Tag Archives: qdacityre

Final Thesis: Text Mining for Relationship Extraction

Abstract: Qualitative Data Analysis (QDA) methods are based on manual coding of texts. To extract a domain model from a text corpus using QDA, information has to be extracted and compiled into the domain model by hand. This is especially a problem for cases where large amounts of data have to be analyzed. For this purpose, We present a relationship extraction approach based on Natural Language Processing. It automates the extraction of relationships between codes that were provided by the coder. This speeds up the analysis process and helps to uncover relationships the human coder might have missed. Our method produces a graphical overview of relationships that were found to exist between codes. It is evaluated by comparison with previously generated models from existing Qualitative Data Analysis projects.

Keywords: Information Retrieval, Text Mining, Natural Language Processing, Qualitative Data Analysis, QDA

PDFs: Master Thesis, Work Description

Reference: Martin Hofmann. Text Mining for Relationship Extraction. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2017.

Final Thesis: A Metamodel for Code Systems

Abstract: Requirements elicitation is an important factor in software engineering. Mainly the information needed is elicited through interviews and other qualitative sources. The analysis that follows is often an ad-hoc process that relies on expertise of the analyst(s) and therefore is hardly replicable. Additionally, the process is not transparent as the resulting modeling elements cannot be mapped to the initial data. First attempts to solve this issues by adapting the clearly defined steps of Qualitative Data Analysis (QDA) suggest that the approach should be followed up. In order to further formalize the process this thesis suggests a metamodel which allows to derive structure and behavior models from the same coding process. The metamodel is derived by analyzing an existing metamodel and by comparing different existing coding systems and their resulting modeling artifacts. The metamodel is extended with a rule system and tested on an exemplary data set. For validation the resulting models are compared to models from an ad-hoc modeling process and evaluated by experts. Results show that utilizing QDA with a code system metamodel allows for an increase in transparency and makes it more easy to vary detail levels of the derived models.

Keywords: Domain Model, Domain Analysis, Requirements Engineering, Qualitative Data Analysis, QDA

PDFs: Master Thesis, Work Description

Reference: Sindy Salow. A Metamodel for Code Systems. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2016.

Final Thesis: The Use of Domain Knowledge for Structuring and Describing Code Systems

Abstract: Domain knowledge is a widely used but seldom defined term in research. Since every research project is located in at least one dedicated domain, its influence to the research work seems to be natural but is not investigated, especially not for qualitative research. An exploratory study was performed interviewing eight qualitative researchers located in different domains: economic education, computer science and business sciences. The interviews were qualitatively analysed using Grounded Theory Methodology (GTM). Of particular interest were possibly existing schematic procedures the researchers apply during their qualitative research process and especially during their coding process and if existing how they are rooted in the domain. With the set-up and reuse of a domain specific code schema in one domain the existence of schemata and its integration to QDA could be confirmed. Furthermore, a suggestion was given on how to generate artefacts for Requirements Engineering (RE) in the form of User Stories based on a code schema. Additionally, a code system meta model has been created to clarify the influence of domain knowledge from an abstract perspective.

Keywords: Qualitative Data Analysis, Grounded Theory Methodology, Requirements Engineering, Domain Knowledge

PDFs: Master Thesis, Work Description

Reference: Rebecca Reuter. The Use of Domain Knowledge for Structuring and Describing Code Systems. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2016.

Final Thesis: Integrating Multiple Views In A Code System

Abstract: Mature requirements engineering is one of the key success factors of professional software development. This thesis proposes an approach that adapts core principles of qualitative data analysis, which is well established in social science, and transforms them into a holistic method for requirements analysis. Our method addresses the process steps between the analysis of the target domain and the generation of a requirements specification and different types of domain models. In particular, it aims at inherently providing a high degree of traceability by the institution of an additional artifact, the so-called code system. We state this code system to introduce significant advantages to the quality of requirements analysis with respect to systematics, documentation, maintainability and efficiency. The proposed approach features the direct deduction of different types of domain models out of the gathered domain knowledge and a substantial support for the development of a requirements specification.

Keywords: Domain Analysis, Domain Modeling, Qualitative Data Analysis, Requirements Engineering, Requirements Specification

PDFs: Diplomarbeit, Work Description

Reference: Florian Schmitt. Integrating Multiple Views In A Code System. Diplomarbeit, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2016.

Final Thesis: Improving Domain Modeling And Requirements Analysis Using Grounded Theory

Abstract: One of the key factors of the success of professional software development is mature requirements engineering. This thesis focuses on the elicitation and analysis of requirements and addresses the process steps between the elicitation of requirements and the gathering of the system requirements speci cation and domain model. We consider the state-of-the-art of these aspects of requirements engineering as suboptimal and propose an approach that implements the elicitation and analysis of requirements as an adaption of the Grounded Theory approach, which is methodically sound at the eld of social studies. Our approach will implicate the institution of an additional artifact within the process, the  so-called code system. Furthermore this approach enables the direct mapping from the  gathered information about the target domain, represented in the code system, into a  domain model.

Keywords: Domain Analysis, Domain Modeling, Qualitative Data Analysis, Requirements Engineering

PDFs: Studienarbeit, Work Description

Reference: Florian Schmitt. Improving Domain Modeling And Requirements Analysis Using Grounded Theory. Studienarbeit, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2015.

Final Thesis: Developing a Domain Analysis Procedure based on Grounded Theory Method

Abstract: Domain analysis is the process of analyzing and modelling the domain in which a future software system is supposed to operate. It is an essential step in requirements engineering (RE) and therefore critical for the success of software development projects. However, common methods for deriving a domain model from natural language descriptions do not address the difficulties of abstracting a complex domain sufficiently and depend on the analyst’s experience and expertise. Grounded theory method (GTM) offers a techniques for breaking up and abstracting qualitative data by developing and relating concepts. Its use can therefore improve the procedure of extracting the important entities of a domain and their relationships, while ensuring traceability between the data and the derived domain model. This thesis shows how GTM has to be adapted for its successful utilization in RE. For this purpose, we applied GTM to a domain analysis example and derived a systematic procedure for domain analysis.

Keywords: Domain Analysis, Domain Model, Requirements Engineering, Qualitative Data Analysis, Grounded Theory Method

PDFs: Master Thesis, Work Description

Reference: Katharina Kunz. Developing a Domain Analysis Procedure based on Grounded Theory Method. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2015.

Research Paper: Improving Traceability of Requirements through Qualitative Data Analysis

Abstract: Traceability is an important quality aspect in modern software development. It facilitates the documentation of decisions and helps identifying conflicts regarding the conformity of one artifact to another. We propose a new approach to requirements engineering that utilizes qualitative research methods, which have been well established in the domain of social science. Our approach integrates traceability between the original documentation and the requirements specification and the domain model and glossary and supports adaptability to change.

Keywords: Requirements analysis, requirements traceability, qualitative data analysis

Reference: Andreas Kaufmann, Dirk Riehle. “Improving Traceability of Requirements through Qualitative Data Analysis.” In Proceedings of the 2015 Software Engineering Konferenz (SE 2015). Springer Verlag, to appear.

The paper is available as a PDF file.

Final Thesis: A Quality Metric of QDA-Derived Theories Using Object-Oriented Modeling

Abstract: Qualitative data analysis is widely accepted as valid approach for inductively developing theories. The in-depth analysis of individual experience often results in novel findings, potentially explaining less common phenomena. However, to achieve valuable results, the discovery must be compliant to various implications and prescribed processes. Grounded theory is a qualitative methodology constituted by very specific procedures, which in turn are supposed to foster scientific rigor. However, there is no definite framework or evaluation strategy, defining which criteria constitute good theory. By building upon principles of qualitative analysis and object-oriented programming, this research suggest an approach to quality assessment for emergent theories. Results demonstrate that a semi-formal memo annotation enables evaluation of code-systems, while providing traceability and follow-up data processing.

Keywords: QDA, qualitative data analysis, quality metrics

PDFs: Master Thesis, Work Description

Reference: Eugen Ananin. A Quality Metric of QDA-Derived Theories Using Object-Oriented Modeling. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2015.

Final Thesis: Definition of a Domain-Specific Language using Qualitative Data Analysis (in German)

Abstract: The design of a domain-specific language, DSL, requires extensive technical and professional know-how. Essential is not only the creation of syntax, semantics and related tools of language, but also an extensive knowledge of the domain. In order to acquire the knowledge of domain experts, we present an approach based on qualitative data analysis (QDA). We illustrate the process of creating a DSL based on the derivation of a domain model of qualitative analyzed interviews with domain experts. We then present the integration of the acquired specialized concepts and activities in a DSL. Qualitative feedback from domain experts could confirm the successful implementation of the DSL and according to that also the entire process.

Keywords: Qualitative data analysis, QDA, domain-specific language, DSL, requirements engineering

PDFs: Master Thesis, Work Description

Reference: Benjamin Mempel. Definition einer DSL mittels QDA. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2015.

Final Thesis: Using Natural Language Processing to Support Interview Analysis

Abstract: In the social sciences the process of interview analysis is often performed as a form of qualitative data analysis (QDA), to extract relevant information from transcribed interviews. A researcher performing such an analysis is usually assisted by Computer-Assisted Qualitative Data Analysis Software (CAQDAS), which provides a structured framework for coding documents. We expect that this process may significantly benefit from the application of natural Language Processing (NLP). This thesis provides an overview of potential applications for different NLP technologies. We applied a machine learning approach to automatically generate codings for an existing coding system. During a prototypical implementation of an autocoding algorithm we measured the impact of different NLP techniques on the autocoding process.

Keywords: QDA, NLP, Interview Analysis, CAQDAS, Coding, Autocoding

PDFs: Master Thesis, Work Description

Reference: Andreas Kaufmann. Using Natural Language Processing to Support Interview Analysis. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2014.