An Indicator Function for Insufficient Data Quality – A Contribution to Data Accuracy

Görz, Quirin; Kaiser, Marcus

doi:10.1007/978-3-642-33244-9_12

Cited by 6 publications

(9 citation statements)

References 25 publications

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“…But also, we can find PS where the contextual aspects of DQ dimensions are based on the ISO/IEC 25012 standard 3 [47,54,69]. To a lesser extent, authors claim that the contextual aspects of the DQ dimensions depend on metadata [45,83] and the task at hand [53]. As we saw before in [10], from another perspective Batini and Scannapieco analyze models for utility-driven quality assessment.…”

Section: Review Resultsmentioning

confidence: 93%

“…In the metrics category, [45] investigates how metrics for the DQ dimensions completeness, validity, and currency can be aggregated to derive an indicator for the accuracy dimension. In [51], a set of requirements for DQ metrics is presented.…”

Section: Review Resultsmentioning

confidence: 99%

“…Although these are also metadata, we consider important to have a category for them, since they are a special type of metadata. For instance, the authors in [45] investigate how metrics for the DQ dimensions completeness, validity, and currency can be aggregated to derive an indicator for accuracy. They highlight that although it is well known that there are interdependencies between particular DQ dimensions, their measurement are usually discussed independently from each other.…”

Section: User Characteristicsmentioning

confidence: 99%

“…Numerical indicators applying functions. In this case, numerical indicators are calculated by applying functions.The context components represented with this representation are metadata [83] and DQ values [6,45]. In [83] an indicator function maps the set of metadata to binary values 0 or 1, where the result 1 denotes that the respective dataset value is incorrect, otherwise it is 0, meaning "clean data".…”

Section: Context Components Representationmentioning

confidence: 99%

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Use of Context in Data Quality Management: a Systematic Literature Review

Serra¹,

Peralta²,

Marotta³

et al. 2022

Preprint

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The importance of context in data quality (DQ) was shown many years ago and nowadays is widely accepted. Early approaches and surveys defined DQ as fitness for use and showed the influence of context on DQ. This paper presents a Systematic Literature Review (SLR) for investigating how context is taken into account in recent proposals for DQ management. We specifically present the planning and execution of the SLR, the analysis criteria and our results reflecting the relationship between context and DQ in the state of the art and, particularly, how that context is defined and used for DQ management.CCS Concepts: • Data Quality → Context in Data Quality Management.

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Section: Review Resultsmentioning

confidence: 93%

Section: Review Resultsmentioning

confidence: 99%

Section: User Characteristicsmentioning

confidence: 99%

Section: Context Components Representationmentioning

confidence: 99%

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Use of Context in Data Quality Management: a Systematic Literature Review

Serra¹,

Peralta²,

Marotta³

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…A common definition of accuracy in information quality (IQ) literature is the proximity of data attributes to its corresponding real-world state (Batini & Scannapieco, 2016;Görz & Kaiser, 2012). However, it is important to note that three types of accuracy metrics are commonly proposed; Boolean, degree and valuedeviation.…”

Section: Information Quality Dimension: Accuracymentioning

confidence: 99%

eHealth-as-a-Service: A Service Based Design Approach for Large Scale eHealth Architecture

Black¹

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A significant challenge for the design of large scale (national) eHealth systems is the fluid nature of the Patient Journey, particularly in primary healthcare modalities.In this context, a patient's journey is predisposed to organic growth rather than intelligent design. As a result, clinical tasks requiring access to high quality information may occur as a function of known healthcare patterns or as a response to a patient's state of health. Whilst Australia's national eHealth system provides the infrastructure to accommodate the self-organizing flexibility and dynamism characteristic of complex information-based ecosystems, the system neglects certain information quality attributes. Specifically, accuracy, timeliness and completeness, which may lead to improved coordination of patient care. Based on the premise that the quality of patient information plays a significant role in the performance of health professionals, consideration must be given to these information quality dimensions as an overarching goal for eHealth architectural design activities. Framed as a problem concerning the design of large scale eHealth architecture that improves the quality of health information, this perspective presents a timely research opportunity.Within a prescriptive design science research (DSR) framework, this thesis is an example of a multi-methodological approach to create and evaluate a purposeful eHealth-as-a-Service (eHaaS) design artifact, which will improve patient information quality. This was achieved by firstly, deriving abstract meta-requirements from an ethnographic examination of care pathways to establish the technical goals of the solution space. Secondly, defining the functions, organization, and structure of an eHaaS conceptual model as an example of how service-based architectures might deliver high quality information services. Finally, by establishing the validity of the conceptual model with the development of a novel evaluation strategy to explain the predicted change produced by an eHaaS design artifact.Several original contributions emerged from the research. First and foremost, the developed eHaaS conceptual model, which encapsulates a set of design principles, service-based architectural patterns and implementation strategies represents a new class of eHealth solution. One that embodies a shift away from data-centric monolithic eHealth-as-a-Service: A Service-Based Design Approach for Large Scale eHealth Architecture iii architecture to process oriented, event-driven application services. To demonstrate the benefits of this shift, an electronic patient information system (ePIMS) was developed as an original solution for orchestrating clinical information services as personalised patient workflows. Another significant contribution of this thesis is a novel evaluation strategy for validating the utility of large scale eHealth systems at the design stage. It is innovative in its use of business process and data modelling techniques (e.g. data flow diagrams, business process modelling notatio...

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