Data, Ontologies and Decision Making
An Inter-disciplinary Case Study
Stephen Dobson, Arun Sukumar and Tony O'Brien
Sheffield Business School, Sheffield Hallam University, Howard Street, Sheffield, U.K.
Keywords: Information Governance, Data Quality, Shared Knowledge, Decision Making.
Abstract: Several studies have highlighted the need for information governance in organisations and the importance of
quality data in decision making. Especially when considering the increasing need for collaboration, data-
sharing, and interoperability. Organisations are not immune to importance of information governance and
given the recent spate of information- related disasters and accidents, information risk management has
become all the more important and its link to corporate governance explicitly noted and mapped. Data
driven organisations typically lack the structure to associate ontologies tagged with data and are unable to
offer the rich semantics that sometimes can enrich a decision maker's worldview. Data documents need not
necessarily capture relationships and ontologically there are unable to offer the rich semantics that the data
can sometimes show. The value of data is enriched by the associated semantics and modern enterprise
systems are inadequate in their capacity to capture this rich source of knowledge and its representation. This
research borrows approaches from urban sustainability to understand domain ontologies and their
implications in system design and subsequent improvement in the value of organisational information. It
uses case studies to highlight ontology modelling and how such an approach can add value in an
organisational context specifically in the domains of system design and information value chain.
1 INTRODUCTION
The traditional view of data management within
organisations have stressed on the notion of the
availability of quality data at appropriate levels of
decision making, but little is known about the value
of semantics in such decision making scenarios. The
complexity of inter-organisational systems and
speed at which decisions are made makes it hard to
encode the semantics associated with data. Data
documents typically available at the decision table
are unable to cope with relationships among other
documents and ontologically there are unable to
offer the rich semantics that the data can sometimes
show. The value of data is enriched by the
associated semantics and modern enterprise systems
are inadequate in their capacity to capture this rich
source of knowledge and its representation.
2 DATA AND ONTOLOGY - THE
PROBLEM
Ontology is concerned with beliefs about reality;
that is, the values and assumptions which support
our worldviews, whether explicitly or tacitly held.
Ontology is then the framework of core values upon
which we base our understanding of the world and
as such represents taken for granted rules and
relationships. A more specific use of the term
considers the formalization of ontology into a
structured and computer-useable manner, i.e. the
applied or ‘formal’ ontology. The creation of formal
ontologies typically starts with brainstorming and
stakeholder activities designed to reveal implicit
definitions and understanding and is gaining
increasing interest as an important means to encode
knowledge gained from a group, subject area, or
domain in order to support knowledge sharing and
increased communication (Teller et al., 2008;
Cimiano et al., 2009; Rettinger et al., 2012; Dobson,
2012): “Ontologies include computer-useable
definitions of basic concepts in the domain and the
relationships among them and are increasingly
valued because of the ever-increasing need for
knowledge interchange” (Mounce et al., 2010, p.
40). The practice of formalising concepts has found
particular relevance within the computer sciences
563
Dobson S., Sukumar A. and O’Brien T..
Data, Ontologies and Decision Making - An Inter-disciplinary Case Study.
DOI: 10.5220/0004616905630568
In Proceedings of the 15th International Conference on Enterprise Information Systems (IVM-2013), pages 563-568
ISBN: 978-989-8565-60-0
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
and organisational studies and especially in relation
to the semantic web (Brüggemann and d’Amato
2012). The application of formal the ontology in
service design is described by Akkermans et al.,
(2004).
The underlying logic behind data aggregation is
fixed in system design. For example, a balanced
scorecard approach necessitates the aggregation of
multiple performance dimensions which are directly
determined by the values and world-views
(ontological position) of those involved in system
design. Whilst data invariably changes - knowledge
is hard coded in the data structure. That is the
domain knowledge belonging to those for whom the
system is intended and/or helped design/commission
the system. Integrating multiple domains does not
necessarily (but may) require changes to data type
and format, but will require knowledge structure to
be extensible and changeable to reflect multiple
perspectives. These are shared structures.
To address the interoperability of data and multi-
sectoral communication, research needs to focus on
formalisation of organisational ontologies (W3C).
Organisational ontologies are beneficial for
enhancing communication, cooperation and
therefore 'metabolic' transaction (Teller et al., 2008).
More importantly it is from these cross-domain
(functional) conceptual models that we might start to
move toward integrated systems- thus leading to an
integrated organisational practice. This work
requires conceptual models that are both
semantically extensive, so as to embrace the many
definitions and perspectives, as well as being
extensible.
Research in this area -coupling data and
organisational ontologies has been minimal, but
there have novel approaches developed in other
disciplines to study the problem of domain ontology.
Here we present a case study that looks into the
issue of urban sustainability. It specifically focuses
on the formalisation of urban domain ontologies as
an important step in understanding the pathways that
can lead to an integrated urban practice. Lessons
learnt from this case study can point to ways that can
help us to better understand the value of data in
organisational ontologies and in the overall
performance of the organisation.
3 CASE STUDY
Urban areas and cities are described as the driving
forces behind the global economy and are the largest
contributors to national output, innovation and
employment (Schauser et al., 2010). As such they
are more than simply built form – cities are the
culmination of inflows and outflows of knowledge,
energy, materials and resources. Cities are dynamic
spaces through which multi-level organization of
transformation processes are performed. It is here
that the three pillars of sustainability – the economic,
social, and environmental - are most entwined,
creating complex and multi-level inter-dependencies
which serve to blur organizational and sectoral
boundaries of concern.
Managing strategic change toward the
sustainability of cities therefore raises key
conceptual challenges, particularly within the
context of multi-sectoral/ multi-stakeholder
complexity. Planning measures need to be
considered through a coherent framework capable of
identifying complex inter-relationships and
interdependencies - such as those existing between
the numerous processes and services which support
the economic, social, and environmental dimensions
of urban areas. The dispersed nature of
responsibility in managing aspects of urban systems,
as evident for example in partnership approaches for
the delivery of public services, forms an adaptive
infrastructure which is often difficult to model in
terms of impacts and longer term effects. Integrated
Assessment (IA) is emerging as a city-wide
approach to address such complexity and aims to
identify the connectivity between all urban systems;
whether natural, human, or technological (Hall et al.,
2009; Dawson, 2011). Communities are key
stakeholders within this information ecology. The
European Union Community Strategy Guidelines
2007-2013 encourage an 'integrated approach'
toward urban cohesion to support economic growth
and job creation as well as support social and
environmental goals. Integration of knowledge,
information and data is a key concern in this context
drawing upon two potential approaches broadly
characterised by either replacement (i.e ERP - single
system, transform existing systems and processes
under one umbrella) or a more open architecture;
extensible, configurable, connecting and translating.
The City Region Leadership Programme (CRLP)
is a postgraduate certificate which aims to provide
University-accredited learning to those in a position
of leadership predominantly within the public sector.
It was developed as a partnership between the two
Sheffield universities (University of Sheffield and
Sheffield Hallam University) and four major public
sector organisations, Sheffield City Council (SCC),
NHS Sheffield (NHS-S), South Yorkshire Fire and
Rescue Service (SYFRS) and South Yorkshire
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
564
Police Service (SYPS). Its overall aim is to create
innovative stakeholder-led collaborative learning
opportunities, which enhance individual and
organisational performance and economic outcomes
in the region. The programme involves four modules
of teaching and the approach presented here
represents one component of a module on Customer
Centric Services. The aim of this component is to
challenge the individual to explore their tacitly held
worldviews (ontological position) of services
relevant to them with the aim of finding semantic
commonalities and differences with representatives
from different public services. The hope is that
semantic connection may pave the way for actual
connections between services and so the exercise
aims to challenge and reveal both individual and
also inter-organisational definitions of services.
The CRLP was initially developed for public
sector services, but the course has demonstrated that
benefits and value are created by cross-agency
working and so now it has been fine tuned to
develop broader partnership working between
public, private and third sector organisations. The
need for a collaborative approach to service design
and delivery is acutely recognised in the CRLP
module, 'Customer Centric Services'. Here,
practitioners are encouraged to perceive how service
user 'customers' might interact with services as
interconnected parts of their journey and particularly
to understand the role of customer involvement in
the development and review of services. A key
emphasis on this part of the CRLP is the process of
building strategic alliances and partnerships to help
configure future services. This requires a keen
understanding of semantic definitions of core
concepts which underpin service ontologies if new
delivery partnerships are to be defined or old ones
redefined. A learning exercise 'game' aimed at
encouraging the collaborative processes of
innovation and 'illumination' (Wallas, 1926) was
devised to help render explicit these often tacit
understandings of what services are - and more
importantly, could be.
Through a series of practitioner workshops and
developed as part of a leadership and management
programme, formal ontology modelling is
introduced as an important means to help build: a)
an integrated understanding of sustainability as a
multifaceted concept, and b) a conceptual
framework from which to create better
understanding of both the intended and unintended
effects relating to service delivery in the longer term.
The work here illustrates just one part of a
necessarily holistic approach to the semantic
understanding of city systems in order to support the
integrated management of urban sustainable
development. Whilst we must acknowledge the
challenge in applying such a tool in practice any
successes are likely to bring significant benefits to
the sustainable management and development of
cities globally. The dimensions of this are:
1) The formation of networks/ communities
practice which are drawn together both by a
common goal and vision, but more
importantly a shared and explicit conceptual
framework.
2) The creation of a conceptual framework
(formal ontology) which fosters common
understanding and aids cross-domain
communication.
3) Integrated assessment of service delivery
within the context of a complex urban system
The activity aims to encourage individuals to
explore their own tacit understanding and definitions
of concepts related to services. However by sharing
these, inter-personal and inter-organisational
variation is introduced through the connecting of
sub-concepts.
For example, to rethink our definitions of public
services, and achieve real collaboration through
closer commonalities in values and understanding,
we must consider how we define our assumptions
and worldviews through language. However,
common language does not ensure we share
understanding, values or expectations and so
conceptual modelling and the formalization of
ontology is a key means to explore and reveal this.
The approach:
1. Each person begins by having their own
service background in mind; then one person starts
by writing down a word/concept related to their own
service (for example: the Police service might write
down the word 'safety')
2. The flip-chart paper is passed around anti-
clockwise and the game progresses through many
'rounds' of the table. When it is a person turn, they
must choose any word on the sheet and think of how
that word might relate to their own service. They
must write another word which they feel relates to
one of those on the sheet and draw a line linking
between them. The nature of the relationship is also
indicated on the line. For example, a teacher playing
the game may decide that children's well-being is a
'part of' safety. In this case the words 'children's
well-being' would be written down and a line drawn
to link this with 'safety'; 'part of' would be indicated
on the linking line.
Data,OntologiesandDecisionMaking-AnInter-disciplinaryCaseStudy
565
3. Each person has to add a concept relating to
their own service and if possible draw and define its
link to an existing one on the sheet. This should be
quite rapidly done. If they cannot think of a link they
must still write down a word/concept but it will
remain floating, i.e. isolated.
4. When it is a player's turn, if they can see a
connection to an isolated word they may choose to
draw a link and define the link before taking their
normal turn.
5. The process progresses for about 20 minutes -
if there are numerous teams, the ones with the most
connected words and fewest isolated words 'wins'.
6. At the end, each participant must write their
service in the same coloured pen they used for the
game. This acts as a 'key' when reading the results.
The purpose is to begin to reveal the ontological
positions whilst also revealing your own. By colour
coding this exercise, interesting themes start to
emerge. For example, certain colours may regularly
go together illustrating potentially stronger parallels
or links in thinking. Alternatively, the presence of
many isolated terms may indicate a difficulty in
establishing commonalities within the team at a
basic conceptual level. However, on the whole most
people can see the relevance of words to their own
service or profession and therefore links are most
typically made - even if they are a result in slight
semantic differences. Since any player may choose
to link isolated terms before making their own move
we may also observe which individuals/services
appear to see the connections between others.
Perhaps they already, or have the potential to,
perform important brokering/intermediary roles
between services.
In the example illustrated in Figure 1, the Police
Service started the game with the word ‘Criminal’ to
which a representative from voluntary sector
associated this as a person with mental health
issues. The professional from services related to
Temporary Accommodation related Anti-Social
Behaviour (ASB) to the word 'Criminal' and
interestingly, the Environmental Services associate
ASB with environmental quality. It is also evident
from the larger number of red connections that it is
the Voluntary Sector representative who can see the
greatest number of cross-sectoral connections.
Whilst these are just very brief snapshots of such an
exercise it is possible to consider the value of this
kind of approach in introducing departure (variation)
from service-specific ways of perceiving the
ontological/semantic relations between terms and
concepts.
The service ontology which starts to emerge
from this exercise is one formed from the shared
perspectives of those around the table. For example,
the links between ASB and environmental quality is
an important dimension to be revealed and arguably
only present because of the presence of the
participant from Environmental Services.
4 CHALLENGES
AND CONCLUSIONS
Working together therefore also requires a level of
cognitive shared understanding starting from the
very semantic framework through which we
communicate ideas. The above example is a means
to help reveal shared semantic knowledge in
practice. Shared understanding is not fixed and so
ontological structure underpinning data sharing
needs to be open, shared, and changeable to reflect
emerging and future uses of information across
domains. The design of enterprise wide systems
often do not facilitate this, their environment is
around modelling a holistic solution for distinct
operations. An ERP approach typically encompasses
an organisation's Financials, Human Capital
Management, Operations and Corporate Services.
This is a comprehensive approach whereby
efficiencies and productivity are gained through
seamless integration of functions. Whether on
premise, or in the cloud - a company's processes and
data governance are ideally aligned, or optimised, to
match ERP system requirements. The underlying
ontological structure is determined by the structure
of the system and reconfiguration can be complex
and problematic. System design methodologies in
future must also recognise this inherent difficulty
and for an organisation to achieve its true potential,
an effort to incorporate the underlying ontological
structures can lead to improved decision making and
can reflect a phenomenon where value addition in
relation to data can be realised.
Ontology modelling can ruffle feathers in view
of system designers but it is important that design of
systems carry this component where shared
understanding and assumptions can be
accommodated. Data enters organisational
boundaries but conversion to information and an
increase in its value can be achieved by
accommodating shared semantic knowledge.
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
566
Figure 1: Example concept map.
REFERENCES
Akkermans, H., Baida, Z., Gordijn, J., Peiia, N., Altuna,
A., & Laresgoiti, I. (2004). ‘Value webs:
Using ontologies to bundle real-world services’.
Intelligent Systems, IEEE, 19(4), pp. 57-66.
Amaral MHR, Loch CH, Wilkinson D, Huberman BA
(1996) Scaling behaviour in the growth of companies.
Nature 379, pp. 831–848.
Batty M, Longley P (1994) Fractal Cities: A Geometrybof
Form and Function (Academic Press, San Diego, CA
and London).
Bhardwaj N, Yan K, Gerstein MB (2010) Analysis of
diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the
middle levels. Proc Natl Acad Sci USA 107, pp 6841–
6846.
Brüggemann, S. and d’Amato, C. (2012) Collaboration
and the Semantic Web: Social Networks, Knowledge
Networks, and Knowledge Resources IGI Global
Cimiano, P., Mädche, A., Staab, S., & Völker, J. (2009).
Ontology learning. Handbook on Ontologies, pp. 245-
267.
Connelly, S. (2007). ‘Mapping sustainable development as
a contested concept’ Local Environment, 12(3), pp.
259-278.
Dawson, R. J. (2011). ‘Potential pitfalls on the transition
to more sustainable cities and how they might be
avoided’ Carbon, 2(2), pp. 175-188.
Dobson, S. (2012) ' The Reflexive Practitioner:
Knowledge Discovery through Action Research'
in (eds) S. Brüggemann and C. d’Amato Collaboration
and the Semantic Web: Social Networks, Knowledge
Networks, and Knowledge Resources IGI Global pp.
135-148.
Erwin D. H., Davidson EH (2009) The evolution of
hierarchical gene regulatory networks. Nat Rev Genet
10, pp. 141–148.
Guimer` R, Danon L, D ́aıaz-Guilera A, Giralt F, Arenas
A (2003) Self-similar community structure in a
network of human interactions. Phys Rev E Stat
Nonlin Soft Matter Phys 68, 065103.
Data,OntologiesandDecisionMaking-AnInter-disciplinaryCaseStudy
567
Hall, J. W., Dawson, R. J., Walsh, C. L., Barker, T., Barr,
S. L., Batty, M., & Zanni, A. M. (2009). Engineering
Cities: How can cities grow whilst reducing emissions
and vulnerability?’ Newcastle University: October.
Hirata H., Ulanowicz R (1985) Information theoretical
analysis of the aggregation and hierarchical structure
of ecological networks. J. Theor. Biol. 116, pp. 321–
341
Krugman PR (1996) Confronting the mystery of urban
hierarchy. Journal of the Japanese and International
Economies 10, pp. 399–418.
Ma H., Buer J., Zeng A (2004) Hierarchical structure and
modules in the escherichia coli transcriptional
regulatory network revealed by a new top-down
approach. BMC Bioinformatics 5, pp. 199
Mihm J., Loch CH, Wilkinson DM, Huberman BA (2010)
Hierarchical structure and search in complex
organizations. Management Science 56, pp. 831–848.
Mounce, S., Brewster, C., Ashley, R. and Hurley, L.
(2010) ‘Knowledge Management for More
Sustainable Water Systems’ in J. Teller, A-F. Cutting-
Decelle and R. Billen (eds.) COST
Action C21 - Future of Urban Ontologies Universite de
Liege
Rettinger, A., Lösch, U., Tresp, V., d’Amato, C., &
Fanizzi, N. (2012). ‘Mining the Semantic
Web’. Data Mining and Knowledge Discovery, pp. 1-50.
Rodrıguez-Iturbe I, Rinaldo A (1996) Fractal River
Basins: Chance and Self-Organization (Cambridge
University press)
Schauser, I., Otto, S., Schneiderbauer, S., Harvey, A.,
Hodgson, N., Robrecht, H., ... & McCallum, S. (2010).
Urban Regions: Vulnerabilities, Vulnerability
Assessments by Indicators and Adaptation Options for
Climate Change Impacts. European Topic Centre on
Air ad Climate Change (ETC/ACC): Bilthoven.
Simon, H.A. (1960) The new science of management
decision Englewood Cliffs, NJ; Prentice Hall
Teller, J., Tweed, C. & Rabino, G. (2008) Conceptual
Models for Urban Practitioners Società Editrice
Esculapio, Bologna
Yu H, Gerstein M (2006) Genomic analysis of the
hierarchical structure of regulatory networks. Proc
Natl Acad Sci USA 103, pp. 14724–14731.
Valverde S, Sol ́ RV (2007) Self-organization versus
hierarchy in open-source social networks. Phys Rev E
StatbNonlin Soft Matter Phys 76, pp. 046118
Wallas, G. (1926) The Art of Thought New York, Harcourt,
Brace and Company
West G., Brown J, Enquist B (1997) A general model for
the origin of allometric scaling laws in biology.
Science 276, pp. 122–126.
Wickens J., Ulanowicz R (1988) On quantifying
hierarchical connections in ecology. J. Social Biol.
Struct. 11, pp. 369–378.
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
568
