Visual Analytics for Soundness Verification of Process Models

2018 ◽  
pp. 744-756 ◽  
Author(s):  
Humberto S. Garcia Caballero ◽  
Michel A. Westenberg ◽  
Henricus M. W. Verbeek ◽  
Wil M. P. van der Aalst
Keyword(s):  
Visual Analytics ◽  
Process Models

scholarly journals Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics

2021 ◽  
pp. 1-21
Author(s):  
Fabio Campos ◽  
June Ahn ◽  
Daniela K. DiGiacomo ◽  
Ha Nguyen ◽  
Maria Hays
Keyword(s):  
Visual Analytics ◽  
School Context ◽  
The United States ◽  
Mixed Methods Study ◽  
Process Models ◽  
Instructional Coaches ◽  
School Settings ◽  
Making Sense ◽  
Vantage Points ◽  
K 12

With the spread of learning analytics (LA) dashboards in K--12 schools, educators are increasingly expected to make sense of data to inform instruction. However, numerous features of school settings, such as specialized vantage points of educators, may lead to different ways of looking at data. This observation motivates the need to carefully observe and account for the ways data sensemaking occurs, and how it may differ across K--12 professional roles. Our mixed-methods study reports on interviews and think-aloud sessions with middle-school mathematics teachers and instructional coaches from four districts in the United States. By exposing educators to an LA dashboard, we map their varied reactions to visual data and reveal prevalent sensemaking patterns. We find that emotional, analytical, and intentional responses inform educators’ sensemaking and that different roles at the school afford unique vantage points toward data. Based on these findings, we offer a typology for representing sensemaking in a K--12 school context and reflect on how to expand visual LA process models.

An Analytics Framework for Physician Adherence to Clinical Practice Guidelines: Knowledge-Based Approach (Preprint)

2018 ◽  
Author(s):  
Jaehoon Lee ◽  
Nathan C Hulse
Keyword(s):  
Clinical Practice ◽  
Knowledge Base ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Visual Analytics ◽  
Process Models ◽  
Care Process ◽  
Knowledge Based ◽  
Clinical Databases ◽  
Knowledge Content

BACKGROUND One of the problems in evaluating clinical practice guidelines (CPGs) is the occurrence of knowledge gaps. These gaps may occur when evaluation logics and definitions in analytics pipelines are translated differently. OBJECTIVE The objective of this paper is to develop a systematic method that will fill in the cognitive and computational gaps of CPG knowledge components in analytics pipelines. METHODS We used locally developed CPGs that resulted in care process models (CPMs). We derived adherence definitions from the CPMs, transformed them into computationally executable queries, and deployed them into an enterprise knowledge base that specializes in managing clinical knowledge content. We developed a visual analytics framework, whose data pipelines are connected to queries in the knowledge base, to automate the extraction of data from clinical databases and calculation of evaluation metrics. RESULTS In this pilot study, we implemented 21 CPMs within the proposed framework, which is connected to an enterprise data warehouse (EDW) as a data source. We built a Web–based dashboard for monitoring and evaluating adherence to the CPMs. The dashboard ran for 18 months during which CPM adherence definitions were updated a number of times. CONCLUSIONS The proposed framework was demonstrated to accommodate complicated knowledge management for CPM adherence evaluation in analytics pipelines using a knowledge base. At the same time, knowledge consistency and computational efficiency were maintained.

scholarly journals Visual Analytics in Process Mining for Supporting Business Process Improvement

2021 ◽  
Author(s):  
Antonia Kaouni ◽  
Georgia Theodoropoulou ◽  
Alexandros Bousdekis ◽  
Athanasios Voulodimos ◽  
Georgios Miaoulis
Keyword(s):  
Business Process ◽  
Visual Analytics ◽  
Domain Knowledge ◽  
Business Processes ◽  
Process Mining ◽  
Conceptual Modeling ◽  
Research Field ◽  
Process Models ◽  
Event Log ◽  
Business User

The increasing amounts of data have affected conceptual modeling as a research field. In this context, process mining involves a set of techniques aimed at extracting a process schema from an event log generated during process execution. While automatic algorithms for process mining and analysis are needed to filter out irrelevant data and to produce preliminary results, visual inspection, domain knowledge, human judgment and creativity are needed for proper interpretation of the results. Moreover, a process discovery on an event log usually results in complicated process models not easily comprehensible by the business user. To this end, visual analytics has the potential to enhance process mining towards the direction of explainability, interpretability and trustworthiness in order to better support human decisions. In this paper we propose an approach for identifying bottlenecks in business processes by analyzing event logs and visualizing the results. In this way, we exploit visual analytics in the process mining context in order to provide explainable and interpretable analytics results for business processes without exposing to the user complex process models that are not easily comprehensible. The proposed approach was applied to a manufacturing business process and the results show that visual analytics in the context of process mining is capable of identifying bottlenecks and other performance-related issues and exposing them to the business user in an intuitive and non-intrusive way.

Identifying suboptimalities with factorial model comparison

2018 ◽  
Vol 41 ◽  
Author(s):  
Wei Ji Ma
Keyword(s):  
Experimental Design ◽  
Model Comparison ◽  
Process Models ◽  
Multiple Forms ◽  
Factorial Experimental Design ◽  
Factorial Model ◽  
Multiple Components ◽  
The Many

AbstractGiven the many types of suboptimality in perception, I ask how one should test for multiple forms of suboptimality at the same time – or, more generally, how one should compare process models that can differ in any or all of the multiple components. In analogy to factorial experimental design, I advocate for factorial model comparison.

A Comparison of Single- and Dual-Process Models of Retrieval Experiences

2007 ◽  
Author(s):  
Lutz Cupper ◽  
Edgar Erdfelder ◽  
Monika Undorf
Keyword(s):  
Process Models ◽  
Dual Process ◽  
Dual Process Models

Re-examining dominance of categories in impression formation: A test of dual-process models.

2018 ◽  
Vol 115 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Brian M. Monroe ◽  
Bryan L. Koenig ◽  
Kum Seong Wan ◽  
Tei Laine ◽  
Swati Gupta ◽  
...  
Keyword(s):  
Impression Formation ◽  
Process Models ◽  
Dual Process ◽  
Dual Process Models

Habitat use of toothed whales in a marine protected area based on point process models

2019 ◽  
Vol 609 ◽  
pp. 239-256 ◽  
Author(s):  
TL Silva ◽  
G Fay ◽  
TA Mooney ◽  
J Robbins ◽  
MT Weinrich ◽  
...  
Keyword(s):  
Habitat Use ◽  
Point Process ◽  
Protected Area ◽  
Marine Protected Area ◽  
Process Models ◽  
Point Process Models
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