Exposing Multi-Relational Networks to Single-Relational Network Analysis Algorithms

Many, if not most network analysis algorithms have been designed specifically for single-relational networks; that is, networks in which all edges are of the same type. For example, edges may either represent "friendship," "kinship," or "collaboration," but not all of them together. In contrast, a multi-relational network is a network with a heterogeneous set of edge labels which can represent relationships of various types in a single data structure. While multi-relational networks are more expressive in terms of the variety of relationships they can capture, there is a need for a general framework for transferring the many single-relational network analysis algorithms to the multi-relational domain. It is not sufficient to execute a single-relational network analysis algorithm on a multi-relational network by simply ignoring edge labels. This article presents an algebra for mapping multi-relational networks to single-relational networks, thereby exposing them to single-relational network analysis algorithms.Comment: ISSN:1751-157

UML Class Diagram or Entity Relationship Diagram : An Object Relational Impedance Mismatch

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model –towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to ithave been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram forconceptual modeling for relational databases, and several popular course text books use UMLnotation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on theother hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice databasedesigner due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER,UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts Keywords: EERD, UML Class Diagram, Relational Database Design, Structural Constraints, relational and object database impedance mismatch. The ER model was originally put forward by Chen [1] and subsequently extensions have been added to add further semantics to the original model; mainly the concepts of specialisation, generalisation and aggregation. In this paper we refer to an Entity-Relationship model (ER) as the basic model and an extended or enhanced entity-relationship model (EER) as a model which includes the extra concepts. The ER and EER models are also often used to aid communication between the designer and the user at the requirements analysis stage. In this paper when we use the term “conceptual model” we mean a model that is not implementation specific.ISBN: 978-84-616-3847-5 3594Peer reviewe

Semantic Interoperability in Archaeological Datasets: Data Mapping and Extraction Via the CIDOC CRM

Abstract. Findings from a data mapping and extraction exercise undertaken as part of the STAR project are described and related to recent work in the area. The exercise was undertaken in conjunction with English Heritage and encompassed five differently structured relational databases containing various results of archaeological excavations. The aim of the exercise was to demonstrate the potential benefits in cross searching data expressed as RDF and conforming to a common overarching conceptual data structure schema- the English Heritage Centre for Archaeology ontological model (CRM-EH), an extension of the CIDOC Conceptual Reference Model (CRM). A semi-automatic mapping/extraction tool proved an essential component. The viability of the approach is demonstrated by web services and a client application on an integrated data and concept network

World city network research at a theoretical impasse::On the need to re-establish qualitative approaches to understanding agency in world city networks

From the late 1990s, the establishment of a new relational ‘turn’ in the study of world city connectedness in globalization has run parallel to the wider relational turn occurring in economic geography. Early work, built firmly upon a qualitative approach to the collection and analyses of new inter-city datasets, considered cities as being constituted by their relations with other cities. Subsequent research, however, would take a strong quantitative turn, best demonstrated through the articulation of the inter-locking world city network (ILWCN) ‘model’ for measuring relations between cities. In this paper, we develop a critique of research based around the ILWCN model, arguing that this ‘top down’ quantitative approach has now reached a theoretical impasse. To address this impasse, we argue for a move away from Structural approaches in which the firm is the main unit of analysis, towards qualitative approaches in which individual agency and practice are afforded greater importance

Exposing the myth: object-relational impedance mismatch is a wicked problem

Addressing a problem of software integration is a fact of life for those involved in software development. The popularity of both object and relational technologies means that they will inevitably be used together. However, the combination of these two technologies introduces problems. These problems are referred to collectively as the object-relational impedance mismatch. A mismatch is addressed using one or more mapping strategies, typically embodied in a pattern. A strategy is concerned with correspondence between the schema of a relational database and an object-oriented program. Such strategies are employed in mapping tools such as Hibernate and TopLink, and reinforce the received wisdom that the problem of object-relational impedance mismatch has been solved. In this paper, we observe that it is not clear whether each strategy, as one possible solution, addresses the cause or a symptom of a mismatch. We argue that the problem is not tame and easily resolved; rather it is complex and wicked. We introduce a catalogue of problem themes that demonstrate the complex nature of the problem and provide a way both to talk about the problem and to understand its complexity. In the future, as software systems become more complex and more connected, it will be important to learn from past endeavours. Our catalogue of problem themes represents a shift, in thinking about the problem of object-relational impedance mismatch, from issues of implementation towards an analysis of cause and effect. Such a shift has implications for those involved in the design of current and future software architectures. Because we have questioned the received wisdom, we are now in a position to work toward an appropriate solution to the problem of object-relational impedance mismatch

Mixed membership stochastic blockmodels

Observations consisting of measurements on relationships for pairs of objects arise in many settings, such as protein interaction and gene regulatory networks, collections of author-recipient email, and social networks. Analyzing such data with probabilisic models can be delicate because the simple exchangeability assumptions underlying many boilerplate models no longer hold. In this paper, we describe a latent variable model of such data called the mixed membership stochastic blockmodel. This model extends blockmodels for relational data to ones which capture mixed membership latent relational structure, thus providing an object-specific low-dimensional representation. We develop a general variational inference algorithm for fast approximate posterior inference. We explore applications to social and protein interaction networks.Comment: 46 pages, 14 figures, 3 table