The Experts below are selected from a list of 4206 Experts worldwide ranked by ideXlab platform
Sebastian Link - One of the best experts on this subject based on the ideXlab platform.
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a Fourth Normal Form for uncertain data
Conference on Advanced Information Systems Engineering, 2019Co-Authors: Ziheng Wei, Sebastian LinkAbstract:Relational database design addresses applications for data that is certain. Modern applications require the handling of uncertain data. Indeed, one dimension of big data is veracity. Ideally, the design of databases helps users quantify their trust in the data. For that purpose, we need to establish a design framework that handles responsibly any knowledge of an organization about the uncertainty in their data. Naturally, such knowledge helps us find database designs that process data more efficiently. In this paper, we apply possibility theory to introduce the class of possibilistic multivalued dependencies that are a significant source of data redundancy. Redundant data may occur with different degrees, derived from the different degrees of uncertainty in the data. We propose a family of Fourth Normal Forms for uncertain data. We justify our proposal showing that its members characterize schemata that are free from any redundant data occurrences in any of their instances at the targeted level of uncertainty in the data. We show how to automatically transForm any schema into one that satisfies our proposal, without loss of any inFormation. Our results are founded on axiomatic and algorithmic solutions to the implication problem of possibilistic functional and multivalued dependencies which we also establish.
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foundations for a Fourth Normal Form over sql like databases
Conceptual Modelling and Its Theoretical Foundations, 2012Co-Authors: Flavio Ferrarotti, Sven Hartmann, Henning Kohler, Sebastian Link, Millist W. VincentAbstract:In the relational model of data the Fourth Normal Form condition guarantees the elimination of data redundancy in terms of functional and multivalued dependencies. For efficient means of data processing the industry standard SQL permits partial data and duplicate rows of data to occur in database systems. Here, the combined class of uniqueness constraints, functional and multivalued dependencies is more expressive than the class of functional and multivalued dependencies itself. Consequently, the Fourth Normal Form condition is not suitable for SQL databases. We characterize the associated implication problem of the combined class in the presence of NOT NULL constraints axiomatically, algorithmically and logically. Based on these results we are able to establish a suitable Fourth Normal Form condition for SQL.
Ranjit Biswas - One of the best experts on this subject based on the ideXlab platform.
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intuitionistic fuzzy multivalued dependency and intuitionistic fuzzy Fourth Normal Form
FICTA, 2016Co-Authors: Asma R Shora, Afshar M Alam, Ranjit BiswasAbstract:Intuitionistic fuzzy databases are used to handle imprecise and uncertain data as they represent the membership, nonmembership, and hesitancy associated with a certain element in a set. This paper presents the Intuitionistic Fuzzy Fourth Normal Form to decompose the multivalued dependent data. A technique to determine Intuitionistic Fuzzy multivalued dependencies by working on the closure of dependencies has been proposed. We derive the closure by obtaining all the logically implied dependencies by a set of Intuitionistic Fuzzy multivalued dependencies, i.e., Inference Rules. A complete set of inference rules for the Intuitionistic Fuzzy multivalued dependencies has been given along with the derivation of each rule. These rules help us to compute the dependency closure and we further use the same for defining the Intuitionistic Fuzzy Fourth Normal Form.
Rami Bahsoon - One of the best experts on this subject based on the ideXlab platform.
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Prioritizing Technical Debt in Database Normalization Using Portfolio Theory and Data Quality Metrics
arXiv: Software Engineering, 2018Co-Authors: Mashel Albarak, Rami BahsoonAbstract:Database Normalization is the one of main principles for designing relational databases. The benefits of Normalization can be observed through improving data quality and perFormance, among the other qualities. We explore a new context of technical debt manifestation, which is linked to ill-Normalized databases. This debt can have long-term impact causing systematic degradation of database qualities. Such degradation can be liken to accumulated interest on a debt. We claim that debts are likely to materialize for tables below the Fourth Normal Form. Practically, achieving Fourth Normal Form for all the tables in the database is a costly and idealistic exercise. Therefore, we propose a pragmatic approach to prioritize tables that should be Normalized to the Fourth Normal Form based on the metaphoric debt and interest of the ill-Normalized tables, observed on data quality and perFormance. For data quality, tables are prioritized using the risk of data inconsistency metric. Unlike data quality, a suitable metric to estimate the impact of weakly or un-Normalized tables on perFormance is not available. We estimate perFormance degradation and its costs using Input\Output (I\O) cost of the operations perFormed on the tables and we propose a model to estimate this cost for each table. We make use of Modern Portfolio Theory to prioritize tables that should be Normalized based on the estimated I\O cost and the likely risk of cost accumulation in the future. To evaluate our methods, we use a case study from Microsoft, AdventureWorks. The results show that our methods can be effective in reducing Normalization debt and improving the quality of the database.
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Identifying and Managing Technical Debt in Database Normalization Using Machine Learning and Trade-off Analysis
arXiv: Software Engineering, 2017Co-Authors: Mashel Albarak, Muna Alrazgan, Rami BahsoonAbstract:Technical debt is a metaphor that describes the long term effects of shortcuts taken in software development activities to achieve near term goals. In this study, we explore a new context of technical debt that relates to database Normalization design decisions. We posit that ill Normalized databases can have long term ramifications on data quality, perFormance degradation and maintainability costs over time, just like debts accumulate interest. Conversely, conventional database approaches would suggest Normalizing weakly Normalized tables, this can be a costly process in terms of effort and expertise it requires for large software systems. As studies have shown that the Fourth Normal Form is often regarded as the ideal Form in database design, we claim that database Normalization debts are likely to be incurred for tables below this Form. We refer to Normalization debt item as any table in the database below the Fourth Normal Form. We propose a framework for identifying Normalization debt. Our framework makes use of association rule mining to discover functional dependencies between attributes in a table, which will help determine the current Normal Form of that table and identify debt tables. To manage such debts, we propose a trade off analysis method to prioritize tables that are candidate for Normalization. The trade off is between the rework cost and the debt effect on the quality of the system as the metaphoric interest. To evaluate our method, we use a case study from Microsoft, AdventureWorks. The results show that our method can reduce the cost and effort of Normalization, while improving the database design.
Asma R Shora - One of the best experts on this subject based on the ideXlab platform.
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intuitionistic fuzzy multivalued dependency and intuitionistic fuzzy Fourth Normal Form
FICTA, 2016Co-Authors: Asma R Shora, Afshar M Alam, Ranjit BiswasAbstract:Intuitionistic fuzzy databases are used to handle imprecise and uncertain data as they represent the membership, nonmembership, and hesitancy associated with a certain element in a set. This paper presents the Intuitionistic Fuzzy Fourth Normal Form to decompose the multivalued dependent data. A technique to determine Intuitionistic Fuzzy multivalued dependencies by working on the closure of dependencies has been proposed. We derive the closure by obtaining all the logically implied dependencies by a set of Intuitionistic Fuzzy multivalued dependencies, i.e., Inference Rules. A complete set of inference rules for the Intuitionistic Fuzzy multivalued dependencies has been given along with the derivation of each rule. These rules help us to compute the dependency closure and we further use the same for defining the Intuitionistic Fuzzy Fourth Normal Form.
Millist W. Vincent - One of the best experts on this subject based on the ideXlab platform.
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foundations for a Fourth Normal Form over sql like databases
Conceptual Modelling and Its Theoretical Foundations, 2012Co-Authors: Flavio Ferrarotti, Sven Hartmann, Henning Kohler, Sebastian Link, Millist W. VincentAbstract:In the relational model of data the Fourth Normal Form condition guarantees the elimination of data redundancy in terms of functional and multivalued dependencies. For efficient means of data processing the industry standard SQL permits partial data and duplicate rows of data to occur in database systems. Here, the combined class of uniqueness constraints, functional and multivalued dependencies is more expressive than the class of functional and multivalued dependencies itself. Consequently, the Fourth Normal Form condition is not suitable for SQL databases. We characterize the associated implication problem of the combined class in the presence of NOT NULL constraints axiomatically, algorithmically and logically. Based on these results we are able to establish a suitable Fourth Normal Form condition for SQL.
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REDUNDANCY AND THE JUSTIFICATION FOR Fourth Normal Form IN RELATIONAL DATABASES
International Journal of Foundations of Computer Science, 1993Co-Authors: Millist W. Vincent, Bala SrinivasanAbstract:The relationship between the absence of redundancy in relational databases and Fourth Normal Form (4NF) is investigated. A relation scheme is defined to be redundant if there exists a legal relation defined over it which has at least two tuples that are identical on the attributes in a functional dependency (FD) or multivalued dependency (MVD) constraint. Depending on whether the dependencies in a set of constraints or the dependencies in the closure of the set is used, two different types of redundancy are defined. It is shown that the two types of redundancy are equivalent and their absence in a relation scheme is equivalent to the 4NF condition.
