HDLalert – a healthcare DL alerting system: from user needs to implementation

Data linkage in medical science using the resource description framework: the AVERT model

There is an ongoing challenge as to how best manage and understand ‘big data’ in precision medicine settings. This paper describes the potential for a Linked Data approach, using a Resource Description Framework (RDF) model, to combine multiple datasets with temporal and spatial elements of varying dimensionality. This “AVERT model” provides a framework for converting multiple standalone files of various formats, from both clinical and environmental settings, into a single data source. This data source can thereafter be queried effectively, shared with outside parties, more easily understood by multiple stakeholders using standardized vocabularies, incorporating provenance metadata and supporting temporo-spatial reasoning. The approach has further advantages in terms of data sharing, security and subsequent analysis. We use a case study relating to anti-Glomerular Basement Membrane (GBM) disease, a rare autoimmune condition, to illustrate a technical proof of concept for the AVERT model.

Data linkage in medical science using the resource description framework: the AVERT model

There is an ongoing challenge as to how best manage and understand 'big data' in precision medicine settings. This paper describes the potential for a Linked Data approach, using a Resource Description Framework (RDF) model, to combine multiple datasets with temporal and spatial elements of varying dimensionality. This "AVERT model" provides a framework for converting multiple standalone files of various formats, from both clinical and environmental settings, into a single data source. This data source can thereafter be queried effectively, shared with outside parties, more easily understood by multiple stakeholders using standardized vocabularies, incorporating provenance metadata and supporting temporo-spatial reasoning. The approach has further advantages in terms of data sharing, security and subsequent analysis. We use a case study relating to anti-Glomerular Basement Membrane (GBM) disease, a rare autoimmune condition, to illustrate a technical proof of concept for the AVERT model.

Conceptual misfits in e‐mail‐based current‐awareness interaction

Purpose

This research aims to identify some requirements for supporting user interactions with electronic current‐awareness alert systems based on data from a professional work environment.

Design/methodology/approach

Qualitative data were gathered using contextual inquiry observations with 21 workers at the London office of an international law firm. The analysis uses CASSM (“Concept‐based Analysis of Surface and Structural Misfits”), a usability evaluation method structured around identifying mismatches, or “misfits”, between user‐concepts and concepts represented within a system.

Findings

Participants were frequently overwhelmed by e‐mail alerts, and a key requirement is to support efficient interaction. Several misfits, which act as barriers to efficient reviewing and follow‐on activities, are demonstrated. These relate to a lack of representation of key user‐concepts at the interface and/or within the system, including alert items and their properties, source documents, “back‐story”, primary sources, content categorisations and user collections.

Research limitations/implications

Given these misfits, a set of requirements is derived to improve the efficiency with which users can achieve key outcomes with current‐awareness information as these occur within a professional work environment.

Originality/value

The findings will be of interest to current‐awareness providers. The approach is relevant to information interaction researchers interested in deriving design requirements from naturalistic studies.