A Diagram Is Worth A Dozen Images

Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding natural images has been extensively studied in computer vision, while diagram understanding has received little attention. In this paper, we study the problem of diagram interpretation and reasoning, the challenging task of identifying the structure of a diagram and the semantics of its constituents and their relationships. We introduce Diagram Parse Graphs (DPG) as our representation to model the structure of diagrams. We define syntactic parsing of diagrams as learning to infer DPGs for diagrams and study semantic interpretation and reasoning of diagrams in the context of diagram question answering. We devise an LSTM-based method for syntactic parsing of diagrams and introduce a DPG-based attention model for diagram question answering. We compile a new dataset of diagrams with exhaustive annotations of constituents and relationships for over 5,000 diagrams and 15,000 questions and answers. Our results show the significance of our models for syntactic parsing and question answering in diagrams using DPGs

Component Composition in Business and System Modelling

Bespoke development of large business systems can be couched in terms of the composition of components, which are, put simply, chunks of development work. Design, mapping a specification to an implementation, can also be expressed in terms of components: a refinement comprising an abstract component, a concrete component and a mapping between them. Similarly, system extension is the composition of an existing component, the legacy system, with a new component, the extension. This paper overviews work being done on a UK EPSRC funded research project formulating and formalizing techniques for describing, composing and performing integrity checks on components. Although the paper focuses on the specification and development of information systems, the techniques are equally applicable to the modeling and re-engineering of businesses, where no computer system may be involved

Drawing OWL 2 ontologies with Eddy the editor

In this paper we introduce Eddy, a new open-source tool for the graphical editing of OWL~2 ontologies. Eddy is specifically designed for creating ontologies in Graphol, a completely visual ontology language that is equivalent to OWL~2. Thus, in Eddy ontologies are easily drawn as diagrams, rather than written as sets of formulas, as commonly happens in popular ontology design and engineering environments. This makes Eddy particularly suited for usage by people who are more familiar with diagramatic languages for conceptual modeling rather than with typical ontology formalisms, as is often required in non-academic and industrial contexts. Eddy provides intuitive functionalities for specifying Graphol diagrams, guarantees their syntactic correctness, and allows for exporting them in standard OWL 2 syntax. A user evaluation study we conducted shows that Eddy is perceived as an easy and intuitive tool for ontology specification

Reasoning with Spider Diagrams

Spider diagrams combine and extend Venn diagrams and Euler circles to express constraints on sets and their relationships with other sets. These diagrams can usefully be used in conjunction with object-oriented modelling notations such as the Unified Modelling Language. This paper summarises the main syntax and semantics of spider diagrams and introduces four inference rules for reasoning with spider diagrams and a rule governing the equivalence of Venn and Euler forms of spider diagrams. This paper also details rules for combining two spider diagrams to produce a single diagram which retains as much of their combined semantic information as possible and discusses disjunctive diagrams as one possible way of enriching the system in order to combine spider diagrams so that no semantic information is lost

On the role of domain ontologies in the design of domain-specific visual modeling langages

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

Challenges in Learning Unified Modeling Language: From the Perspective of Diagrammatic Representation and Reasoning

Unified modeling language (UML) is widely taught in the information systems (IS) curriculum. To understand UML in IS education, this paper reports on an empirical study that taps into students’ learning of UML. The study uses a concept-mapping technique to identify the challenges in learning UML notational elements. It reveals that some technical properties of UML diagrammatic representation, coupled with students’ cognitive attributes, hinder both perceptual and conceptual processes involved in searching, recognizing, and inferring visual information, which creates learning barriers. This paper also discusses how to facilitate perceptual and conceptual processes in instruction to overcome learning challenges. The study provides valuable insights for the IS educators, the UML academic community, and practitioners

A Classification of Infographics

Classifications are useful for describing existing phenomena and guiding further investigation. Several classifications of diagrams have been proposed, typically based on analytical rather than empirical methodologies. A notable exception is the work of Lohse and his colleagues, published in Communications of the ACM in December 1994. The classification of diagrams that Lohse proposed was derived from bottom-up grouping data collected from sixteen participants and based on 60 diagrams. Mean values on ten Likert-scales were used to predict diagram class. We follow a similar methodology to Lohse, using real-world infographics (i.e. embellished data charts) as our stimuli. We propose a structural classification of infographics, and determine whether infographics class can be predicted from values on Likert scales

Sixteen years of Collaborative Learning through Active Sense-making in Physics (CLASP) at UC Davis

This paper describes our large reformed introductory physics course at UC Davis, which bioscience students have been taking since 1996. The central feature of this course is a focus on sense-making by the students during the five hours per week discussion/labs in which the students take part in activities emphasizing peer-peer discussions, argumentation, and presentations of ideas. The course differs in many fundamental ways from traditionally taught introductory physics courses. After discussing the unique features of CLASP and its implementation at UC Davis, various student outcome measures are presented showing increased performance by students who took the CLASP course compared to students who took a traditionally taught introductory physics course. Measures we use include upper-division GPAs, MCAT scores, FCI gains, and MPEX-II scores.Comment: Also submitted to American Journal of Physic