can be detailed along

the utility and warranty dimensions. Table 2 lists the

utility and warranty details of the VN offerings in

the Urban Residential Electricity Industry.

The utility of ECN is to provide electricity (f1)

for residential purposes. For the electricity supply to

be useful, it provides a set of warranties related to

temporal (f15, 16) and spatial availability (f12),

dollar (f42-46) and non-dollar cost (f49, 50), ease of

use (f25-33) and reliability (f5, 6, 10).

The utility of ENV offering is to provide natural-

resources (f2) required for electricity generation.

These natural-resources can either be provided in

perpetuity (f17) or only for a limited period of time

(f18), with little (f52) or significant (f51) ecological

impact, thereby constituting the warranty of the

ENV offering.

The utility of SCN is to exhibit demand (f4) for

electricity. Demand includes both the expected load

and the willingness/ability to pay. The temporal

sensitivity of consumption (f35-40, 48), the

specificities of the expected electrical load (f23, 41),

tolerance to qualitative variance (f54) and the

payment guarantees (f9, 13, 20, 24) are the

warranties that detail the utility offered by the SCN

to other VNs in the industry.

The utility of GVN is to provide the high level

policy (f3) framework that guides the industry in the

desired direction. These policies can be evaluated

for their suitability of implementation - command &

control (f21) or reward & penalty (f22). A simplified

(f34), sensitive (f7, 11), stable (f19) and uniform

policy regime (f14) limits the industries’ cost of

compliance (f47) and results in the industry growth

(f53).

5.3 Value Identification

Every VN in an industry receives some value in

return to his contribution to the Industry. Value can

either be positive or negative, solicited in the case of

strategic VNs or unsolicited in the case of non-

strategic players. Table 3 lists the utility and

warranty of the different value created in the Urban

Residential Electricity Supply Industry, the VNs that

adopt these value and the enterprises in the adopter

VN where these value are realized.

The utility of the positive value realized at the ECN

is profit (v1-3). To accomplish this, the Distribution

Company tries to forecast demand (v8), inform

policy makers about its requirements (v12), exploit

the need of consumers for electricity (v18) and

ensure continued flow of revenue (v19). On the

transmission front, the spatial diversity of demand

(v14) creates more business opportunities for the

Transmission Company. Continued availability of

fuel (v17) for electricity generation is the primary

warranty for a Generation Company. All the ECN

enterprises bear the transaction cost (v29-31) of

doing business under some policy regime.

The utility of the negative value realized at the EVN

is pollution (v4, 5). At the micro level the pollution

can lead to a variety of displeasures (v34-38) to the

inhabitants of a certain geographical area. At the

macro level pollution can manifest itself as

undesired alterations to climate (v39-41).

The utility of the positive value realized at the

SCN is the comfortable living (v7) of household

members. The household convenience is maximised

by ensuring safe & continued operation of electrical

appliances (v13, 21) and giving the household

complete freedom of the financial (v33) and social

aspect (v16, 23) of electricity supply. Simplifying

the interactions between the household and the

service provider (v28) also brings added comfort to

the household. In certain situations, specificities of

the supply network may impose restrictions on the

use of some types of appliances (v10), for instance

heavy load motors on single phase connections.

The utility of the positive value realized at the

GVN is to ensure collective welfare of the society by

accumulating political capital (v6). Achieving

independence in electricity supply (v9) through

increased investments (v15, 20, 26), making

electricity available for every one (v24), ensuring

minimum quality standard of supply (v27) at a fair

price (v32) are important warranties of electricity

supply that affect the consumers at large.

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

Table 3: List of Value identified in URESI.

5.4 Establishing Regulatory Oversight

Table 4 presents the mapping between the different

members of the Resource, Feature and Value set.

This mapping exploits the property constraints

detailed in 2.4.4. In the interest of space, here we

only elaborate the realization of auditory displeasure

(v34) as a negative value created at the Habitat by

the introduction of time based pricing scheme in the

electricity supply industry.

Balancing the supply and demand for electricity

is central to the proper functioning of an electricity

grid. The demand, however, tends to exhibit time

sensitivities with more electricity required during

specific times of the day or year, for example

increased lighting requirements during the night and

higher climate control needs during peak

winter/summer season. In the absence of efficient

large scale electricity storage techniques such

variability in demand can only be met through

flexible generation capabilities. Not all generation

units support variable output. For example, nuclear

power plants must be run at close to-full capacity at

all times whereas production from other sources

such as wind and solar, though inherently variable in

nature, remains hard to predict.

Table 4: Resource-Feature-Value mapping in URESI.

Further, the cost of electricity production varies

from one type of generation unit to another.

Generation Company operates these units in an

increasing order of marginal costs (r1). Thus

increased generation required to meet higher

demands (peak hours) results in a higher per-unit

cost of electricity. Similarly, during periods of low

demand (off-peak hours) generation units with high

marginal costs are cycled down resulting in a lower

per-unit cost of electricity. Installation of smart

meters (r49) allows the Distribution Co. to extend its

billing capability (r22) and help the ECN introduce

time of use (ToU) electricity pricing tariffs (f44).

ToU presents economic incentives to enterprises in

ECN and SCN alike. Electricity suppliers can

increase profits by charging a higher per-unit cost

during peak hours and consumers can minimize their

bill (f48) by moving their time insensitive workloads

(f35) to off-peak hours when the per-unit cost is low.

The sensitivity of households to electricity bill is a

function of their monthly budget (r94) and spending

strategy (r66). Any attempt by households to move

electricity workloads to off-peak hours is limited to

the rescheduling of time insensitive workloads (f35)

which in turn depends on the availability of requisite

PANHAA SYSTEMIC DESIGN OF REGULATION ENABLING ONTOLOGY

electrical appliances (r14, 19) and batch oriented

workload characteristics (r67).

The temptation to move workloads to hours of

low overall activity, e.g. night time, may result in

increased noise levels during odd hours leading to

the realization of a negative value of auditory

displeasure (v34) to surrounding neighborhoods, the

habitat. Use of REGENT to formally represent the

value realization process exposes the industry

concepts that enable it and the relationship these

concepts have with the real world. Industry

regulators can use this knowledge, for instance, to

clearly identify the different industry elements that

need to be monitored so as to track the realization of

a given value of interest. An AND/OR graph

depicting the value realization process for auditory

displeasure (v34) is depicted in Figure 9.

Figure 9: Monitoring auditory displeasure.

6 RELATED WORK

The role of ontology in formalizing the concepts in a

knowledge system is well established. In the context

of industry, ontology development has primarily

focused on formalizing the domain specificities. The

concepts and relationships that occur between

entities from different domains have not attracted

much ontological attention. E3 value (Gordijn &

Akkermans, 2003) is one of the few attempts to

study the value exchange between the stakeholders

in an industry. It is, however, restricted to analyzing

the economic exchange between companies active in

an e-commerce business. Some ontology

development has also been recently noticed in

understanding regulation, for example IPROnto

(Delgado, Gallego, Llorente, & García, 2003) which

presents a formalization of the concepts in digital

rights management. In the Electricity industry power

quality measurement related ontology has been

presented in PQONT (Küçük, Salor, Inan, Çadırcı,

& Ermis, 2010).

7 CONCLUSIONS

REGENT enables an explicit specification of multi-

party relationships in an industry by formalizing the

concepts that influence the realization of stakeholder

value. A systematic representation of industry

knowledge will expose any deficiencies in

regulators’ understanding of the industry, thereby

assisting the regulator in developing a holistic view

of the industry. REGENT is an important first step

in our larger effort of developing a knowledge

system for the regulation of utilities.

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