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On Context Frames and Their Implementations
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-0396-1993
2021 (English)In: BUSINESS MODELING AND SOFTWARE DESIGN (BMSD 2021) / [ed] Shishkov B, Springer, 2021, Vol. 422, p. 133-153Conference paper, Published paper (Refereed)
Abstract [en]

When an actor is selecting an action in order to fulfill its intents, in a given context, the actor’s knowledge and beliefs about the specific context will impact the possibility to achieve a desired outcome. The context is often affected by unobserved, or unmeasured, factors, which can impact the result of the desired outcome.

The context specific knowledge and beliefs an actor has about a domain, together with the possibilities to evaluate and learn which actions shall be taken, are packaged into a context frame. Our intention with this study is to evaluate an implementation of such a context frame. The context frame concept is meant to support actors to fulfill their intents in a given knowledge domain, by enforcing the needed, and available, actions which cause effects on the outcomes. We have built our implementation of the context frame on the OODA-loop, Pask’s conversation theory, and structural causal models, by using a Bayesian approach, and probabilistic programming.

The research approach is based on evaluation research. We evaluated our implementation with the help of a proof of concept. During the proof of concept we used data sets containing decisions about treatment and survival analysis regarding cancer patients, information obtained during focus group interviews, and questionnaire data.

The proof of concept used to evaluate our implementation of a context frame was regarded as successful and the concept of context frames deemed as useful.

Our division of a context frame in three parts, supported by four different types of analysis functions, made it easier to create a solution which supports evaluation and learning.

Place, publisher, year, edition, pages
Springer, 2021. Vol. 422, p. 133-153
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 422
Keywords [en]
Bayesian approach, Structural causal models, Context frame
National Category
Software Engineering
Research subject
Software Engineering; Computer Science
Identifiers
URN: urn:nbn:se:bth-22177DOI: 10.1007/978-3-030-79976-2_8ISI: 000841498500008Scopus ID: 2-s2.0-85117795365ISBN: 9783030799755 (print)OAI: oai:DiVA.org:bth-22177DiVA, id: diva2:1600774
Conference
11th International Symposium on Business Modeling and Software Design, BMSD 2021, Sofia, Bulgaria, 5 July 2021 through 7 July 2021
Available from: 2021-10-05 Created: 2021-10-05 Last updated: 2022-09-02Bibliographically approved
In thesis
1. Towards Intent-Driven Systems Based on Context Frames
Open this publication in new window or tab >>Towards Intent-Driven Systems Based on Context Frames
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this research project we investigate how machine actors can support the business intents (desired outcomes) of an enterprise via predictive execution flows, prescriptive execution flows, and bidirectional knowledge creation between human actors and machine actors. A context frame supports bidirectional knowledge creation via interventions and counterfactual analysis. An intent-driven system combines execution flows to obtain business intents, and a context frame is a component in these flows. 

Our aim is to develop theoretical frameworks supporting intent-driven systems and context frames, and to validate the components needed to realize such frame- works. 

We are using the design science framework as our research framework. During our design science study we have used the following research methods: systematic literature review, case study, quasi experiment, action research, and evaluation research. 

We have created theoretical frameworks supporting intent-driven systems, and context frames, and implemented needed functionality in the involved components. The framework supports knowledge creation and knowledge validation. The possibility of using the knowledge for predictive analysis, prescriptive analysis, and counterfactual analysis, makes it possible to obtain bidirectional knowledge creation between a human actor and a machine actor. This enables a context frame to be part of an intent-driven system which supports predictive, and prescriptive, executions flows. 

The produced artifacts provide answers to our research questions. These answers are a base for theoretical frameworks supporting intent-driven systems and context frames, and provide knowledge of how to construct the components needed to realize these frameworks. 

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2021. p. 50
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 2021:08
Keywords
business intent, knowledge creation, decision making, rule adherence, OODA-loop, causal models
National Category
Software Engineering
Research subject
Software Engineering
Identifiers
urn:nbn:se:bth-22178 (URN)978-91-7295-430-4 (ISBN)
Public defence
2021-12-10, J1630 + Zoom, Campus Gräsvik, Karlskrona, 09:30 (English)
Opponent
Supervisors
Funder
Knowledge Foundation
Available from: 2021-10-08 Created: 2021-10-07 Last updated: 2021-11-23Bibliographically approved

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Silvander, Johan

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