Clinical data wrangling using Ontological Realism and Referent Tracking

Ontological realism aims at the development of high quality ontologies that faithfully represent what is general in reality and to use these ontologies to render heterogeneous data collections comparable. To achieve this second goal for clinical research datasets presupposes not merely (1) that the requisite ontologies already exist, but also (2) that the datasets in question are faithful to reality in the dual sense that (a) they denote only particulars and relationships between particulars that do in fact exist and (b) they do this in terms of the types and type-level relationships described in these ontologies. While much attention has been devoted to (1), work on (2), which is the topic of this paper, is comparatively rare. Using Referent Tracking as basis, we describe a technical data wrangling strategy which consists in creating for each dataset a template that, when applied to each particular record in the dataset, leads to the generation of a collection of Referent Tracking Tuples (RTT) built out of unique identifiers for the entities described by means of the data items in the record. The proposed strategy is based on (i) the distinction between data and what data are about, and (ii) the explicit descriptions of portions of reality which RTTs provide and which range not only over the particulars described by data items in a dataset, but also over these data items themselves. This last feature allows us to describe particulars that are only implicitly referred to by the dataset; to provide information about correspondences between data items in a dataset; and to assert which data items are unjustifiably or redundantly present in or absent from the dataset. The approach has been tested on a dataset collected from patients seeking treatment for orofacial pain at two German universities and made available for the NIDCR-funded OPMQoL project

A conceptual framework for studying collective reactions to events in location-based social media

Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events

A software system for teaching and commanding the industrial robots

Design features of a system for programming the industrial robots with dynamic control are described. When specifying the system, special attention was given to achieving hardware transportability, simplicity of communication between the user and the system, possibility of active user participation in generation of control algorithms, and possibility of implementing the software on a computer with relatively modest characteristics. The software is intended for implementation on a microprocessor-based system and should enable the user to control a robot via specialized programming language RL which incorporates structures for defining the positions and orientations of working points, motion specification, and synchronization of the robot with its environment. The paper contains descriptions of the RL language and of the system structure. The main characteristics and advantages of the system as well as questions concerning its realization on existing microprocessors are also discussed

A software system for teaching and commanding the industrial robots

Design features of a software system for programming industrial robots with dynamic control are described. The software is intended for implementation an a microprocessor-based system and should enable the user to control a robot via specialized programming language RL. The paper contains description of the RL language and description of the system structure. Main characteristics and advantages of the system as well as questions concerning its realization on existing microprocessors are also discussed

Taxonomy for Humans or Computers? Cognitive Pragmatics for Big Data

Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between precision and ambiguity that are key to designing effective solutions for generating big data about biodiversity. We focus on the importance of theory-dependence as a source of ambiguity in taxonomic nomenclature and hence a persistent challenge for implementing a single, long-term solution to storing and accessing meaningful sets of biological specimens. We argue that ambiguity does have a positive role to play in scientific progress as a tool for efficiently symbolizing multiple aspects of taxa and mediating between conflicting hypotheses about their nature. Pursuing a deeper understanding of the trade-offs and synthesis of precision and ambiguity as virtues of scientific language and communication systems then offers a productive next step for realizing sound, big biodiversity data services

The Blackfoot demonstrative system: Function, form, and meaning

This thesis presents a comprehensive analysis of the Blackfoot demonstrative system. Previous research on Blackfoot (Uhlenbeck 1938, Taylor 1969, Frantz 2009) identifies sixteen morphemes that make up demonstrative words in the language. I propose a demonstrative template that takes into account the fixed morpheme ordering observed in demonstrative forms. Based on the proposed template, I motivate the analysis of the suffix -ka as encoding motion towards the speaker as this accounts for its position together with the suffixes -ya, -ma, and -hka, each of which encode features of motion or visibility. In describing situational functions of each of the morphemes, I make use of Imai’s (2003) inventory of spatial deictic features. I present the first analysis of the morphologically analyzable, but heretofore undescribed suffix -o as encoding the geometric configuration feature [interior]. This thesis also offers the first explanation of the syntactic contexts that govern the two identificational suffixes -ayi and -ao’ka. Earlier analyses of the Blackfoot demonstrative system focus on the spatial features encoded by situational uses of demonstratives to the exclusion of other pragmatic functions. As a result, the proposals do not address variations in meaning when used in non-situational pragmatic contexts. To address this gap in the literature, I examine non-situational pragmatic functions, as well as symbolic situational demonstrative uses (e.g. deictic projection, wider-context). The result of this study is a comprehensive analysis of the Blackfoot demonstrative system which takes into account both syntactic and pragmatic functions, providing new insights into the meanings of many of the morphemes that comprise the system. It also provides support from Blackfoot for Himmelmann’s (1996) claim that there are four universal pragmatic functions of demonstratives, and support for Diessel’s (1999) claim that situational uses are the basic demonstrative uses from which the others are derived

A Two-Level Identity Model To Support Interoperability of Identity Information in Electronic Health Record Systems.

The sharing and retrieval of health information for an electronic health record (EHR) across distributed systems involves a range of identified entities that are possible subjects of documentation (e.g., specimen, clinical analyser). Contemporary EHR specifications limit the types of entities that can be the subject of a record to health professionals and patients, thus limiting the use of two level models in healthcare information systems that contribute information to the EHR. The literature describes several information modelling approaches for EHRs, including so called “two level models”. These models differ in the amount of structure imposed on the information to be recorded, but they generally require the health documentation process for the EHR to focus exclusively on the patient as the subject of care and this definition is often a fixed one. In this thesis, the author introduces a new identity modelling approach to create a generalised reference model for sharing archetype-constrained identity information between diverse identity domains, models and services, while permitting reuse of published standard-based archetypes. The author evaluates its use for expressing the major types of existing demographic reference models in an extensible way, and show its application for standards-compliant two-level modelling alongside heterogeneous demographics models. This thesis demonstrates how the two-level modelling approach that is used for EHRs could be adapted and reapplied to provide a highly-flexible and expressive means for representing subjects of information in allied health settings that support the healthcare process, such as the laboratory domain. By relying on the two level modelling approach for representing identity, the proposed design facilitates cross-referencing and disambiguation of certain demographics standards and information models. The work also demonstrates how it can also be used to represent additional clinical identified entities such as specimen and order as subjects of clinical documentation

Informed Consent to Address Trust, Control, and Privacy Concerns in User Profiling

More and more, services and products are being personalised or\ud tailored, based on user-related data stored in so called user profiles or user\ud models. Although user profiling offers great benefits for both organisations and\ud users, there are several psychological factors hindering the potential success of user profiling. The most important factors are trust, control and privacy\ud concerns. This paper presents informed consent as a means to address the\ud hurdles trust, control, and privacy concerns pose to user profiling

Music 2025 : The Music Data Dilemma: issues facing the music industry in improving data management

© Crown Copyright 2019Music 2025ʼ investigates the infrastructure issues around the management of digital data in an increasingly stream driven industry. The findings are the culmination of over 50 interviews with high profile music industry representatives across the sector and reflects key issues as well as areas of consensus and contrasting views. The findings reveal whilst there are great examples of data initiatives across the value chain, there are opportunities to improve efficiency and interoperability