1,721,001 research outputs found
A physical database model
No full text214 leaves ; 30 cm. Includes bibliographical references. University of Otago department: Information Science. "December 2004".A good database design brings total attention to data. Data have been recognized as a valuable resource, resulting in an increased use of database systems. A wide variety of models and techniques are available to aid in system development at the analysis and logical stage. Once the system is defined at the logical stage, many other decisions have to be made to define the construction, operation and maintenance of the database system at the physical stage.
Database design whether physical or logical is the process of determining the organization of a database. The concept of logical and conceptual modelling has been widely researched. However, few researchers seem to have considered physical modelling explicitly. Physical modelling is the conversion of a logical model to a physical model that will be suitable for a specific system with its own hardware configuration (Batini, Ceri et al. 1990).
The objective of this thesis is to propose a physical database modelling technique that will demonstrate a join between logical and physical design to improve the performance of a database system using physical tuning techniques. It will annotate an entity model with physical detail that will provide a framework for building a physical model.
To substantiate the relevance of the physical database model, the author looks at the physical storage structures in a database system and other physical database models that have been previously developed.
This thesis will use a moderately realistic database system case study. The case study is used as an example for interpreting possible physical problem areas in a "real" database system. The aim will be to model and optimise the physical design of the discussed case study.UnpublishedAmbler, S. W. (2002). Agile Data, Agile Modelling. 2003.
Batini, Ceri, et al. (1990). Entity Modelling, Publishing Company Inc.
Batory, D. S. (1985). "Modelling the Storage Architectures of Commercial
Database Systems." ACM Transactions on Database Systems 10(4): 463-528.
Beynon-Davies, P. (1992). "Using an entity model to drive physical database
design." Information and Software Technology 34(12/1992): 805-813.
Beynon-Davies, P. (1996). Database Systems, Macmillan, USA
Campbell, D. (1992). "Entity-Relationship Modelling: One Style Suits All?"
DATABASE.23(3):12-18
Chan and Lochovsky (1980). Entity-Relationship Approach: The use of ER
concept in knowledge representation. Edited by P. P. Chen.
Chanchani, N. Understanding Clustering. Developer EIB,www.ejbsamples.com
Last accessed date 14/08/2004.
Connoly, T. and C. Begg (2002). Database Systems- A practical approach to
design, implementation and Management, Addison-Wesley.
Corey, M. J. and Abbey (1997). ORACLE data warehousing - A practical guide to
successful data warehouse analysis, build, roll-out, Osborne McGraw-Hill.
Coronel, R. Database Systems - Design, Implementation & Management,
Thomson Learning.
Date, C. J. (1995). An Introduction to Database Systems, 2nd Edition, Addison
Wesley Publishing Company.
D'Orazio, R. and G. Happel (1996). Practical Data Modelling for Database
Design- The IT Series, John Wiley & Sons.
Feldman, P. and D. Miller (1986). "Entity Model Clustering: Structuring A Data
Model By Abstraction." The Computer Journal 29(4).Pages 348-360
Cane and Sarson (1978) Structured System Analysis: Tools and Techniques.
Prentice Hall
Gillenson, M. L. (1990). " Physical Design Equivalences in Database Conversion."
Communications of the ACM 33(8).Pages 120-131
Kaminski, D. M. (1985). "Query Processing Optimisation Strategies: Possible vs.
Optimal Solutions." ACM Transactions on Database Systems Volume 85 pg 449-
456.
Knuth, D. E. (1973). The Art of Computer Programming - Sorting and
Searching, Addison Wesley.
McFadden, F. R. and J. A. Hoffer (1991). Modern Database Management, The
Benjamin/Cummings Publishing Company Inc.
Naiburg and Maksimchuk (2001) referenced from Agile Modeling. 2003.
O'Neil, P. (1994). Database- Design, Principles And Programming, Morgan
Kaufmann.
O'Neil, P. and E. O'Neil (1994). Database Principles, Programming and
Performance, Morgan Kaufmann Publishers.
Powell, J. D. and D. P. Tiliman(1979) "Automating the development of a
conceptual schema." ACM Transactions on Database Systems pg 98-105
Robinson, K. A. (1979). "An entity/event data modelling method." The Computer
Journal 22(3) pg 270-271.
Roti, S. (1996). Indexing and Access Mechanism. DBMS pg 65-68.
Severance, D. G. and A. G. Merten (1986). "Performance Evaluation of File
Organizations through Modeling." ACM Transactions on Database Systems
pg 543-545
Silberschatz(1999). "Database Systems and Concepts" Fifth Edition
Spiegler, I. and D. Widder (1993). "Physical Database Design: A Decision Support
Model." DATABASE pg 5-11.
Stanger, N. (2001). BDL Electronics.Case study for paper INFO 321 (Database
Systems), Department of Information Science, University of Otago
Teorey, T. J. and J. P. Fry (1982). Design of Database Structures, New Jersey,
Prentice Hall.
Tewari, R. (1990). "Expert Design Tools for Physical Database Design." ACM
Transactions on Database Systems pg 538-549.
Tufte, E. (1997). Visual Explanations, Images & Quantities, Evidence & Narrative,
Graphics Press.
Tufte, E. R. (1998). Envisioning Information, Graphics Press.
Wiederhold (1993). "Physical Database Design (DDMS)." ACM Transactions on
Database Systems pg 657-659.
Willits, J. (1992). Database Design & Construction - an open learning course for
students and information managers, Library Association Publishing, London
Adattár tíz nap alatt – Új-Zéland első nyílt hozzáférésű adattárának megvalósítási tapasztalatai
No full text-STANGER, Nigel-McGREGOR, Graham: Hitting the ground running: Building New Zealand's first publicly available institutional repository, 2006
A physical database model
No full text214 leaves ; 30 cm. Includes bibliographical references. University of Otago department: Information Science. "December 2004".A good database design brings total attention to data. Data have been recognized as a valuable resource, resulting in an increased use of database systems. A wide variety of models and techniques are available to aid in system development at the analysis and logical stage. Once the system is defined at the logical stage, many other decisions have to be made to define the construction, operation and maintenance of the database system at the physical stage.
Database design whether physical or logical is the process of determining the organization of a database. The concept of logical and conceptual modelling has been widely researched. However, few researchers seem to have considered physical modelling explicitly. Physical modelling is the conversion of a logical model to a physical model that will be suitable for a specific system with its own hardware configuration (Batini, Ceri et al. 1990).
The objective of this thesis is to propose a physical database modelling technique that will demonstrate a join between logical and physical design to improve the performance of a database system using physical tuning techniques. It will annotate an entity model with physical detail that will provide a framework for building a physical model.
To substantiate the relevance of the physical database model, the author looks at the physical storage structures in a database system and other physical database models that have been previously developed.
This thesis will use a moderately realistic database system case study. The case study is used as an example for interpreting possible physical problem areas in a "real" database system. The aim will be to model and optimise the physical design of the discussed case study.UnpublishedAmbler, S. W. (2002). Agile Data, Agile Modelling. 2003.
Batini, Ceri, et al. (1990). Entity Modelling, Publishing Company Inc.
Batory, D. S. (1985). "Modelling the Storage Architectures of Commercial
Database Systems." ACM Transactions on Database Systems 10(4): 463-528.
Beynon-Davies, P. (1992). "Using an entity model to drive physical database
design." Information and Software Technology 34(12/1992): 805-813.
Beynon-Davies, P. (1996). Database Systems, Macmillan, USA
Campbell, D. (1992). "Entity-Relationship Modelling: One Style Suits All?"
DATABASE.23(3):12-18
Chan and Lochovsky (1980). Entity-Relationship Approach: The use of ER
concept in knowledge representation. Edited by P. P. Chen.
Chanchani, N. Understanding Clustering. Developer EIB,www.ejbsamples.com
Last accessed date 14/08/2004.
Connoly, T. and C. Begg (2002). Database Systems- A practical approach to
design, implementation and Management, Addison-Wesley.
Corey, M. J. and Abbey (1997). ORACLE data warehousing - A practical guide to
successful data warehouse analysis, build, roll-out, Osborne McGraw-Hill.
Coronel, R. Database Systems - Design, Implementation & Management,
Thomson Learning.
Date, C. J. (1995). An Introduction to Database Systems, 2nd Edition, Addison
Wesley Publishing Company.
D'Orazio, R. and G. Happel (1996). Practical Data Modelling for Database
Design- The IT Series, John Wiley & Sons.
Feldman, P. and D. Miller (1986). "Entity Model Clustering: Structuring A Data
Model By Abstraction." The Computer Journal 29(4).Pages 348-360
Cane and Sarson (1978) Structured System Analysis: Tools and Techniques.
Prentice Hall
Gillenson, M. L. (1990). " Physical Design Equivalences in Database Conversion."
Communications of the ACM 33(8).Pages 120-131
Kaminski, D. M. (1985). "Query Processing Optimisation Strategies: Possible vs.
Optimal Solutions." ACM Transactions on Database Systems Volume 85 pg 449-
456.
Knuth, D. E. (1973). The Art of Computer Programming - Sorting and
Searching, Addison Wesley.
McFadden, F. R. and J. A. Hoffer (1991). Modern Database Management, The
Benjamin/Cummings Publishing Company Inc.
Naiburg and Maksimchuk (2001) referenced from Agile Modeling. 2003.
O'Neil, P. (1994). Database- Design, Principles And Programming, Morgan
Kaufmann.
O'Neil, P. and E. O'Neil (1994). Database Principles, Programming and
Performance, Morgan Kaufmann Publishers.
Powell, J. D. and D. P. Tiliman(1979) "Automating the development of a
conceptual schema." ACM Transactions on Database Systems pg 98-105
Robinson, K. A. (1979). "An entity/event data modelling method." The Computer
Journal 22(3) pg 270-271.
Roti, S. (1996). Indexing and Access Mechanism. DBMS pg 65-68.
Severance, D. G. and A. G. Merten (1986). "Performance Evaluation of File
Organizations through Modeling." ACM Transactions on Database Systems
pg 543-545
Silberschatz(1999). "Database Systems and Concepts" Fifth Edition
Spiegler, I. and D. Widder (1993). "Physical Database Design: A Decision Support
Model." DATABASE pg 5-11.
Stanger, N. (2001). BDL Electronics.Case study for paper INFO 321 (Database
Systems), Department of Information Science, University of Otago
Teorey, T. J. and J. P. Fry (1982). Design of Database Structures, New Jersey,
Prentice Hall.
Tewari, R. (1990). "Expert Design Tools for Physical Database Design." ACM
Transactions on Database Systems pg 538-549.
Tufte, E. (1997). Visual Explanations, Images & Quantities, Evidence & Narrative,
Graphics Press.
Tufte, E. R. (1998). Envisioning Information, Graphics Press.
Wiederhold (1993). "Physical Database Design (DDMS)." ACM Transactions on
Database Systems pg 657-659.
Willits, J. (1992). Database Design & Construction - an open learning course for
students and information managers, Library Association Publishing, London
Influence of non-technical elements on the choice of and engagement with social media platforms: Culture and religion and their impact on how young Saudi adults use social media
No full textThis thesis explores how young Saudi Arabian social media users engage with social media platforms in relation to their social, cultural and religious values. This thesis argues that these elements influence the users’ self-presentation, level of engagement, sharing practices, online identity, and even their community’s acceptance of certain media platforms, alongside the technical and aesthetic design of the platforms. This thesis argues that these non-technical aspects of user engagement need to be considered when designing for user experience, in that they shape behaviour, expectations, and restrictions on users.
This research emerged out of earlier work that suggested a gender difference in social media use and uptake by Saudi youth, which was significantly different from the general Saudi population. This research extends that earlier work by comparing social media use by gender and region within Saudi Arabia. Platforms studied are Facebook, Twitter, Instagram, and Snapchat.
One key influence on Saudi culture is religion, which is, generally, an underexplored area in prior research especially in Saudi social media research. This thesis developed a religiosity scale to assess how and to what extent religious practice influences social media use and to provide a better understanding of the impact of religion as a part of culture. Other influences emerged from the religiosity scale and the wider research: those of family, friends, religious leaders and the wider culture. To further understand various aspects of cultural influence on social media use, this thesis also developed Hofstede’s ideas on collectivistic cultures and power distance. Further evidence shows that spending time in an individualistic culture has little to no bearing on cultural behaviour of members of a collectivistic culture with regards to social media use and uptake.
Data collection was through cultural and religious scales, interviews, social media profile analysis and analysis of public data such as local news coverage and public Imam profiles and comment threads. From this, an overall picture of social media use in Saudi Arabia was synthesized. Female participants were recruited from across three regions in Saudi Arabia and compared with a matched group of male Saudi students living in New Zealand.
This research is important because with the increasing use of social media in Saudi Arabia, it is critical to evaluate the impact of culture on the use of social media, which will help inform the design of user interfaces and tools. It will also help business and government in respect of communication and policy development, such as for privacy. This thesis includes several recommendations for both businesses and social media developers, and recommends areas for further research
Chosen-Ciphertext Secure Hierarchical Identity-Based Key Encapsulation Mechanisms
No full textIn 1984, Shamir managed to build an Identity-Based Encryption (IBE) scheme in which an entity's public identification information, such as an email address or a telephone number, can be used as a valid public key. For instance, in an IBE email system, when Alice wishes to send an email to Bob at [email protected], she simply encrypts the email using the public key string "[email protected]", without the need for Bob's public key certificate. Once Bob receives the encrypted email, he authenticates himself to a trusted third party, which we call the Private Key Generator (PKG), to request his private key corresponding to the public identity [email protected]. After receiving the private key, Bob can read the email. It was not until 2001 that the first efficient and provably secure IBE scheme was presented by Boneh and Franklin. Since then, this breakthrough technology has pushed back the boundaries of exploring schemes based on the idea of identity-based cryptography, and various extensions were developed, such as Hierarchical Identity-Based Encryption (HIBE) schemes and Identity-Based Key Encapsulation Mechanisms (IB-KEMs).
An IBE scheme employs only one PKG (i.e., root PKG) to generate private keys to its users, while an HIBE scheme as a generalisation of IBE contains a hierarchy of PKGs, which can greatly reduce the workload of the root PKG by delegating identity authentication and private key generation to its descendant PKGs.
By comparison with (H)IBE schemes, in some scenarios, a hybrid encryption scheme may be more attractive since it has an unrestricted message space and is efficient to perform encryption for large amounts of data. Such a scheme is separated into two parts: one part, called Key Encapsulation Mechanism (KEM), focuses on encrypting a symmetric key by public key techniques; while the other part, called Data Encapsulation Mechanism (DEM), concentrates on using the symmetric key to encrypt an actual message. The encryption of the key together with the encryption of the message is then sent to the intended recipient. Bentahar et al. extended the concept of KEM to the identity-based setting and developed a generic IB-KEM which is based on one of Dent's generic KEM constructions. A specific instantiation of the generic IB-KEM was given in the same paper and when combining it with a suitable DEM, we can produce a hybrid IBE scheme (IB-KEM/DEM) that is secure in a strong sense in the random oracle model.
In this work, we primarily study how to extend the concept of KEM to the hierarchical identity-based setting, thereby achieving Hierarchical Identity-Based Key Encapsulation Mechanisms (HIB-KEMs). As to DEM, the other component of a hybrid HIBE scheme (HIB-KEM/DEM), we shall not deal with too much as it is relatively easy to acquire an appropriate DEM which works together with our HIB-KEMs to provide secure hybrid HIBE schemes.
We first construct an HIB-KEM, which is secure in a strong sense in the random oracle model, from Gentry and Silverberg's basic HIBE scheme, which is secure in a weak sense in the random oracle model. In addition, we discuss how to shorten the length of encapsulated keys as the depth of a recipient increases in the resulting HIB-KEM.
Next, we shift our attention to the constructions of HIB-KEM that are secure without random oracle models and present a couple of HIB-KEMs of this type. Basically, both HIB-KEMs are built on the Boyen-Mei-Waters Hierarchical Identity-Based Key Encapsulation Mechanism (BMW-KEM), but from different angles. The first one is as secure as the BMW-KEM, but having an improved efficiency. The efficiency is achieved by incorporating into the BMW-KEM a tag technique proposed by Abe et al., accordingly, replacing almost all the quite expensive pairing-based verifications for the validity of an encapsulated key with only one Message Authentication Code (MAC)-based verification. MAC can be quickly produced with the help of fast hash functions, such as MD5 or SHA-1, and the resulting overhead is trivial. The second one makes use of threshold technology to resolve the key escrow problem that is inherent in the original BMW-KEM. In the threshold BMW-KEM, at least a certain amount (threshold) of PKGs are required to cooperate for the decapsulation of a given encapsulated key
Investigating Cultural Dimensions via Developers Artefacts: The Utility of Repository Mining
Get PDFA growing body of research is using artefacts from online development communities to explore the impact of developers’ behaviours on the software development process. Although this research has produced many insights, researchers have yet to fully explore the impact of developers’ cultural backgrounds on their behaviours in an online community, although such understandings could be useful for helping the community to understand and plan for team dynamics. This study utilised a pragmatic case study to explore the relationship between culture and online behaviour among developers from the United States (U.S.), China, and Russia—three countries that differ in their orientations as individualistic or collectivist cultures. The data for the study comprised artefacts supplied over an 11-year period by users of Stack Overflow1, a popular online programming community that addresses questions from members by providing them with rapid access to the knowledge and expertise of their peers. Artefacts consisted of developers’ questions and answers, personal profiles, Up and Down voting records, online reputations, and earned badges. Data mining techniques, as well as statistical, linguistic, and content analysis were used to compare artefacts from the three groups of developers based on their cultural orientation as individualistic or collectivistic, attitudes, and interaction and knowledge sharing patterns. The findings revealed differences among the three groups that were consistent with their cultural backgrounds. U.S. developers, who are from an individualistic culture, asked and responded to more questions, had higher average reputations, used the pronoun “I” more frequently, and were more task- focused. Conversely, Chinese developers, who are from a collectivistic culture, provided more extensive commenting and editing of posts, used the pronouns “we” and “you” more frequently, and were more likely to engage in information exchange. Russian developers had been using Stack Overflow the longest and were the most reflective. The cultural patterns identified in this study have numerous implications for enhancing in- group interactions and behaviour management among software development communities
Influence of non-technical elements on the choice of and engagement with social media platforms: Culture and religion and their impact on how young Saudi adults use social media
No full textThis thesis explores how young Saudi Arabian social media users engage with social media platforms in relation to their social, cultural and religious values. This thesis argues that these elements influence the users’ self-presentation, level of engagement, sharing practices, online identity, and even their community’s acceptance of certain media platforms, alongside the technical and aesthetic design of the platforms. This thesis argues that these non-technical aspects of user engagement need to be considered when designing for user experience, in that they shape behaviour, expectations, and restrictions on users.
This research emerged out of earlier work that suggested a gender difference in social media use and uptake by Saudi youth, which was significantly different from the general Saudi population. This research extends that earlier work by comparing social media use by gender and region within Saudi Arabia. Platforms studied are Facebook, Twitter, Instagram, and Snapchat.
One key influence on Saudi culture is religion, which is, generally, an underexplored area in prior research especially in Saudi social media research. This thesis developed a religiosity scale to assess how and to what extent religious practice influences social media use and to provide a better understanding of the impact of religion as a part of culture. Other influences emerged from the religiosity scale and the wider research: those of family, friends, religious leaders and the wider culture. To further understand various aspects of cultural influence on social media use, this thesis also developed Hofstede’s ideas on collectivistic cultures and power distance. Further evidence shows that spending time in an individualistic culture has little to no bearing on cultural behaviour of members of a collectivistic culture with regards to social media use and uptake.
Data collection was through cultural and religious scales, interviews, social media profile analysis and analysis of public data such as local news coverage and public Imam profiles and comment threads. From this, an overall picture of social media use in Saudi Arabia was synthesized. Female participants were recruited from across three regions in Saudi Arabia and compared with a matched group of male Saudi students living in New Zealand.
This research is important because with the increasing use of social media in Saudi Arabia, it is critical to evaluate the impact of culture on the use of social media, which will help inform the design of user interfaces and tools. It will also help business and government in respect of communication and policy development, such as for privacy. This thesis includes several recommendations for both businesses and social media developers, and recommends areas for further research
Enhancing Citation Context based Information Services through Sentence Context Identification
Get PDFOver the years, scientific articles have played a vital role in disseminating scientific knowledge. Typically, the published scientific information builds upon the previous or existing scientific knowledge and citations play a key role in presenting the argument of the article and defining inter-article relationships across articles. Understanding the use of citations within articles and citation relationships across articles is essential for conducting good research. However, the search and browsing capabilities to trace these relationships are currently limited to finding documents citing a given document and providing links to citing documents, and do not provide insights about the reasons for citations either within an article or across articles. Development of information systems capable of identifying these reasons can be helpful in providing useful services for the research community.
Against this background, we investigate in this thesis the possibility of identifying contexts associated with sentences in scientific articles and use this information to provide useful citation context based information services. To achieve this objective, we developed an annotation scheme that defines context types for sentences in scientific articles. An inter-rater reliability study was carried out to examine the reliability of our scheme. We achieved an overall agreement of 89.93% among annotators, indicating the acceptability of our scheme. In order to develop a contextual model of sentence context types in scientific article, we developed the Sentence Context Ontology for generating semantic contextual data that was used for developing applications that provide contextual information services. We also developed a text extraction and preparation system for processing scientific documents.
Another key aspect of citation context based information services is the ability to automatically identify contexts of sentences. We achieved this by using Conditional Random Fields (CRFs), a sequential probabilistic classifier. We trained the CRF classifier using a training dataset of 1000 paragraphs extracted from 71 research articles and achieved an accuracy of 91% in classifying the sentences according to our proposed scheme.
Finally, using the results obtained from the tasks described above, we developed various applications for providing citation context based information services. These included a standalone system and applications using linked data principles and Web APIs
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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