Marrying Universal Dependencies and Universal Morphology

The Universal Dependencies (UD) and Universal Morphology (UniMorph) projects each present schemata for annotating the morphosyntactic details of language. Each project also provides corpora of annotated text in many languages - UD at the token level and UniMorph at the type level. As each corpus is built by different annotators, language-specific decisions hinder the goal of universal schemata. With compatibility of tags, each project's annotations could be used to validate the other's. Additionally, the availability of both type- and token-level resources would be a boon to tasks such as parsing and homograph disambiguation. To ease this interoperability, we present a deterministic mapping from Universal Dependencies v2 features into the UniMorph schema. We validate our approach by lookup in the UniMorph corpora and find a macro-average of 64.13% recall. We also note incompatibilities due to paucity of data on either side. Finally, we present a critical evaluation of the foundations, strengths, and weaknesses of the two annotation projects.Comment: UDW1

The psychological dimension of transformation in teacher learning

Against a background which recognises pedagogical content knowledge as the distinctive element of teacher competence/expertise, this theoretical essay argues for its central construct - that of transformation – to be understood by teachers and teacher-educators in psychological terms (as was originally proposed by Dewey). Transformation requires teachers to fashion disciplinary knowledge such that it is accessible to the learner. It is argued that for transformation to happen, teacher thinking must include a sophisticated grasp of cognition and metacognition if teachers are to be characterised as competent, let alone expert. This article is written within a context of considerable social and academic scrutiny in the United Kingdom of the form and content of professional teacher preparation and development. In recent years the contribution of psychological knowledge to teacher-education has been filtered through procedural lenses of how best to 'manage classrooms', 'assess learning', 'build confidence' or whatever without a matched concern for psychological constructs through which such issues might be interpreted; thus leaving teachers vulnerable in their professional understandings of learning and its complexities. That society now requires high-level cognitive engagement amongst its participants places cognitive and metacognitive demands on teachers which can only be met if they themselves are conceptually equipped

Completing Queries: Rewriting of IncompleteWeb Queries under Schema Constraints

Reactive Web systems, Web services, and Web-based publish/ subscribe systems communicate events as XML messages, and in many cases require composite event detection: it is not sufficient to react to single event messages, but events have to be considered in relation to other events that are received over time. Emphasizing language design and formal semantics, we describe the rule-based query language XChangeEQ for detecting composite events. XChangeEQ is designed to completely cover and integrate the four complementary querying dimensions: event data, event composition, temporal relationships, and event accumulation. Semantics are provided as model and fixpoint theories; while this is an established approach for rule languages, it has not been applied for event queries before

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

Supporting Semantically Enhanced Web Service Discovery for Enterprise Application Integration

The availability of sophisticated Web service discovery mechanisms is an essential prerequisite for increasing the levels of efficiency and automation in EAI. In this chapter, we present an approach for developing service registries building on the UDDI standard and offering semantically-enhanced publication and discovery capabilities in order to overcome some of the known limitations of conventional service registries. The approach aspires to promote efficiency in EAI in a number of ways, but primarily by automating the task of evaluating service integrability on the basis of the input and output messages that are defined in the Web service’s interface. The presented solution combines the use of three technology standards to meet its objectives: OWL-DL, for modelling service characteristics and performing fine-grained service matchmaking via DL reasoning, SAWSDL, for creating semantically annotated descriptions of service interfaces, and UDDI, for storing and retrieving syntactic and semantic information about services and service providers

Towards a Formal Approach to Validating and Verifying Functional Design for Complex Safety Critical Systems

The quality and reliability of safety criticalsoftware systems are highly dependent on proper systemvalidation and verification. In model-driven softwaredevelopment, semi-formal notations are often used inrequirements capture. Though semi-formal notations possessadvantages, their major disadvantage is their imprecision. Atechnique to eliminate imprecision is to transform semi-formalmodels into an analyzable representation using formalspecification techniques (FSTs). With this approach to systemvalidation and verification, safety critical systems can bedeveloped more reliably. This work documents early experienceof applying FSTs on UML class diagrams as attributeconstraints, and pre- post-conditions on procedures. Thevalidation and verification of the requirements of a system tomonitor unmanned aerial vehicles in unrestricted airspace is theorigin of this work. The challenge is the development of a systemwith incomplete specifications; multiple conflicting stakeholders’interests; existence of a prototype system; the need forstandardized compliance, where validation and verification areparamount, which necessitates forward and reverse engineeringactivities

Refining Transformation Rules For Converting UML Operations To Z Schema

The UML (Unified Modeling Language) has its origin in mainstream software engineering and is often used informally by software designers. One of the limitations of UML is the lack of precision in its semantics, which makes its application to safety critical systems unsuitable. A safety critical system is one in which any loss or misinterpretation of data could lead to injury, loss of human lives and/or property. Safety Critical systems are usually specified by very precisely and frequently required formal verification. With the continuous use of UML in the software industry, there is a need to augment the informality of software models produced to remove ambiguity and inconsistency in models for verification and validation. To overcome this well-known limitation of UML, formal specification techniques (FSTs), which are mathematically tractable, are often used to represent these models. Formal methods are mathematical techniques that allow software developers to produce softwares that address issues of ambiguity and error in complex and safety critical systems. By building a mathematically rigorous model of a complex system, it is possible to verify the system\u27s properties in a more thorough fashion than empirical testing. In this research, the author refines transformation rules for aspects of an informally defined design in UML to one that is verifiable, i.e. a formal specification notation. The specification language that is used is the Z Notation. The rules are applied to UML class diagram operation signatures iteratively, to derive Z schema representation of the operation signatures. Z representation may then be analyzed to detect flaws and determine where there is need to be more precise in defining the operation signatures. This work is an extension of previous research that lack sufficient detail for it to be taken to the next phase, towards the implementation of a tool for semi-automated transformation

The effect of background knowledge on young children's comprehension of explicit and implicit information

Bibliography: leaves 15-16Supported in part by the National Institute of Educatio

Formal Validation of Schema Clustering for Large Information Systems

To become usable for documentation and visualisation purposes, the conceptual schema of a large information system (IS) has to be clustered. [1] But most of the clustering , abstraction , or concentration rules proposed in [1]-[6] are substantiated only intuitively and have not been validated formally. As a consequence, the application of these rules to large IS schemata leads to inconsistencies (e.g. cyclic references), unnecessary loss of information (e.g. arbitrary object type subsets), and/or impractical results (e.g. combinatorical explosion). In this paper, the NF2 relational model [7] is used to validate the application of clustering operations to conceptual schemata. Based on this validation concept and a critical review of schema clustering literature, some validated, general clustering rules are presented. The schema clustering concept is extended to the clustering of textual documentations. To prove the concept\u27s feasibility, conceptual schemata and textual documentations of SAP\u27s R/3 modules Production Planning and Sales & Distribution have been clustere

Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version)

Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data