Ing. Vojtěch Knaisl

Článek

10.1007/s10844-023-00809-w

Katedra softwarového inženýrství

Along with the ongoing digitalization of society, we witness a strong movement to make scientific data FAIR, machine-actionable, and available in the form of knowledge graphs. On the other hand, converting machine-actionable data from knowledge graphs back into human-oriented formats, including documents, graphical, or voice user interfaces, poses significant challenges. The solutions often build on various templates tailored to specific platforms on top of the shared underlying data. These templates suffer from limited reusability, making their adaptations difficult. Moreover, the continuous evolution of data or technological advancements requires substantial efforts to maintain these templates over time. In general, these challenges increase software development costs and are error-prone. In this paper, we propose a solution based on Normalized Systems Theory to address this challenge with the aim of achieving evolvability and sustainability in the transformation process of knowledge graphs into human-oriented formats with broad applicability across domains and technologies. We explain the theoretical foundation and design theorems used in our solution and outline the approach and implementation details. We theoretically evaluate our solution by comparing it to the traditional approach, where the systems are crafted manually. The evaluation shows that our solution is more efficient and effective on a large scale, reducing the human labor required to maintain various templates and supported target platforms. Next, we demonstrate the technical feasibility of our solution on a proof-of-concept implementation in a domain of data management planning that may also serve as a basis for future development.

Stať ve sborníku

10.1007/978-3-031-04819-7_14

Katedra softwarového inženýrství

During the last decade, there was a huge shift in the problem of evolvability. However, still, the problem remains fully unresolved. Our focus is to improve evolvability in the domain of data stewardship planning. The main problem causing the low evolvability is the use of traditional documents – data management plans. Our approach redesigns the workflow of creating the data management plan with a possibility to extend an application to similar well-structured documents in different domains. We base our approach on principles and recommendations from the Normalized Systems Theory and on the usage of ontologies. The result is a new workflow that should increase the evolvability compared to the current state.

Stať ve sborníku

10.1007/978-3-030-45688-7_5

Katedra softwarového inženýrství

A problem of evolvability is widely discussed in the current world, and still, it has not been fully addressed yet. Our approach tries to improve evolvability in a domain of documents. Our approach is based on principles and recommendations from the Normalized Systems Theory. We try to redefine the process of how the document is created and maintained by involving ontologies. We offer a solution which should increase evolvability for a sort of documents which is created by a template and which is often updated. We demonstrate our solution to an example of a Data Management Plan document.

Stať ve sborníku

10.1007/978-3-030-35646-0_6

Katedra softwarového inženýrství

In the current world, low evolvability of documents is a big challenge which has not been fully addressed. This paper focuses on types of documents which have mostly predefined structure, and we use them over and over. Examples of these documents are contracts, applications, legal documents or manuals. The key problem here is that the documents are not modular and evolvable. The problem of modularity and evolvability is addressed by Normalized Systems Theory. This theory is formally proven, and it has great practical results from the first application in a software area. This paper designs a way how to apply principles and recommendations from Normalized Systems Theory in the area of non-evolvable documents.

Článek

10.5334/dsj-2019-059

Katedra softwarového inženýrství

The Data Stewardship Wizard is a tool for data management planning that is focused on getting the most value out of data management planning for the project itself rather than on fulfilling obligations. It is based on FAIR Data Stewardship, in which each data-related decision in a project acts to optimize the Findability, Accessibility, Interoperability and/or Reusability of the data. The background to this philosophy is that the first reuser of the data is the researcher themselves. The tool encourages the consulting of expertise and experts, can help researchers avoid risks they did not know they would encounter by confronting them with practical experience from others, and can help them discover helpful technologies they did not know existed. In this paper, we discuss the context and motivation for the tool, we explain its architecture and we present key functions, such as the knowledge model evolvability and migrations, assembling data management plans, metrics and evaluation of data management plans.