Ing. Marek Suchánek, Ph.D. et Ph.D.

Stať ve sborníku

10.5220/0012837900003756

Katedra softwarového inženýrství

In recent times, Data Management Planning has become increasingly crucial. Effective practices in data management ensure more precise data collection, secure storage, proper handling, and utilization beyond the primary project. However, existing DMPs often suffer from complex structures that impede accessibility for humans and machines. This project aims to address these challenges by converting DMPs into formats that are both machine-actionable and human-readable. Leveraging established DMP templates and relevant ontologies, our methodology involves analyzing diverse approaches to achieve this dual functionality. We assess machine-actionability through comparative evaluations using AI and NLP tools. Furthermore, we identify gaps in ontologies, laying the groundwork for future enhancements in this critical area of research.

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10.3233/FAIA230229

Katedra softwarového inženýrství

Effective management of research data is crucial in modern scientific research, and ontologies and vocabularies play a significant role in describing and organizing such data. However, the abundance of available ontologies and vocabularies for various aspects of research data management (RDM) poses challenges in selecting the most suitable ones. This work aims to comprehensively analyze the key ontologies relevant to data stewardship and RDM. By investigating concepts, properties, interlinks, and potential overlaps, we establish and describe the relationships between these selected ontologies. Our analysis not only enhances understanding of existing ontologies and vocabularies used in RDM but also suggests practical applications for the outcomes of this study. For instance, we propose leveraging the findings to develop semantic data management plans in RDF, thereby improving the organization and accessibility of research data. Moreover, we identify potential ontologies for future extensions of this work.

Článek

10.5334/dsj-2023-028

Katedra softwarového inženýrství

Most research funders require Data Management Plans (DMPs). The review process can be time consuming, since reviewers read text documents submitted by researchers and provide their feedback. Moreover, it requires specific expert knowledge in data stewardship, which is scarce. Machine-actionable Data Management Plans (maDMPs) and semantic technologies increase the potential for automatic assessment of information contained in DMPs. However, the level of automation and new possibilities are still not well-explored and leveraged. This paper discusses methods for the automation of DMP assessment. It goes beyond generating human-readable reports. It explores how the information contained in maDMPs can be used to provide automated pre-assessment or to fetch further information, allowing reviewers to better judge the content. We map the identified methods to various reviewer goals.

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10.3233/FAIA230230

Katedra softwarového inženýrství

OntoUML, an ontology-driven conceptual modelling language based on the Unified Foundational Ontology (UFO), has been demonstrated to have superior clarity in comparison to other commonly used modeling languages, as supported by empirical evidence. Furthermore, the use of RDF technology has led to the creation of the gUFO ontology, enabling the interoperability and reuse of RDF tools, thereby providing new opportunities to explore and evaluate large OntoUML/UFO models and their instances/data. This study utilizes the SPARQL query language to evaluate the quality of OntoUML models and develop queries for identifying and retrieving instances of anti-patterns defined for OntoUML. The effectiveness of these queries is assessed by applying them to a set of conceptual models of varying complexity that have been captured using gUFO.

Článek

10.1186/s13326-022-00274-4

Katedra softwarového inženýrství

The concept of Data Management Plan (DMP) has emerged as a fundamental tool to help researchers through the systematical management of data. The Research Data Alliance DMP Common Standard (DCS) working group developed a set of universal concepts characterising a DMP so it can be represented as a machine-actionable artefact, i.e., machine-actionable Data Management Plan (maDMP). The technology-agnostic approach of the current maDMP specification: (i) does not explicitly link to related data models or ontologies, (ii) has no standardised way to describe controlled vocabularies, and (iii) is extensible but has no clear mechanism to distinguish between the core specification and its extensions.This paper reports on a community effort to create the DMP Common Standard Ontology (DCSO) as a serialisation of the DCS core concepts, with a particular focus on a detailed description of the components of the ontology. Our initial result shows that the proposed DCSO can become a suitable candidate for a reference serialisation of the DMP Common Standard.

Článek

10.1007/s10844-022-00706-8

Katedra softwarového inženýrství

Functional requirements on a software system are traditionally captured as text that describes the expected functionality in the domain of a real-world system. Natural language processing methods allow us to extract the knowledge from such requirements and transform it, e.g., into a model. Moreover, these methods can improve the quality of the requirements, which usually suffer from ambiguity, incompleteness, and inconsistency. This paper presents a novel approach to using natural language processing. We use the method of grammatical inspection to find specific patterns in the description of functional requirement specifications (written in English). Then, we transform the requirements into a model of Normalized Systems elements. This may realize a possible component of the eagerly awaited text-to-software pipeline. The input of this method is represented by textual requirements. Its output is a running prototype of an information system created using Normalized Systems (NS) techniques. Therefore, the system is ready to accept further enhancements, e.g., custom code fragments, in an evolvable manner ensured by compliance with the NS principles. A demonstration of pipeline implementation is also included in this paper. The text processing part of our pipeline extends the existing pipeline implemented in our system TEMOS, where we propose and implement methods of checking the quality of textual requirements concerning ambiguity, incompleteness, and inconsistency.

Článek

10.1162/dint_a_00179

Katedra softwarového inženýrství

Rapid and effective data sharing is necessary to control disease outbreaks, such as the current coronavirus pandemic. Despite the existence of data sharing agreements, data silos, lack of interoperable data infrastructures, and different institutional jurisdictions hinder data sharing and accessibility. To overcome these challenges, the Virus Outbreak Data Network (VODAN)-Africa initiative is championing an approach in which data never leaves the institution where it was generated, but, instead, algorithms can visit the data and query multiple datasets in an automated way. To make this possible, FAIR Data Points – distributed data repositories that host machine-actionable data and metadata that adhere to the FAIR Guidelines (that data should be Findable, Accessible, Interoperable and Reusable) – have been deployed in participating institutions using a dockerised bundle of tools called VODAN in a Box (ViB). ViB is a set of multiple FAIR-enabling and open-source services with a single goal: to support the gathering of World Health Organization (WHO) electronic case report forms (eCRFs) as FAIR data in a machine-actionable way, but without exposing or transferring the data outside the facility. Following the execution of a proof of concept, ViB was deployed in Uganda and Leiden University. The proof of concept generated a first query which was implemented across two continents. A SWOT (strengths, weaknesses, opportunities and threats) analysis of the architecture was carried out and established the changes needed for specifications and requirements for the future development of the solution.

Článek

10.1162/dint_a_00161

Katedra softwarového inženýrství

While the FAIR Principles do not specify a technical solution for ‘FAIRness’, it was clear from the outset of the FAIR initiative that it would be useful to have commodity software and tooling that would simplify the creation of FAIR-compliant resources. The FAIR Data Point is a metadata repository that follows the DCAT(2) schema, and utilizes the Linked Data Platform to manage the hierarchical metadata layers as LDP Containers. There has been a recent flurry of development activity around the FAIR Data Point that has significantly improved its power and ease-of-use. Here we describe five specific tools—an installer, a loader, two Web-based interfaces, and an indexer—aimed at maximizing the uptake and utility of the FAIR Data Point.

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10.3233/FAIA220290

Katedra softwarového inženýrství

Normalized Systems are a model-driven development technique focusing on evolvability and sustainability of resulting enterprise information systems. It applies well-defined principles to create a fine-grained modular structure while limiting combinatorial effects. The systems are generated (or, more precisely, expanded) from models of so-called NS Elements. NS has its own modelling language; however, interoperability with other knowledge representations is necessary. This work presents our solution for transforming knowledge kept in one of the most generic forms – RDF semantic triples – to NS Elements. The transformation enables mapping using RDFS/OWL ontologies describing both the input RDF. It utilizes SPARQL for executing the transformation to RDF based on the existing NS Element ontology. The presented transformation is demonstrated on an example case study, and its features and limitations are discussed together with potential future steps.

Článek

10.5334/dsj-2021-032

Katedra softwarového inženýrství

This paper presents the application profile for machine-actionable data management plans that allows information from traditional data management plans to be expressed in a machine-actionable way. We describe the methodology and research conducted to define the application profile. We also discuss design decisions made during its development and present systems which have adopted it. The application profile was developed in an open and consensus-driven manner within the DMP Common Standards Working Group of the Research Data Alliance and is its official recommendation.

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10.3233/FAIA210018

Katedra softwarového inženýrství

Normalized Systems (NS) theory describes how to design and develop evolvable systems. It is applied in practice to generate enterprise information systems using NS Expanders from models of NS Elements. As there are various wellestablished modelling languages, the possibility to (re-)use them to create NS applications is desired. This paper presents a mapping between the NS metamodel and the Ecore metamodel as a representant of essential structural modelling. The mapping is the basis of the transformation execution tool based on Eclipse Modeling Framework and NS Java libraries. Both the mapping and the tool are demonstrated in a concise case study but cover all essential Ecore constructs. During the work, several interesting similarities of the two metamodels were found and are described, e.g., its meta-circularity or ability to specify data types using references to Java classes. Still, there are significant differences between the metamodels that prevent some constructs from being mapped. The issues with information loss upon the transformation are mitigated by incorporating additional options that serve as key-value annotations. The results are ready to be used for any Ecore models to create an NS model that can be expanded into an NS application.

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Katedra softwarového inženýrství

RDF data are being described by ontologies (OWL or RDFS) to state the meaning and promote interoperability or so-called machine-readability. However, there are many overlapping ontologies that one can use for a single dataset. To overcome this issue, mappings between ontologies are made to capture the relations forming the overlaps. Such mappings can be used with inference and reasoning tools, but rewriting rules must be applied to transform the dataset. This work proposes a new way of transformations builds on top of the SPARQL query language. It uses defined RDF patterns representing modules that can be interrelated. Our method's primary focus is for larger-scale transformations where existing methods require hard-to-maintain, i.e., non-evolvable mapping definitions. A brief demonstration, as well as a comparison with other transformation languages, is provided.

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10.5220/0010653900003064

Katedra softwarového inženýrství

Business Object Relationship Modeling (BORM) is a business process analysis method based on communicating finite-state machines and Petri nets. However, because of its tooling support and non-interoperability of formats, it is rather niche. This work proposes a way of representing the knowledge from BORM process models in RDF by creating a BORM ontology. It benefits from previous work done on different conceptual and process modelling languages and their transformations to OWL. The resulting RDF representation brings increased interoperability and enhanced analysis possibilities, e.g., using SPARQL or RDF visualization tools. A part of this work is also a BORM-to-RDF export feature for the OpenPonk modelling platform. The resulting BORM ontology is ready for use in practice and further work.

Stať ve sborníku vyzvaná či oceněná

10.1007/978-3-030-70006-5_9

Katedra softwarového inženýrství

Normalized Systems (NS) enables sustainable software development and maintenance using code generation of evolvable information systems from models of so-called NS Elements. To promote semantic interoperability with other conceptual models, RDF and OWL technologies can be used for knowledge representation in NS as it is common within the Semantic Web and Linked Open Data domains. Previous research resulted in initial NS-OWL bi-directional transformation and a prototype tool for its execution. In this extended paper, these efforts are further elaborated into an evolvable solution based on NS Expanders. The transformation utilizes RDF to encode all domain-specific structural knowledge of an NS model to ensure bi-directionality. In addition, it also maps entities of NS metamodel to OWL concepts to serve as an ontology for underlying data. Because of the metacircular NS metamodel, any NS model including the metamodel itself, can be transformed. Moreover, the transformation of application data to or from RDF is also possible. Having the NS metamodel, NS models, and potentially also data in RDF opens further research possibilities in terms of analysis and integrations. The use of NS Expanders caused that the solution can be easily extended and refined, e.g. when the metamodel is updated. The results of our research are expected to help with the design of real-world information systems, including the NS tooling and the metamodel.

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10.5220/0009356800740085

Katedra softwarového inženýrství

Knowledge representation in OWL ontologies gained a lot of popularity with the development of Big Data, Artificial Intelligence, Semantic Web, and Linked Open Data. OWL ontologies are very versatile, and there are many tools for analysis, design, documentation, and mapping. They can capture concepts and categories, their properties and relations. Normalized Systems (NS) provide a way of code generation from a model of so-called NS Elements resulting in an information system with proven evolvability. The model used in NS contains domain-specific knowledge that can be represented in an OWL ontology. This work clarifies the potential advantages of having OWL representation of the NS model, discusses the design of a bi-directional transformation between NS models and domain ontologies in OWL, and describes its implementation. It shows how the resulting ontology enables further work on the analytical level and leverages the system design. Moreover, due to the fact that NS metamodel is metacircular, the transformation can generate ontology of NS metamodel itself. It is expected that the results of this work will help with the design of larger real-world applications as well as the metamodel and that the transformation tool will be further extended with additional features which we proposed.

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10.1109/CBI49978.2020.00036

Katedra softwarového inženýrství

Building ontologies in The Web Ontology Language (OWL) as a knowledge representation about a particular domain gained a lot of interest over the recent years. Thanks to its large community and many options concerning tooling and methods for representation and transformations, OWL is being used not only in Linked Open Data and Artificial Intelligence but also in conceptual modelling. OWL allows capturing concepts and their properties, including relationships which can also be done using traditional conceptual models, for example, in Unified Modelling Language (UML). Both UML and OWL have their own specifics when compared to each other, and one may be more suitable than the other in concrete cases. There are several methods for transformation between knowledge representation in OWL and UML. In this paper, we review key methods for transforming UML to OWL and vice versa. To compare the methods, we use a non-trivial conceptual model that contains all commonly used constructs, e.g., generalization sets, composition, or relationships with constraints. The methods are evaluated in terms of information loss during transformation, the need for human intervention, and versatility.

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Katedra softwarového inženýrství

Inheritance as a relation for expressing generalisations and specialisations or taxonomies is natural for conceptual modelling, but causes evolvability problems in software implementations. Each inheritance relation represents a tight coupling between a superclass and a subclass. Coupling in this case leads to a combinatorial effect or even combinatorial explosion in case of complex hierarchies. This paper analyses how multiple inheritance and method resolution order affect these problems in the Python programming language. The analysis is based on the design of inheritance implementation patterns from our previous work. Thanks to the flexibility of Python, it shows that inheritance can be implemented with minimisation of combinatorial effect using the patterns. Nevertheless, it is crucial to generate helper constructs related to the patterns from the model automatically for the sake of evolvability, including potential future in the patterns themselves.

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10.1007/978-3-030-65847-2_13

Katedra softwarového inženýrství

Powerful incentives are driving the adoption of FAIR practices among a broad cross-section of stakeholders. This adoption process must factor in numerous considerations regarding the use of both domain-specific and infrastructural resources. These considerations must be made for each of the FAIR Guiding Principles and include supra-domain objectives such as the maximum reuse of existing resources (i.e., minimised reinvention of the wheel) or maximum interoperation with existing FAIR data and services. Despite the complexity of this task, it is likely that the majority of the decisions will be repeated across communities and that communities can expedite their own FAIR adoption process by judiciously reusing the implementation choices already made by others. To leverage these redundancies and accelerate convergence onto widespread reuse of FAIR implementations, we have developed the concept of FAIR Implementation Profile (FIP) that captures the comprehensive set of implementation choicesmade at the discretion of individual communities of practice. The collection of community-specific FIPs compose an online resource called the FIP Convergence Matrix which can be used to track the evolving landscape of FAIR implementations and inform optimisation around reuse and interoperation. Ready-made and well-tested FIPs created by trusted communities will find widespread reuse among other communities and could vastly accelerate decision making on well-informed implementations of the FAIR Principles within and particularly between domains.

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10.1007/978-3-030-35646-0_1

Katedra softwarového inženýrství

Ontologies and conceptual modelling are very close areas in software engineering. This paper is focused on initial steps towards the integration of conceptual models by the foundation of Ontology for Conceptual Models Integration to capture the knowledge about various conceptual modelling languages, including process, event, and objectrole modelling. It is based on previous work in this area and has an ambitious goal to allow semantic integration of conceptual models made in different languages to cover more aspects and details of the problem domain. The presented contribution consists of the related work research, the initial ontology designed to be easily extensible, and related ideas for future work based on this foundation. We foresee this ontology to help also with using various conceptual models to create complete, consistent, and requisite software implementation in an automated way.

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Katedra softwarového inženýrství

Inheritance is a well-known construct in conceptual modelling, as well as in the object-oriented programming, where it is often used to enable reusability and to modularize complex applications. While it helps in conceptual modelling and understanding of complex domains, it usually results in evolvability issues in software implementations. This paper discusses problems caused by single and multiple inheritance with respect to increasing accidental complexity of a model and evaluates various patterns that can be used to transform conceptual-level inheritance into implementation with respect to code evolvability. The points are illustrated on the transformation of an example ontological conceptual model in OntoUML into various software implementation models.

Stať ve sborníku

10.1007/978-3-030-35646-0_4

Katedra softwarového inženýrství

Independent and preferably atomic services sending messages to each other are a significant approach of Separations of Concerns principle application. There are already standardised formats and protocols that enable easy implementation. In this paper, we go deeper and introduce evolvable and machine-actionable reports that can be sent between services. It is not just a way of encoding reports and composing them together; it allows linking semantics using technologies from semantic web and ontology engineering, mainly JSON-LD and Schema.org. We demonstrate our design on the Data Stewardship Wizard project where reports from evaluations are crucial functionality, but thanks to its versatility and extensibility, it can be used in any message-oriented software system or subsystem.

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10.1007/978-3-030-35646-0_7

Katedra softwarového inženýrství

Process modelling is the key part of a problem domain analysis, and there are multiple modelling languages for that purpose. In this paper, we present the mapping of three of such languages – namely BPMN, BORM, and UML Activity Diagram – with Unified Foundational Ontology UFO, more specifically its part describing behavioural aspects called UFO-B. Due to the mapping, we were able to find out interesting similarities and options when working with the selected languages and we also compare them in terms of expressiveness with respect to UFO. The specific properties of each languages became even more highlighted and explained, so this comparison can be used for a decision which language to use in a particular case. Our contribution can be used for future work in models integrations and transformations.

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.

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Katedra softwarového inženýrství

Every year, the amount of data (in science) grows significantly as information technologies are used more intensively in various domains of human activities. Biologists, chemists, linguists, and others are not data experts but often just regular users who need to capture and process some huge amount of data. This is where serious problems emerge – bad data management leading to losing important data, producing unverifiable results, wasting funds, and so on. Thousands of qualified data stewards will be needed in following years to deal with this issues. At the Faculty of Information Technology, CTU in Prague, we participate in the European platform ELIXIR in which we work on the Data Stewardship Wizard to help researchers and data stewards with building high-quality FAIR data management plans that are accurate and helpful to their projects. We cooperate on this challenging project with our colleagues from other ELIXIR nodes.

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Katedra softwarového inženýrství

We may say that documents are one of the cornerstones of our civilization. Information technologies enabled unparalleled flexibility and power for retrieving, storing, and sharing documents. However, in a daily documents-intensive job, one needs to deal with severe complications of documents evolvability and reusability of their parts. Maintaining consistency across several documents and their versions is typically a tedious and error-prone task. Similar evolvability challenges have been dealt with in software engineering and principles such as modularity, loose coupling, and separation of concerns have been studied and applied. There is a hypothesis that they may help in the domain of evolvable documents, as well. We perceive devising a conceptualization of documents as the first step in this endeavor. In this paper, we present a generic conceptualization leading to evolvable documents applicable in any documentation domain, and we propose next steps.

Článek

Katedra softwarového inženýrství

Documents surround us in our everyday lives and affect us even without noticing it. Information technology brought an evolution to documents in terms of flexibility and efficiency in their composing, processing, and sharing. However, in these days, an electronic document lacks the evolvability and reusability of its parts. Maintaining the consistency across one or even several documents and their versions makes it a very complicated task. We encounter a similar problem in the software development domain where, however, effective principles and techniques have been developed and adopted. Incorporating modularity, design patterns, loose coupling, separation of concerns, and other principles are being successfully applied to achieve evolvability. Results are proven in decades by scientific research and countless practical applications. Hypothetically, such principles may be used also for documents in order to achieve reliable and easy-to-maintain documents. This paper presents our generic conceptualization leading to evolvable documents and which is applicable in any documentation domain based on related work in the electronic documents, as well as the evolvable software development domains. Advantages and core ideas of our conceptualization are then demonstrated in a case study - prototype design of OntoUML modelling language documentation. Finally, possible next steps for generic evolvable documents are proposed, as we perceive our contribution as the first step in the journey towards evolvable documents in the scientific point of view. The results from this paper can be used for further research and as the first boilerplate for designing custom evolvable documentation.