Barbara Weber

Title

Prof. Dr.

Last Name

Weber

First name

Barbara

barbara.weber@unisg.ch

ORCID

0000-0002-6004-4860

Phone

+41 71 224 34 43

Web Site

https://ics.unisg.ch/chair-se-weber/

Google Scholar

https://scholar.google.com/citations?user=iEBRDLkAAAAJ&hl=de

Now showing 1 - 4 of 4

Some of the metrics are blocked by your
consent settings
Understanding Quality in Declarative Process Modeling Through the Mental Models of Experts
(Springer International Publishing, 2020)
Amine Abbad-Andaloussi
;
Christopher J. Davis
;
Andrea Burattin
;
Hugo A. López
;
Tijs Slaats
Imperative process models have become immensely popular. However, their use is usually limited to rigid and repetitive processes. Considering the inherent flexibility in most processes in the real-world and the increased need for managing knowledge-intensive processes, the adoption of declarative languages becomes more pertinent than ever. While the quality of imperative models has been extensively investigated in the literature, little is known about the dimensions affecting the quality of declarative models. This work takes an advanced stride to investigate the quality of declarative models. Following the theory of Personal Construct Psychology (PCT), our research introduces a novel method within the Business Process Management (BPM) field to explore quality in the eyes of expert modelers. The findings of this work summarize the dimensions defining the quality of declarative models. The outcome shows the potential of PCT as a basis to discover quality dimensions and advances our understanding of quality in declarative process models.
Type:conference paper
Journal:Business Process Management
URL:https://link.springer.com/chapter/10.1007/978-3-030-58666-9_24
DOI:10.1007/978-3-030-58666-9_24
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/122088
Scopus© Citations 11
Some of the metrics are blocked by your
consent settings
The Impact of Modularization on the Understandability of Declarative Process Models: A Research Model
(Springer International Publishing, 2020)
Amine Abbad-Andaloussi
;
Pnina Soffer
;
Tijs Slaats
;
Andrea Burattin
;
Barbara Weber
Process models provide a blueprint for process execution and an indispensable tool for process management. Bearing in mind their trending use for requirement elicitation, communication and improvement of business processes, the need for understandable process models becomes a must. In this paper, we propose a research model to investigate the impact of modularization on the understandability of declarative process models. We design a controlled experiment supported by eye-tracking, electroencephalography (EEG) and galvanic skin response (GSR) to appraise the understandability of hierarchical process models through measures such as comprehension accuracy, response time, attention, cognitive load and cognitive integration.
Type:conference paper
Journal:Lecture Notes in Information Systems and Organisation, Information Systems and Neuroscience (NeuroIS)
URL:https://link.springer.com/chapter/10.1007/978-3-030-60073-0_15
DOI:10.1007/978-3-030-60073-0_15
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/122091
Scopus© Citations 9
Some of the metrics are blocked by your
consent settings
Toward an Automated Labeling of Event Log Attributes
(Springer International Publishing, 2018)
Amine Abbad-Andaloussi
;
Andrea Burattin
;
Barbara Weber
Process mining aims at exploring the data produced by executable business processes to mine the underlying control-flow and data-flow. Most of the process mining algorithms assume the existence of an event log with a certain maturity level. Unfortunately, the logs provided by process unaware information systems often do not comply with the required maturity level, since they lack the notion of process instance, also referred in process mining as “case id”. Without a proper identification of the case id attribute in log files, the outcome of process mining algorithms is unpredictable. This paper proposes a new approach that aims to overcome this challenge by automatically inferring the case id attribute from log files. The approach has been implemented as a ProM plugin and evaluated with several real-world event logs. The results demonstrate a high accuracy in inferring the case id attribute.
Type:conference paper
URL:https://link.springer.com/chapter/10.1007/978-3-319-91704-7_6
DOI:10.1007/978-3-319-91704-7_6
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/122093
Scopus© Citations 15
Some of the metrics are blocked by your
consent settings
Evaluating the understandability of hybrid process model representations using eye tracking: first insights
(2018)
Amine Abbad-Andaloussi
;
Tijs Slaats
;
Andrea Burattin
;
Thomas T. Hildebrandt
;
Barbara Weber
Type:conference paper
Journal:Business Process Management Workshops
DOI:10.1007/978-3-030-11641-5_37
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/122079
Scopus© Citations 13

Barbara Weber

Filters

Settings

Sort By

Results per page