Enhancing Traceability in Clinical Research Data through a Metadata Framework

Background The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tools provide limited metadata traceability capabilities and are unable to query variables across all phases of the data lifecycle. Objectives To develop a metadata traceability framework that can help query and visualize traceability metadata, identify traceability gaps, and validate metadata traceability to improve data lineage and reproducibility within clinical research studies. Methods This research follows the design science research paradigm where the objective is to create and evaluate an information technology (IT) artifact that explicitly addresses an organizational problem or opportunity. The implementation and evaluation of the IT artifact demonstrate the feasibility of both the design process and the final designed product. Results We present Trace-XML, a metadata traceability framework that extends standard clinical research metadata models and adapts graph traversal algorithms to provide clinical research study traceability queries, validation, and visualization. Trace-XML was evaluated using analytical and qualitative methods. The analytical methods show that Trace-XML accurately and completely assesses metadata traceability within a clinical research study. A qualitative study used thematic analysis of interview data to show that Trace-XML adds utility to a researcher's ability to evaluate metadata traceability within a study. Conclusion Trace-XML benefits include features that (1) identify traceability gaps in clinical study metadata, (2) validate metadata traceability within a clinical study, and (3) query and visualize traceability metadata. The key themes that emerged from the qualitative evaluation affirm that Trace-XML adds utility to the task of creating and assessing end-to-end clinical research study traceability.

Accommodating Practices During Episodes of Disillusionment with Mobile IT

This study investigates how tablet users react when technology falls short of their expectations. We deploy a data/frame model to study this process and investigate resistance-related reactions and the deployment of accommodating practices at the individual level. Analyzing user blogs that provide narratives on user interaction with tablets, we identify triggers of episodes of disillusionment and illustrate five sensemaking paths that users follow, eventually leading to one of three practices: 1) users choose to defer tasks until the situation changes, or they abandon the platform altogether; 2) they develop workarounds at different levels of proficiency; or 3) they proceed by reframing their expectations of the platform. By revealing user decision-making process during episodes of disillusionment, the findings contribute to information systems post-adoption research. At a practical level, the findings inform IT artifact and application design by offering insights on how users process discrepancies between their expectations and actual use experience.

Augmenting Advanced Analytics into Enterprise Systems: A Focus on Post-Implementation Activities

An analytics-empowered enterprise system looks to many organizations to be a far-fetched target, owing to the vast amounts of factors that need to be controlled across the implementation lifecycle activities, especially during usage and maintenance phases. On the other hand, advanced analytics techniques such as machine learning and data mining have been strongly present in academic as well as industrial arenas through robust classification and prediction. Correspondingly, this paper is set out to address a methodological approach that works on tackling post-live implementation activities, focusing on employing advanced analytics techniques to detect (business process) problems, find and recommend a solution to them, and confirm the solution. The objective is to make enterprise systems self-moderated by reducing the reliance on vendor support. The paper will profile an advanced analytics engine architecture fitted on top of an enterprise system to demonstrate the approach. Employing an advanced analytics engine has the potential to support post-implementation activities. Our research is innovative in two ways: (1) it enables enterprise systems to become self-moderated and increase their availability; and (2) the IT artifact i.e., the analytics engine, has the potential to solve other problems and be used by other systems, e.g., HRIS. This paper is beneficial to businesses implementing enterprise systems. It highlights how enterprise systems could be safeguarded from retirement caused by post-implementation problems.

A Web-Based Information System to Evaluate Different Versions of IT Artefacts in Online Experiments

Design science research is a common research method in the field of information systems (IS), as it bridges the gap between IS research and practice. The outcome of design science research are artifacts, which – besides others –can be prototypical applications, so-called IT artifacts. When such IT artifacts are evaluated as part of a design science research cycle, questionnaires and inter- views are a commonly used method. We have integrated the demonstration and evaluation phase of a web-based IT artifact, by developing a web-based infor- mation system which integrates both a web-based prototype with a questionnaire system. Our information system supports multiple studies, different versions of the IT artifact and several question-specific and participant-specific configura- tion options.

Decision making support in security forces command centers at open air music festivals: Localization of resources and sharing information

We describe a case study on decision making in command centers of security forces at major open air music festivals. Our goal was to assess current modus operandi and to identify design implications. We have carried out two expert interviews, two field observations and four group discussions with experts based on a fully functional prototype as IT artifact to concretize discussions. Key insights are that in this case localization of relevant resources is the most important aspect of situation awareness, and that state of current knowledge needs to be clearly shared within the command center.