Faceted Classification Scheme Research Articles

Novel comprehensive unified classification system toward smart standardized built environment knowledge and low-risk international collaborations: UniCCC

The Construction Industry (CI) data is acknowledged to still be unstructured and high-dimensional. Efforts were undertaken to tackle this problem using regional Unified Classification Systems (UCSs). The study emphasizes the necessity for a comprehensive international UCS to manage the growing trend of international collaborations within the CI and associated data risks. Existing UCSs exhibit significant inconsistencies, such as regional omissions, terminological disparities, and diverse data structuring, underscoring the need for a unified approach. Accordingly, using a 3-stage mixed method, the novel UCS ‘Unified Classification of Construction Components_ UniCCC’ was developed, comprising 4 phyla, 9 divisions, and 54 classes, and was shown to have good adaptability/scalability, structure/breakdown, clarity, codifiability, and inclusivity of the 11 key CI aspects. By addressing inconsistencies and smartly structuring CI knowledge from North America, Europe, Africa, and the Middle East, using a faceted classification scheme aligned with ISO 12,006, and being developed using a conventional modeling language, UniCCC represents a significant advancement in UCSs, with promising implications for global CI practices and research, paving the way for new avenues in CI performance, innovation, and sustainability. It demonstrated efficiency in various CI aspects, including risk reduction, automation, and sustainability enhancement. As evidence of its performance, using UniCCC for scheduling might decrease up to 58.17%, 66.85%, and 31.74% of the related time, request for information, and omissions, respectively. The study suggests future research perspectives to explore UniCCC's applicability in different regions, its integration with emerging technologies, its proficiency metrics for different purposes, and strategies for organizational implementation.

Automated Subject Identification using the Universal Decimal Classification: The ANN Approach

Universal Decimal Classification (UDC) is a popular controlled vocabulary that is used to represent subjects of documents. Text categorization determines a text's category, as evident from the notation-text label format of the Universal Decimal Classification. With the help of machine learning techniques and the Universal Decimal Classification (UDC), the present work aims to develop an end-user (library professional) based recommender system for automatically classifying documents using the UDC scheme. The proposed work is conceived for determining and constructing a complex class number using the syntax of Universal Decimal Classification (UDC). A corpus of documents classified with the UDC scheme is used as a training dataset. The classification of the documents is done with human mediation having proficiency in classificatory approaches. The BERT model and the KNIME software are used for the study. This study uses the classified dataset to fine-tune the pre-trained BERT model to construct the semi-automatic classification model. The results show that the model is constructed with high accuracy and Area Under Curve (AUC) value, although the prediction represented a low accuracy rate. This study reflected that if the model is explicitly trained by annotating each concept and if the full licensed version of UDC class numbers becomes available, there is a greater potency of developing an automated, freely faceted classification scheme for practical use.

Migrating a complex classification scheme to the semantic web: expressing the Integrative Levels Classification using SKOS RDF

PurposeThe Integrative Levels Classification (ILC) is a comprehensive “freely faceted” knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation.Design/methodology/approachThe design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool.FindingsThe ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed.Originality/valueComplex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship – specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.

Astronomy Classification: Towards a Faceted Classification Scheme

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WhatsApp voice messaging as an emergent digital practice : a multi-method analysis

In this contribution, I describe the development process of my Masters thesis in which I investigated WhatsApp Voice Messaging through a multi-method approach, using Conversation Analysis in combination with ethnographic methods. This exploratory study allowed me to classify WhatsApp Voice Messaging within Susan Herring’s Faceted Classification Scheme for Computer-Mediated Discourse (2007). In the first part, I introduce Voice Messaging and provide some background for the reader to understand the elements founding the multi-method I used. Next, I describe my methodology step-by-step in a comprehensive way. Then I take the reader through a detailed analysis of three selected findings, assembling complementary results. Finally, I list the limitations of my methodology and provide some orientation for future research.

An Effort Estimation Taxonomy for Agile Software Development

In Agile Software Development (ASD) effort estimation plays an important role during release and iteration planning. The state of the art and practice on effort estimation in ASD have been recently identified. However, this knowledge has not yet been organized. The aim of this study is twofold: (1) To organize the knowledge on effort estimation in ASD and (2) to use this organized knowledge to support practice and the future research on effort estimation in ASD. We applied a taxonomy design method to organize the identified knowledge as a taxonomy of effort estimation in ASD. The proposed taxonomy offers a faceted classification scheme to characterize estimation activities of agile projects. Our agile estimation taxonomy consists of four dimensions: estimation context, estimation technique, effort predictors and effort estimate. Each dimension in turn has several facets. We applied the taxonomy to characterize estimation activities of 10 agile projects identified from the literature to assess whether all important estimation-related aspects are reported. The results showed that studies do not report complete information related to estimation. The taxonomy was also used to characterize the estimation activities of four agile teams from three different software companies. The practitioners involved in the investigation found the taxonomy useful in characterizing and documenting the estimation sessions.

A Component Retrieval Tree Matching Algorithm Based on a Faceted Classification Scheme

Abstract An efficient scheme of component retrieval can significantly reduce the cost of software reuse. For this purpose, a method of successfully retrieving of specified components from the component repository is a crucial consideration. However, neither the retrieval efficiency, nor the query-matching rate of the traditional method, which is based on a faceted classification scheme, satisfies the requirements of component retrieval. In this paper a novel component retrieval method combining the features of the faceted classification scheme and the theory of tree matching is proposed. This method not only accurately retrieves components that match queries, but also considers any incomplete descriptions of the retrieval component to completely ensure the relaxation ability of the component retrieval. The experimental results show that the retrieval matching method proposed is highly efficient, and it retrieves feasibly and efficiently the components.

Massive-scale learning of image and video semantic concepts

Rapid growth in the capture and generation of images and videos is driving the need for more efficient and effective systems for analyzing, searching, and retrieving this data. Specific challenges include supporting automatic content indexing at a large scale and accurately extracting a sufficiently large number of relevant semantic concepts to enable effective search. In this paper, we describe the development of a system for massive-scale visual semantic concept extraction and learning for images and video. The system models the visual semantic space using a hierarchical faceted classification scheme across <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">objects</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scenes</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">people</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">activities</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">events</i> and utilizes a novel machine learning approach that creates ensemble classifiers from automatically extracted visual features. The ensemble learning and extraction processes are easily parallelizable for distributed processing using Hadoop® and IBM InfoSphere® Streams, which enable efficient processing of large data sets. We report on various applications and quantitative and qualitative results for different image and video data sets.

A Discourse‐Based Approach to CALL Training and Professional Development

AbstractPhase 1 of this study explores findings from a nationwide survey on computer‐assisted language learning (CALL) that was completed by 409 in‐service teachers of French, German, and Spanish. These results, in turn, informed specific themes that were explored in greater detail during focus group sessions with 22 in‐service K–12 foreign language teachers (Phase 2). The main theme that emerged from the survey and the focus groups was the perceived need (expressed by in‐service teachers) for future teachers to learn how to think about, analyze, and integrate new technologies into a foreign language curriculum without having to depend on tool‐specific training since prospective teachers will use a number of new technologies—many of which have not yet been developed—throughout their career. Consequently, Phase 3 of this study examines a new component of a foreign language pedagogy course in which 18 prospective teachers studied and applied a faceted classification scheme for analyzing and understanding computer‐mediated discourse as a tool‐independent approach to CALL training.

A Software Component Library Implemented by Using Faceted Classification Scheme and Component Management Protocol

In order to avoid the shortcoming of faceted classification scheme for being not flexible enough, in this paper, an integrated method which combining the advantages of faceted classification scheme and key value pair method is proposed to represent the logical model of software component. The faceted classification scheme provides a set of summarized optional information for software component to choose. And the key value pair method uses key and value to express the information contained in software component. The information contained in a software component can be divided into four basic facets, namely, the application field, expression method, using environment, development process. And they describe the basic information, using information, and storage information of a software component. The component management protocol based on URL is defined to represent software component, which can be used for storing, transmitting, and analyzing of software component inside of system.

BUILDING AN ADVANCE DOMAIN ONTOLOGY MODEL OF INFORMATION SCIENCE (OIS)

The paper describes the process of modelling domain knowledge of Information Science (IS) by creating an Ontology of Information Science domain (OIS). It also reports on the life cycle of the ontology building process using Methontology, based on the IEEE standard for development software life cycle process, which mainly consists of: specification, conceptualization, formalization, implementation, maintenance and evaluation. The information resource used in acquisition and evaluation has been obtained from Information Science. The conceptualization consists of identifying IS concepts and grouping them into a hierarchy tree based on a faceted classification scheme. The OIS ontology is formalized by using the ontology editor Protege to generate the ontology code. The achieved result is OIS ontology which has fourteen facets: Actors, Method, Practice, Studies, Mediator, Kinds, Domains, Resources, Legislation, Philosophy & Theories, Societal, Tool, Time and Space. The model is evaluated using ontology quality criteria to check the ontology’s usefulness, and how it could be transferred into application ontology for Information Science education.

Ranganathan's layers of classification theory and the FASDA model of classification

Describes four waves of Ranganathan’s dynamic theory of classification. Outlines components that distinguish each wave, and porposes ways in which this understanding can inform systems design in the contemporary environment, particularly with regard to interoperability and scheme versioning. Ends with an appeal to better understanding the relationship between structure and semantics in faceted classification schemes and similar indexing languages.

Classifying art with Bliss

The second edition of the Bliss Classification (BC2) is a faceted classification scheme which reworks the original Bliss Classification, devised a century ago. It compares favourably in terms of its wealth of detail, the fineness of its analysis, its flexibility and the conciseness of its notation with its main rivals, the Library of Congress Classification, the Dewey Decimal Classification and the Universal Decimal Classification. The Art class, W, is one of the most detailed and best organised of the BC2 schedules, with the caveat that the author did not find the giving of priority to place over period and the listing of individual artists separately from their periods and places to be the most helpful arrangement. However, room is left for alternative arrangements within the scheme.

Using linked data to classify web documents

PurposeThe purpose of this paper is to find a relationship between traditional faceted classification schemes and semantic web document annotators, particularly in the linked data environment.Design/methodology/approachA consideration of the conceptual ideas behind faceted classification and linked data architecture is made. Analysis of selected web documents is performed using Calais' Semantic Proxy to support the considerations.FindingsTechnical language aside, the principles of both approaches are very similar. Modern classification techniques have the potential to automatically generate metadata to drive more precise information recall by including a semantic layer.Originality/valueLinked data have not been explicitly considered in this context before in the published literature.

The generation of faceted classification schemes for use in the organisation of engineering design documents

Vast quantities of electronic information are generated and stored such that engineers may later retrieve, assimilate and ultimately utilise such information during their daily activities. Where term-based querying relies upon suitable query formulation, browsing of pre-organised information allows the information to be displayed against a descriptive structure. Traditional classification schemes generally cater for certain viewpoints, however faceted schemes concurrently describe multiple perspectives. The literature specifying the creation of such schemata is sparse, and distributed across different domains and eras. This paper reviews this literature and proposes a means by which the underlying theory may be more readily applied within engineering design.

Building a faceted classification for the humanities: principles and procedures

PurposeThis paper aims to provide an overview of principles and procedures involved in creating a faceted classification scheme for use in resource discovery in an online environment.Design/methodology/approachFacet analysis provides an established rigorous methodology for the conceptual organization of a subject field, and the structuring of an associated classification or controlled vocabulary. This paper explains how that methodology was applied to the humanities in the FATKS project, where the objective was to explore the potential of facet analytical theory for creating a controlled vocabulary for the humanities, and to establish the requirements of a faceted classification appropriate to an online environment. A detailed faceted vocabulary was developed for two areas of the humanities within a broader facet framework for the whole of knowledge. Research issues included how to create a data model which made the faceted structure explicit and machine‐readable and provided for its further development and use.FindingsIn order to support easy facet combination in indexing, and facet searching and browsing on the interface, faceted classification requires a formalized data structure and an appropriate tool for its management. The conceptual framework of a faceted system proper can be applied satisfactorily to humanities, and fully integrated within a vocabulary management system.Research limitations/implicationsThe procedures described in this paper are concerned only with the structuring of the classification, and do not extend to indexing, retrieval and application issues.Practical implicationsMany stakeholders in the domain of resource discovery consider developing their own classification system and supporting tools. The methods described in this paper may clarify the process of building a faceted classification and may provide some useful ideas with respect to the vocabulary maintenance tool.Originality/valueAs far as the authors are aware there is no comparable research in this area.

Information Architecture: Getting richer

The ASIS&T Information Architecture Summit is a pivotal event in the yearly cycle for many IA-related professionals. Sessions and hallway conversations help the community learn from recent work and also generate points of focus for future exploration. The mixture of case study, research, practical tools and ethical discussion in this issue of the Bulletin reflects the range of session and hallway topics at the April Summit. The success of the research track this year is particularly encouraging. IA practice needs stress-testing and rigor, and these attributes are brought to bear when research is carried out and widely shared. As D. Grant Campbell discusses in “Information Architecture Research: The Future State of the Art,” academics have the job of creating and testing IA tools, teaching a curriculum truly relevant to the next generations and helping define how information architecture relates to and interacts with other areas of expertise. Campbell also encourages academics and practitioners to take advantage of next year's Summit research track or apply for a grant to support their work through the IA Institute. In “FaceTag: Integrating Bottom-up and Top-down Classification in a Social Tagging System,” Emanuele Quintarelli, Andrea Resmini and Luca Rosati begin with a succinct overview of semantic structures in tagging systems. This introduction alone is a must-read for anyone interested in collaborative tagging issues and tools. The authors go on to describe FaceTag, a prototype that demonstrates how user-generated tags can be integrated with a faceted classification scheme to deliver an excellent browseable, interactive social bookmarking experience. This work should be of great interest to anyone wrestling with structured and user-generated categorizations. In “Evolutionary Psychology as a Basis for Ethical Design: Virtual Status and Ubiquitous Altruism,” Olly Wright discusses evolutionary psychology in the realm of social networking. He proposes that IAs apply an understanding of evolutionary psychology to the achievement of more ethical information structures and user experience. In particular, the author looks at virtual status and enabling and rewarding altruism through online media. I particularly appreciate the closing summation: “[A]s information architects, designers of these new social tools and mediated interactions, we are in a position to influence [design for an ethical and healthy culture], should we choose to.” This work offers particularly useful insights within the context of the developing world, and I hope to see these concepts elaborated further in a future issue of the Bulletin. In “Data Driven Design: Using Web Analytics to Validate Heuristics,” Andrea Wiggins offers practical, research-based, straightforward ways for the information architect to work with web analytics to improve the user experience. Further, this article enriches the practice of IA by describing a teamwork approach for web analytics staff and IAs and by suggesting that measures of user experience be identified as key performance indicators early in the process. The author also discusses heading off the managerial temptation to replace user testing with web analytics alone. Rich Internet applications (RIA) are what people are talking about when they say “Web 2.0.” User experience professionals naturally want to work on RIA projects, and those who haven't had the chance yet may feel daunted or concerned about being left behind. Adam Polansky's lively case study, “IA and RIAs — You Know More Than You Think You Do,” describes his first RIA engagement. He offers practical insights and helpful advice and, in the process, assures us that a well-rounded IA already has the foundations for success on an RIA project team. Josh Knauer's “Information Commons: Service to the Community Starts with Solid IA” packs three high value messages into one tight narrative. In this case study Knauer describes the development of a distributed database system that enables social services professionals to access and update information across a decentralized collection of data repositories. The article also showcases how an open system architecture and the use of universally unique identifiers (UUIDs) can help users build new tools in a collaborative manner. Finally, Knauer demonstrates that a solid IA methodology underpins a responsive and innovative solution to a widespread problem.

Cataloging our information architecture

PurposeTo explore the potential impact of Shiyali Ramamrita Ranganathan's classification theories on the accessibility and exposure of digital repository content.Design/methodology/approachConceptual analysis of: faceted classification schemes; the symantic web; object‐oriented analysis, design and programming; and digital repository content.FindingsWith the rapid proliferation of digital repositories and digital archives comes the need for appropriate and flexible classification schemes that can be implemented in conjunction with current technology such as object‐oriented programming techniques. Shivali Ranganathan was a forerunner in the area of classification systems, and developed a classification system, which is very suited to the need at hand: faceted classification. This column explores the relationship between Ranganathan's theories and their potential use in the contemporary digital library context (specifically digital repositories).Practical implicationsRanganathan's methodology may help libraries to expose digital repository content on a larger scale within a very flexible and forward‐looking framework. This will allow libraries to anticipate the development of the semantic web and become key players in this environment.Originality/valueSuggests a theoretical framework for describing and syndicating digital repository content, which is flexible and anticipatory in nature, based on the work of Shiyali Ranganathan.

Toward reuse of object-oriented software design models

In software reuse, which is an important approach to improving the practice of software engineering, many factors may hinder reusing software artifacts. Among those factors are the availability of software artifacts at a different level of abstraction and a method to classify and retrieve them. This paper proposes an approach based on faceted classification scheme for the classification and retrieval of software design artifacts, namely Object-Oriented Design Models, thus facilitating their reuse. Six facets, Domain, Abstractions, Responsibilities, Collaborations, Design View, and Asset Type have been defined to constitute the classification and the retrieval attributes. Each of the facets describes one aspect of an Object-Oriented design model. It contains a number of predefined terms chosen through the analysis of various software systems specifications. The selected terms of each facet are arranged on a conceptual graph to aid the retrieval process. A design artifact is classified by associating with it a software descriptor through the selection of one or more terms from each facet. The role of a descriptor is to emphasize the important structural and behavioral properties of a design artifact and also to document the artifacts associated with the design model. The associated similarity-based retrieval mechanism helps users to search for candidate design artifacts that best match their target specification. The similarity analysis is based on the estimation of the conceptual distance between the terms in a query descriptor and the terms in the specified descriptors of various design models in a software repository. A case study is presented to illustrate the classification and the retrieval process.

Question types in digital reference: An evaluation of question taxonomies

AbstractThis study evaluates four taxonomies of question types to determine the expressiveness of each for questions received by digital reference services. The result is a faceted classification scheme that can be used as a basis for automating parts of the digital reference question answering process.