Domain Ontologies

This paper presents an ontology architecture concept for the European Space Agency‘s (ESA) Space Situational Awareness (SSA) Program. It incorporates the author‘s domain ontology, The Space Situational Awareness Ontology and related ontology work. I summarize computational ontology, discuss the segments of ESA SSA, and introduce an option for a modular ontology framework reflecting the divisions of the SSA program. Among other things, ontologies are used for data sharing and integration. By applying ontology to ESA data, the ESA may better achieve its integration and innovation goals, while simultaneously improving the state of peaceful SSA.

In conceptual models of Enterprise Architecture, a key component is the model of Business Architecture. The term is frequently used and the concept is well accepted, however in practice definitions of Business Architecture are surprisingly poorly articulated.

CAPSICUM proposes a comprehensive, semantic meta-model for a Business Architecture, inserted into a framework for an executable Enterprise Architecture, explicitly aligned with a model of business strategy and models for the technical and platform designs of an Information System.

This paper develops the ontology of space objects for theoretical and computational ontology applied to the space (astronautical/astronomical) domain. It follows “An ontological architecture for Orbital Debris Data” (Rovetto, 2015) and “Preliminaries of a Space Situational Awareness Ontology” (Rovetto, Kelso, 2016). Important considerations for developing a space object ontology, or more broadly, a space domain ontology are presented. The main category term ‘Space Object’ is analyzed from a philosophical perspective, and the ontological commitments of legal definitions for artificial space objects are also discussed. Space object taxonomies are offered and space object terms are defined. Part of the taxonomy of my Space Object Ontology (SOO), a computational ontology under-development using Protege ontology editor, is introduced. Given the narrow scope of an SOO, it serves as a part or module of a broader Space Situational Awareness Ontology, or alternatively an Orbital Space Environment Ontology (Rovetto, 2016).

Automatic classification has become an important research area due to the rapid increase of digital information. Evidently, manual classification of documents is a tough work due to occurrences of vocabulary ambiguities of classification schemes as well as the language used in the text in hand.

In our study, we made an attempt to resolve this matter. This research has developed a computer program that can automatically classify a given text document based on a well developed ontology. Therefore, the user gets correct options of classification just after feeding the document to the new system. The new ontology is a domain ontology which is based on the Dewey Decimal Classification scheme and the Sears List. Data was obtained for classification accuracy for both manual and automatic methods. Moreover, the relationship between the vagueness of language in documents and the inaccuracy of classification were determined against manual classification and manual classification with automatic aid.

The research revealed that the results were more accurate when the newly developed automatic system was used. In addition, it also revealed that the vagueness of documents affects more in manual classification than in manual classification with the automatic aid.

The orbital debris problem presents an opportunity for international cooperation toward the mutually beneficial goals of orbital debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and related domains, taking steps in the creation of an orbital debris ontology. The purpose of the ontology is to capture general scientific domain knowledge; formally represent the entities within the domain; form, structure, and standardize (where needed) orbital and SSA terminology; and foster semantic interoperability and data-exchange. In doing so I hope to offer a scientifically accurate ontological representation of the orbital domain; contribute to research in astroinformatics, space ontology, and space data management; and improve spaceflight safety by providing a means to capture and communicate information associated with space debris.

During project planning, knowledge about software processes is useful in several situations: software processes are defined, activities are scheduled, and people are allocated to these activities. In this context, standard software processes are used as basis for defining project processes, and tools are used to support scheduling, people allocation, and so on. Ideally, people and tools should share a common conceptualization regarding this domain for allowing interoperability, and correct use of the tools. A domain ontology can be used to define an explicit representation of this shared conceptualization. Moreover, for a domain ontology to adequately serve as a reference model, it should be built explicitly taking foundational concepts into account. This paper discusses the reengineering of part of a Software Process Ontology based on the Unified Foundational Ontology (UFO). The part reengineered concerns standard processes, project processes, and activities, which are analyzed at the light of UFO concepts.

Ontologies are becoming an important mechanism to build information systems. Nevertheless, there is still no systematic approach to support the design of such systems using tools that are common to information systems developers. In this paper, we propose an approach for deriving object frameworks from domain ontologies and then we show the application of this approach in the software process domain.

Τα τελευταία χρόνια γίνονται πολλές έρευνες οι οποίες δείχνουν πως οι Οντολογίες και οι τεχνολογίες βασισμένες σε οντολογίες, βρίσκουν ευρεία εφαρμογή στην εκπαίδευση και αποτελούν έναν από τους πιο σημαντικούς τομείς έρευνας της εκπαιδευτικής τεχνολογίας.
Οι φιλόσοφοι μελετούν τις οντολογίες για αιώνες στην αναζήτησή τους για μια συστηματική εξήγηση της ύπαρξης: «​ Τι είδους πράγματα υπάρχουν;​ »
Πρόσφατα, οι οντολογίες εμφανίστηκαν ως ένα σημαντικό ερευνητικό θέμα στους τομείς της τεχνητής νοημοσύνης και της διαχείρισης της γνώσης όπου ασχολούνται με το περιεχόμενο: «​ Τι είδους πράγματα πρέπει να εκπροσωπούμε;​ »
Η απάντηση σε αυτό το ερώτημα διαφέρει από το πεδίο της οντολογίας. Οι οντολογίες που είναι ανεξάρτητες από το θέμα ονομάζονται οντολογίες ανώτερου επιπέδου και προσπαθούν να ορίσουν έννοιες που μοιράζονται όλοι οι τομείς, όπως ο
χρόνος και ο χώρος.
Οι ​ οντολογίες τομέα​ , από την άλλη πλευρά, επιχειρούν να καθορίσουν τα πράγματα που σχετίζονται με έναν συγκεκριμένο τομέα εφαρμογών. Και οι δύο τύποι οντολογιών γίνονται ολοένα και πιο σημαντικοί στην εποχή του Διαδικτύου όπου οι συνεπείς και αναγνώσιμοι από τον υπολογιστή σημασιολογικοί ορισμοί των
οικονομικών φαινομένων γίνονται η γλώσσα του ηλεκτρονικού εμπορίου. Σε αυτό το άρθρο, προτείνουμε το εννοιολογικό λογιστικό πλαίσιο του μοντέλου Resource-Event-Agent (REA) του McCarthy (1982) ως οντολογία τομέα επιχείρησης και βασίζουμε το αρχικό έργο οντολογίας των ​ Geerts και McCarthy (2000) που διερεύνησε το REA σε σχέση με τις οντολογικές κατηγοριοποιήσεις του ​ John Sowa
(1999)​ . Λόγω της εννοιολογικής κληρονομιάς της μοντελοποίησης, η REA μοιάζει ήδη με μια καθιερωμένη οντολογία από πολλές δηλωτικές (κατηγορίες) και διαδικαστικές (αξιώματα) απόψεις, και προτείνουμε επίσης εδώ να επεκτείνουμε επίσημα αυτό το πλαίσιο τόσο (1) κάθετα σε όρους επιχειρηματικής λογικής.
Δίνεται μεγάλη έμφαση σε ολόκληρη την εργασία στα μικροοικονομικά θεμέλια των ορισμών κατηγορίας.

The currently available frameworks for describing and classifying video games rely mainly on game studies hierarchies of concepts focusing on specific research interests. These methods are not taking into account the multiplicity of internal and external video games components and their relationships, and can not be used to establish similarity or resemblance between games. The existing search and recommendation tools use either imprecise genre-based categories or gamers' purchase and preference behaviors statistics. This article describes the creation of a domain ontology and search and recommendation web-based prototype. We demonstrate that this application affords new ways for documenting and exploring video game knowledge and provides more accurate results than the existing tools.

In recent years, there has been a growing interest in the development and use of domain ontologies, strongly motivated by the Semantic Web initiative. However, as we demonstrate in this paper, an approach for ontology representation uniquely based on the modeling languages adopted in the Semantic Web is insufficient to address a number of semantic interoperability problems that arise in concrete application scenarios. The main objective of this paper is to advocate in favor of an approach for conceptual modeling, in general, and domain ontology representation, in particular, in which lightweight modeling languages such as OWL and standard UML are complemented by modeling languages and methodologies based on theoretically principled Foundational Ontologies.

In this chapter, we present a framework for the evaluation and (re)design of modeling languages. In our approach, this property can be systemati- cally evaluated by comparing a concrete representation of the worldview underly- ing the language (captured in the language ́s meta-model), with an explicit and formal representation of a conceptualization of that domain (a reference ontology). Moreover, we elaborate on formal characterizations for the notions of reference ontology, conceptualization and meta-model, as well as on the relations between them. By doing this, we can also formally define the relation between the state of affairs in reality deemed possible by an ontology and the grammatical models ad- mitted by a modeling language. The precise characterization of this relation allows for a systematic improvement of a modeling language by incorporating ontologi- cal axioms as grammatical constraints in the language’s meta-model. Furthermore, we demonstrate how an approach based on visual simulation could be used to as- sess this relation, i.e., to evaluate the distance between the valid models of a lan- guage and the intended models according to the underlying conceptualization. Fi- nally, we demonstrate how the use of a system of formal ontological properties can be systematically exploited in the design of pragmatically efficient Domain- Specific Visual Languages.

With an ever-increasing data over the internet, efficient information retrieval of data for its users has always been on stake. The issue is deeper when it comes to e-governance based real estate scenario, where there is a lack of interoperability found in buying and selling of property formats and loads of miscellaneous legal terminology that fetches inappropriate legal documentation for the users. Hence in today's S emantic web scenario, a Real estate ontology has been proposed under the Real Estate Information Retrieval Model and the model is evaluated by applying various information retrieval measures. This paper shows the implementation and analysis of various popular information retrieval metrics, be it a set retrieval or rank retrieval that can be used for performance evaluation of web retrieval of data. The proposed system depicts better results in almost all the metrics as compared to the initial user query set.

This case study aims to preserve and disseminate cultural heritage information about the North American community folk dance tradition of contra dance through development of a thesaurus of choreographic terms and a domain ontology. A survey of dance resources was conducted, reviewing historic and modern examples of contra dance choreography notation and instructions, records of dance events, and recordings of dance performances. Domain and content analysis were performed on the resources to collect and organize concepts and themes regarding choreographic components and their relationships, the structure and function of cultural works, their creative expressions, and the evidence of those expressions in documents and recordings. Vocabulary used in the description of contra dance choreography was identified, classified, and notated to build a thesaurus, which was used as the basis of a domain ontology. Ontology building methodology and existing conceptual models for cultural heritage domains guided the ontology development and revision phases. The study also seeks to safeguard an intangible cultural heritage by applying knowledge organization and semantic approaches to folk dance in order to model such challenges as multiple, simultaneous modes of communication and forms of representation, modular conceptual components, descriptive sequences, differing levels of structured information, and complex cultural networks found at various levels of domain discourse.

Recommender systems usually operate on similarities between recommended items or users. Tag based recommender systems utilize similarities on tags. The tags are however mostly free user entered phrases. Therefore, similarities computed without their semantic groundings might lead to less relevant recommendations. In this paper, we study a semantic grounding used for tag similarity calculus. We show a comprehensive analysis of semantic grounding given by 20 ontologies from different domains. The study besides other things reveals that currently available OWL ontologies are very narrow and the percentage of the similarity expansions is rather small. WordNet scores slightly better as it is broader but not much as it does not support several semantic relationships. Furthermore, the study reveals that even with such number of expansions, the recommendations change considerably.

Recommender systems usually operate on similarities between recommended items or users. Tag based recommender systems utilize similarities on tags. The tags are however mostly free user entered phrases. Therefore, similarities computed without their semantic groundings might lead to less relevant recommendations. In this paper, we study a semantic grounding used for tag similarity calculus. We show a comprehensive analysis of semantic grounding given by 20 ontologies from different domains. The study besides other things reveals that currently available OWL ontologies are very narrow and the percentage of the similarity expansions is rather small. WordNet scores slightly better as it is broader but not much as it does not support several semantic relationships. Furthermore, the study reveals that even with such number of expansions, the recommendations change considerably.

The advances in manufacturing systems and automation in recent years has been vast. The
mechatronic age is apparent in any highly automated manufacturing facility. There is
however, an emerging need to improve the domain model to keep pace. Much has been
written regarding “big data” and the interoperability of systems, the detrimental effects of
dirty data.
This research sets out to review the current state of manufacturing domain data, the options
for manipulating data while an organisation grows through natural growth and acquisitions.
The research adopted a design science methodology to guide through an iterative process,
adding more data and creating a higher level of understanding through each cycle. This
research follows using a 4D foundation ontology to model the products and processes of a
test case manufacturing organisation creating a minimum viable ontology.
The accomplishments of this thesis are designing, building a foundation grounded
ontological domain model for contact lenses and contact lens manufacturing process. In the
final cycles of the evaluation, to empirically demonstrate the use of a philosophical
foundational ontology within a legacy data conversion process enhancing the
interoperability of systems by identifying and cleaning erroneous data. This research
demonstrates the use of data representation, modelling using space time maps to explain
both simple and complex domain data interactions within products and manufacturing
processes.

1 Postgraduate student, Federal University of Espírito Santo, Ontology and Conceptual Modeling Research Group (NEMO) Av. Fernando Ferrari, 514, CT-VII, 29075-910, Vitória, Brazil E-mail: [email protected] 2 Professor, Federal University of Espírito Santo, Ontology and Conceptual Modeling Research Group (NEMO) Av. Fernando Ferrari, 514, CT-VII, 29075-910, Vitória, Brazil E-mail: [email protected], [email protected]

Conceptual models are often built with techniques which propose a strict stratification of entities into two classification levels: a level of types (or classes) and a level of instances. Despite that, there are several situations in which domains of inquiry transcend the conventional two-level stratification and domain experts use types of types (or categories of categories) to articulate their conceptualizations. In these settings, types are instances of other types and multiple levels of classification can be identified (individuals, classes, metaclasses, metametaclasses, and so on), characterizing what is now called " multi-level modeling ". Over the last years, we have worked out a foundational theory for multi-level modeling (dubbed MLT), whose aim is to clarify the basic elements of multi-level conceptual modeling. This paper describes the development of this theory, and reports on some of its applications, namely: the detection of (thousands of) occurrences of anti-patterns in the Wikidata knowledge base and the revision of the powertype pattern in UML.

There has been an explosion in the types, availability and volume of data accessible in an information system, thanks to the World Wide Web (the Web) and related inter-networking technologies. In this environment, there is a critical need to replace or complement earlier database integration approaches and current browsing and keyword-based techniques with concept-based approaches. Ontologies are increasingly becoming accepted as an important part of any concept or semantics based solution, and there is increasing realization that any viable solution will need to support multiple ontologies that may be independently developed and managed. In particular, we consider the use of concepts from pre-existing real world domain ontologies for describing the content of the underlying data repositories. The most challenging issue in this approach is that of vocabulary sharing, which involves dealing with the use of different terms or concepts to describe similar information. In this paper, we describe the architecture, design and implementation of the OBSERVER system. Brokering across the domain ontologies is enabled by representing and utilizing interontology relationships such as (but not limited to) synonyms, hyponyms and hypernyms across terms in different ontologies. User queries are rewritten by using these relationships to obtain translations across ontologies. Well established metrics like precision and recall based on the extensions underlying the concepts are used to estimate the loss of information, if any.

In product-diverse, end-of-life (EoL) production lines the relevant markets, competitors and customer bases continuously change as new products are processed. The resale market itself changes with the influx of new products, as well as hardware and software discontinuations. Competitive business decision making is often performed by a human operator and may not be timely or fully informed. These are decisions such as whether to perform a high cost repair or recycle a product or whether to use a batch of parts in repair or sell them on can be used to optimise product life-cycle management (PLM) and profit margins. A real-time decision making capability can reduce the risk of performing non-profitable processing. The novel contribution of this work is an interoperable semantic decision support toolset that is necessary to enable a capability for timely EoL decisions based on complete knowledge on profitability, predicted pricing and cost-of-production. Many decision support systems have been proposed for the EoL domain, but a lack of interoperability and use of unstructured knowledge bases has led to decisions based on knowledge that is not up to date. Using formalised, semantic technologies offers sustainable decision making in this volatile and increasingly competitive domain.

This doctoral seminar is an introduction to Digital Humanities defined as the application of methods and tools from Information and Communication Technologies to areas of Arts, Humanities and Social Sciences. Rather than a simple application of computer tools, Digital Humanities offer a multidisciplinary perspective that has recently led to rethinking certain practices, e.g., in the acquisition and representation of knowledge in the field, and opened up new perspectives for the disciplines concerned. In the framework of this training, the focus will be on the digital representation of cultural objects in the form of Linked and Open Data accessible by means of standards of the Semantic Web. To validate the acquired knowledge, the seminar includes a full day of hands-on practice on how to query and to structure data in cultural heritage collections.

[Critique of religion in the classroom. School subject, critique, and ontology in the Norwegian school system]

Artikkelen utforskar spørsmålet om religionskritikk i norsk skule med saerleg blikk på religions-og livssynsundervisninga i grunnskule (KRLE) og på vidaregåande trinn (RE). Eg tar utgangspunkt i to bidrag av nyare dato til tematikken, frå filosofen Gunnar Skirbekk og religionsvitaren Bengt-Ove Andreassen. Ut frå ei drøfting av religionskritikkens form og funksjon i klasserommet ønskjer eg å retta merksemd mot det didaktisk sett viktige spørsmålet om skulefagets praktiske ontologi. Med dette meiner eg spørsmålet om kva som grunnleggjande sett får sleppa til som relevante perspektiv og gyldige rammer for skulen sitt KRLE/RE-fag. Det er her viktig at skulefaget ivaretar eit ope arbeids-og samtalerom, som i sin tur inneber eit fagleg perspektiv-og metodemangfald i det didaktiske arbeidet, også i måten ein arbeider med religionskritikk på.

Nøkkelord: religionskritikk, fagontologi, religionsdidaktikk, perspektivmangfald, KRLE/RE

My text explores the topic of the critique of religion in the Norwegian school system, paying particular attention to the school subject of religion, philosophy and ethics (in Norway: KRLE and RE). I take my departure from two different positions in the field – one a historian of religion, the other a philosopher – in order to focus on the didactically important question of domain ontology. By this I mean the question of what, in terms of basic parameters drawn up for the school subject, is permitted as relevant perspectives and frames of reference for the exploration of religion and world-views in the classroom. My own argument supports sustaining a range of perspectives in our educational praxis, in order to accomodate a complex understanding as well as opening towards a more facetted critique of the phenomena in question.

Keywords: the critique of religion, domain ontology, didactics of religion, plurality of perspectives, RE

A promising approach to Smart Energy Grids is to empower communities of consumers with a novel role in the management of their electricity by sharing excess electricity and therefore becoming energy producers (prosumers). We achieve it using a framework to connect dynamic, context-aware, heterogeneous virtual and real entities on the Internet of Smart Meters (IoSM). We transform the smart electricity meters into fully-fledged intelligent computers on the IoSM and enable them to securely collect data from heterogeneous meters and sensors, detect smart meters with similar goals, exchange and aggregate data from multiple autonomous physical or virtual meters, and manage the actual energy demand and ensure the achievement of demand response for the community involved. Domain ontologies are used to store the semantics of the collected data from IoSM. A problem we have encountered is how our framework can use ontologies for community-grounded decision rules, which need to be consistent based on aggregation of collected data and contexts. We use Semantic Decision Table (SDT), which is a decision table enhanced with ontology technologies, to tackle the problem. This paper records our efforts in 1) the general design of the framework; 2) decision support models, namely SDTs, for fulfilling this requirement; 3) an algorithm of creating invocational SDTs; 4) the implementation of visualizing invocational SDTs.

Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user's perspective, the language's modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community.

1 Postgraduate student, Federal University of Espírito Santo, Ontology and Conceptual Modeling Research Group (NEMO) Av. Fernando Ferrari, 514, CT-VII, 29075-910, Vitória, Brazil E-mail: [email protected] 2 Professor, Federal University of Espírito Santo, Ontology and Conceptual Modeling Research Group (NEMO) Av. Fernando Ferrari, 514, CT-VII, 29075-910, Vitória, Brazil E-mail: [email protected], [email protected]

There has been a growing interest in Domain-Specific Visual Model- ing Languages (DSVL) and their support for domain understanding and com- munication. However, the quality of these languages fundamentally depends on how well their structure reflects the structure of the abstractions constituting the underlying domain conceptualization. Since a well-founded domain ontology aims at faithfully representing a domain, it can be seen the ideal input for engi- neering a DSVL. In this paper, we present an experiment that analyses the per- formance of computer students in interpreting instance models by varying the concrete syntax of the language used. We contrast a generic notation (UML- based notation for object diagrams) and a domain specific notation that was de- signed based on a well-founded ontology for the domain of organizational structures. The hypothesis is that the performance of participants in interpreting the models using the domain specific notation is better than those who ...

This paper demonstrates the development of ontology for satellite databases. First, I create a computational ontology for the Union of Concerned Scientists (UCS) Satellite Database (UCSSD for short), called the UCS Satellite Ontology (or UCSSO). Second, in developing UCSSO I show that The Space Situational Awareness Ontology (SSAO)-—an existing space domain reference ontology—-and related ontology work by the author (Rovetto 2015, 2016) can be used either (i) with a database-specific local ontology such as UCSSO, or (ii) in its stead. In case (i), local ontologies such as UCSSO can reuse SSAO terms, perform term mappings, or extend it. In case (ii), the author_s orbital space ontology work, such as the SSAO, is usable by the UCSSD and organizations with other space object catalogs, as a reference ontology suite providing a common semantically-rich domain model. The SSAO, UCSSO, and the broader Orbital Space Environment Domain Ontology project is online at https://purl.org/space-ontology and GitHub. This ontology effort aims, in part, to provide accurate formal representations of the domain for various applications. Ontology engineering has the potential to facilitate the sharing and integration of satellite data from federated databases and sensors for safer spaceflight.

Ontologies are becoming an important mechanism to build information systems. Nevertheless, there is still no systematic approach to support the design of such systems using tools that are common to information systems developers. In this paper, we propose an approach for deriving object frameworks from domain ontologies and then we show the application of this approach in the software process domain.

—An ontology is a formal and explicit specification of a shared conceptualization. Manual construction of domain ontology does not adequately satisfy requirements of new applications, because they need a more dynamic ontology and the possibility to manage a considerable quantity of concepts that humans cannot achieve alone. Researchers have discussed ontology learning as a solution to overcome issues related to the manual construction of ontology. Ontology learning is either an automatic or semi-automatic process to apply methods for building ontology from scratch, or enriching or adapting an existing ontology. This research focuses on improving the process of term extraction for identifying concepts in ontology learning. Available approaches for term extraction process are limited in various ways. These limitations include: (1) obtaining domain-specific terms from a domain expert as seed words without automatically discovering them from the corpus, and (2) unsuitable usage of corpora in discovering domain-specific terms for multiple domains. Our study uses linguistic analysis and statistical calculations to extract domain-specific simple and complex terms to overcome this first limitation. To eliminate the second limitation, we use multiple contrastive corpora that reduce the biasness in using a single contrastive corpus. Evaluations show that our system is better at extracting terms when compared with the previous research that used the same corpora.

Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user's perspective, the language's modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community.

Abstract

Objective – This research was designed as a pilot study to test a methodology for subject based collection analysis for public libraries.
Methods – WorldCat collection data from eight Australian public libraries was extracted using the Collection Evaluation application. The data was aggregated and filtered to assess how the sample’s titles could be compared against the OCLC Conspectus subject categories. A hierarchy of emphasis emerged and this was divided into tiers ranging from <0.1% of the sample to >1% of the sample. These tiers were further analysed to quantify their representativeness against both
the sample’s titles and the subject categories taken as a whole. The interpretive aspect of the study sought to understand the types of knowledge embedded in the tiers and was underpinned by hermeneutic phenomenology.
Results – The study revealed that there was a marked tendency for a small percentage of subject categories to constitute a large proportion of the potential topicality that might have been
represented in these types of collections. The study also found that distribution of the aggregated collection conformed to a Power Law distribution (80/20) so that approximately 80% of the collection was represented by 20% of the subject categories. The study also found that there were
significant commonalities in the types of subject categories that were found in the designated tiers and that it may be possible to develop ontologies that correspond to the collection tiers.
Conclusions – The evidence-based methodology developed in this pilot study has the potential for further development to help to improve the practice of collection development. The introduction of the concept of the epistemic role played by collection tiers is a promising aid to inform our understanding of knowledge organization for public libraries. The research shows a way forward to help to link subjective decision making with a scientifically based approach to managing knowledge resources.