Roman Lukyanenko

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• Information Systems
• Associate Professor at University of Virginia

Non-scientists are now participating in research in ways that were previously impossible, thanks to more web-based projects to collect and analyse data. Here we suggest a way to encourage broader participation while increasing the quality of data. Participation may be passive, as when someone donates their computer's 'downtime' to projects such as...

User-generated content (UGC) is becoming a valuable organizational resource, as it is seen in many cases as a way to make more information available for analysis. To make effective use of UGC, it is necessary to understand information quality (IQ) in this setting. Traditional IQ research focuses on corporate data and views users as data consumers....

As crowdsourced user-generated content becomes an important source of data for organizations, a pressing question is how to ensure that data contributed by ordinary people outside of traditional organizational boundaries is of suitable quality to be useful for both known and unanticipated purposes. This research examines the impact of different inf...

The role of information systems (IS) as representations of real-world systems is changing in an increasingly digitalized world, suggesting that conceptual modeling is losing its relevance to the IS field. We argue the opposite: Conceptual modeling research is more relevant to the IS field than ever, but it requires an update with current theory. We...

Conceptual modeling is an important part of information systems development and use that involves identifying and representing relevant aspects of reality. Although the past decades have experienced continuous digitalization of services and products that impact business and society, conceptual modeling efforts are still required to support new tech...

ER2025 Call for Papers 44th International Conference on Conceptual Modeling (ER 2025), 20-23 October 2025, Poitiers, France https://er2025.ensma.fr/ ER is the premier international conference for research and practice on Conceptual Modelling. The conference provides a vibrant forum for discussing and extending the state-of-the-art conceptual modeli...

Researchers must ensure that the claims about the knowledge produced by their work are valid. However, validity is neither well-understood nor consistently established in design science, which involves the development and evaluation of artifacts (models, methods, instantiations, and theories) to solve problems. As a result, it is challenging to dem...

Researchers must ensure that the claims about the knowledge produced by their work are valid. However, validity is neither well-understood nor consistently established in design science, which involves the development and evaluation of artifacts (models, methods, instantiations, and theories) to solve problems. As a result, it is challenging to dem...

The ever-increasing global demand for computational power has led to escalating energy consumption within the IT sector. Traditional data management approaches, reliant on classical computing infrastructures, struggle to keep pace with both the data explosion and the need for energy efficiency. Quantum computing, with its fundamentally different pr...

The continuing, explosive developments in generative artificial intelligence (GenAI), built on large language models and related algorithms, has led to much excitement and speculation about the potential impact of this new technology. Claims include artificial intelligence (AI) being poised to revolutionize business and society and dramatically cha...

The continuing, explosive developments in generative artificial intelligence (GenAI), built on large language models and related algorithms, has led to much excitement and speculation about the potential impact of this new technology. Claims include AI being poised to revolutionize business and society and dramatically change personal life. However...

L’ontologie générale constitue un fondement théorique important pour l’analyse, la conception et le développement dans les technologies de l’information. L’ontologie est une branche de la philosophie qui étudie ce qui existe dans la réalité. Une ontologie largement utilisée dans les systèmes d’information, en particulier pour la modélisation concep...

[EXTRAIT DU TROISIÈME NUMÉRO DE Mεtascience. TOUS LES ARTICLES ONT ÉTÉ RETIRÉS À L'EXCEPTION DE LA PRÉSENTATION. TOUS LES NUMÉROS SONT DISPONIBLES AUX ÉDITIONS MATÉRIOLOGIQUES: https://materiologiques.com/fr/27-mtascience-discours-general-scientifique]. Ce troisième numéro de la revue Mεtascience poursuit la caractérisation de cette nouvelle branch...

L'informatisation de la société se poursuit à un rythme effréné. Cependant, pour développer les technologies modernes de l'information, la complexité croissante du monde réel doit être modélisée, ce qui nécessite de revoir la façon de réaliser une modélisation conceptuelle. Cette étude propose que la notion souvent négligée de « système » doive êtr...

The continuing, explosive developments in generative artificial intelligence (GenAI), built on large language models and related algorithms, has led to much excitement and speculation about the potential impact of this new technology. Claims include artificial intelligence (AI) being poised to revolutionize business and society and dramatically cha...

The psychometric approach in IS offers a foundational framework for a broad spectrum of research endeavors, typically relying on construct validation to confirm that a series of indicators accurately measures the intended construct. However, a longstanding issue with construct validity, unaddressed since its introduction by Cronbach and Meehl in 19...

One novel direction for conceptual modeling would be to consider an ontology of fields. While this ontology has been recognized in modern philosophy, it has not found its footing in conceptual modeling yet. In consideration of this potential opportunity, we describe aspects of the ontology of fields in order to consider it as a new foundational bas...

The paper proposes universal conceptual modeling, conceptual modeling that strives to be as general-purpose as possible and accessible to anyone, professionals and non-experts alike. The idea of universal conceptual modeling is meant to catalyze new thinking in conceptual modeling and be used to evaluate and develop conceptual modeling solutions, s...

In an era dominated by information technology, the critical discipline of data management remains undervalued compared to the innovations it enables, such as artificial intelligence and social media. The ambiguity surrounding what constitutes data management and its associated activities complicates efforts to explain its importance and ensure data...

In an era dominated by information technology, the critical discipline of data management remains undervalued compared to the innovations it enables, such as artificial intelligence and social media. The ambiguity surrounding what constitutes data management and its associated activities complicates efforts to explain its importance and ensure data...

The digitalization of human society continues at a relentless rate. However, to develop modern information technologies, the increasing complexity of the real-world must be modeled, suggesting the general need to reconsider how to carry out conceptual modeling. This research proposes that the often-overlooked notion of ‘‘system’’ should be a separa...

[[ COMPLETE THIRD ISSUE OF METASCIENCE ]] This third issue of the journal Mεtascience continues the charac- terization of this new branch of knowledge that is metascience. If it is new, it is not in a radical sense since Mario Bunge practiced it in an exemplary way, since logical positivists were accused of prac- ticing only a mere metascience, s...

Agile Development has been an integral part of project management and product development since its formal introduction by the Agile Manifesto in 2001. Subsequently, Agile has rapidly gained in popularity, leading to significant improvements in on-time delivery and managing costs, as well as successful delivery of the required scope for information...

Research transparency promotes openness and trust in the process, evidence, contributions, and implications of scientific inquiry. Information Systems (IS), as a pluralistic research community, must address transparency in relation to its use of multiple research methods appropriate to complex socio-technical contexts and challenging research quest...

This paper examines the impact of training on bias in crowdsourced data for machine learning. It finds that less training results in less biased data, with untrained contributors providing the most unbiased and highest quality data for machine learning models. The study highlights the importance of minimizing training to gather more representative,...

The growing global demand for computational power has driven a sharp rise in energy consumption within the IT sector. Conventional data management, dependent on classical computing infrastructure, faces challenges in keeping up with both the rapid expansion of data and the increasing need for energy efficiency. Quantum computing, with its fundament...

Citizen science projects that collect natural history observations often do not have an underlying research question in mind. Thus, data generated from such projects can be considered "use-agnostic." Nevertheless, such projects can yield important insights about species distributions. Many of these projects use a class-based data schema, whereby co...

Research transparency promotes openness and trust in the performed process, produced evidence, claimed contributions, and actionable implications of scientific inquiry. The field of information systems (IS), as a pluralistic research community, must address transparency in relation to its use of multiple research methods appropriate to complex soci...

Online citizen science has emerged as a popular way to engage volunteers in various aspects of scientific research. A significant benefit of citizen science is the ability to facilitate discoveries, particularly through the participation of ordinary people who can detect anomalies and think outside the box. However, the theoretical and design knowl...

We propose a vision for inclusive conceptual modeling. The urgency to address inclusiveness comes from two converging trends: the deepening reliance on information technology; and broader engagement of the members of the public in IT development and use, including conceptual modeling. In this paper, we propose inclusive conceptual modeling as a cri...

This paper presents the architecture of a universal conceptual data modeling language, Datish, with the aim of enabling anyone to model anything. Although there are many conceptual modeling languages, there was no language that could model a wide range of domains and at the same time be used by diverse audiences, including the general public. In th...

With the proliferation of collaborative and mobile technologies, online citizen science has become a booming approach to research and public engagement. Citizen science refers to various forms of engaging non-credentialed volunteers (citizens) in different aspects of scientific research, such as data collection, analysis and, more rarely, developme...

The traditionally applied approach to determine the boundaries of poverty and the middle class based predominantly on the criteria of income level overlooks a wide group of citizens related to low-income category. The paper examines multicriteria approaches in determining the boundaries of poverty and the middle class which cover social, economic a...

The paper proposes a new frontier for conceptual modeling-universal conceptual modeling (UCM)-defined as conceptual modeling that is general-purpose and accessible to anyone. For the purposes of the discussion, we envision a non-existent, hypothetical universal conceptual modeling language, which we call Datish (as in English or Spanish for data)....

Background All aspects of our society, including the life sciences, need a mechanism for people working within them to represent the concepts they employ to carry out their research. For the information systems being designed and developed to support researchers and scientists in conducting their work, conceptual models of the relevant domains are...

The paper proposes a new frontier for conceptual modeling – universal conceptual modeling (UCM) – defined as conceptual modeling that is general-purpose and accessible to anyone. For the purposes of the discussion, we envision a non-existent, hypothetical universal conceptual modeling language, which we call Datish (as in English or Spanish for dat...

This paper proposes a Conceptual Alignment (CA) Method for conceptual modeling and machine learning. The model consists of a three-step cycle that selects an initial conceptual model, aligns it with machine learning models, and refines both models to reach predictive consistency. Alignment is based on composition methods that can be instantiated by...

These are supplementary materials for the paper, “Conceptual Modeling: Topics, Themes, and Technology Trends.” Conceptual modeling is an important part of information systems development and use that involves identifying and representing relevant aspects of reality. Although the past decades have experienced continuous digitalization of services an...

We propose a universal conceptual data modeling language, Datish. A universal conceptual modeling language can address some of the challenges faced by modern data modeling. Conceptual data modeling seeks to represent the domain's substance and form, identifying the kinds of data to be collected, stored, or used, and have been effective in supportin...

With the rise of artificial intelligence (AI), the issue of trust in AI emerges as a paramount societal concern. Despite increased attention of researchers, the topic remains fragmented without a common conceptual and theoretical foundation. To facilitate systematic research on this topic, we develop a Foundational Trust Framework to provide a conc...

The article explores multicriterial approaches to determine the boundaries of poverty and the middle class. Applied regression analysis confirms the significance of some households’ social and economic characteristics that increase the likelihood of their belonging to a certain population group. Based on various methodological approaches, the analy...

Conceptual modeling is often applied to real-world tasks to capture and integrate individual requirements from domain and technical experts for the development of an information system. Increasingly, information systems integrate machine learning models for providing predictive functionalities. Since complex machine learning models are considered a...

Although conceptual modeling has been integral to information systems development and use, much of its potential remains underutilized. This is evidenced by the lack of a broad adoption of modeling concepts beyond traditional database design and process modeling applications. In this paper, we propose a fundamentally new perspective on conceptual m...

As COVID-19 continues to wreak havoc in everyday lives, the need to limit the spread of the virus remains a challenge, even with advances in medical knowledge, patient care, and vaccine development. Furthermore, COVID-19 is one in a recent series of airborne diseases, and probably not the last, given the ongoing encroachment of humans into animal h...

Elevator Pitch A quiet revolution is happening in the offices, cubicles, and boardrooms of the world. Non-IT professionals are becoming empowered by leveraging organizational data for analytics. We support this movement by offering a powerful way to make data more usable via a combination of graphical conceptual models with narratives. Longer Versi...

The digitalization of human society continues at a relentless rate. However, to develop modern information technologies, the increasing complexity of the real-world must be modeled, suggesting the general need to reconsider how to carry out conceptual modeling. This research proposes that the often-overlooked notion of "system" should be a separate...

As COVID-19 continues to create havoc in everyday lives, the need to limit the spread of the virus remains a challenge, even with advances in medical knowledge and patient care, and the promise of a vaccine. Furthermore, COVID-19 is one in a recent series of airborne diseases, and probably not the last one, given the ongoing encroachment of humans...

General ontology is a prominent theoretical foundation for information technology analysis, design, and development. Ontology is a branch of philosophy which studies what exists in reality. A widely used ontology in information systems , especially for conceptual modeling, is the BWW (Bunge-Wand-Weber), which is based on ideas of the philosopher an...

[[COMPLETE SECONDE ISSUE OF METASCIENCE]] This second issue of the journal Mεtascience continues the char- acterization of this new branch of knowledge that is metasci- ence. If it is new, it is not in a radical sense since Mario Bunge practiced it in an exemplary way, since logical positivists were accused of practicing only a mere metascience, s...

[[EXTRAITS DU SECOND NUMÉRO DE METASCIENCE DISPONIBLE AUX ÉDITIONS MATÉRIOLOGIQUES: https://materiologiques.com/fr/27-mtascience-discours-general-scientifique]] Ce deuxième numéro de la revue Mεtascience poursuit la caractéri- sation de cette nouvelle branche du savoir qu’est la métascience. Si elle est nouvelle ce n’est pas en un sens radical pu...

As digitalized products and services have become more pervasive and complex, the need grows to better facilitate their design, use, and management. This presupposes a deeper understanding of the nature of digital technologies. The paper develops a new ontology-a Realist Ontology of Digital Objects and Digitalized Systems. It is based on Bunge's rig...

Artificial intelligence (AI) is beginning to transform traditional research practices in many areas. In this context, literature reviews stand out because they operate on large and rapidly growing volumes of documents, that is, partially structured (meta)data, and pervade almost every type of paper published in information systems research or relat...

Digitizing activities and processes of business and society has resulted in explosive growth and availability of data. Machine learning provides methods for detecting patterns in datasets to predict outcomes and support decisions. However, many forms of machine learning are considered black boxes because the internal logic is often opaque. Given th...

Many artificial intelligence (AI) applications involve the use of machine learning, which continues to evolve and address more and more complex tasks. At the same time, conceptual modeling is often applied to such real-world tasks so they can be abstracted at the right level of detail to capture and represent the requirements for the development of...

In our modern, digital world, the critical role of information technology makes data management an important research topic. This paper curates data management research at MIS Quarterly as it has progressed from its early context of understanding requirements of relatively simple information systems to the sophisticated and complex systems of today...

A poem which reflects on the priorities (related to my own research) of our times.

In the year 2021 we asked students at a top business school in North America to imagine and draw a device of the future in the 2050. They only had a short time to draw it, but the results are quite interesting. What did they draw and imagine? Will their predictions come true? What do you think will happen in 2050? If you are intrigued by these ques...

Many organizations rely on machine learning techniques to extract useful information from large collections of data. Much research in this area has focused on developing and applying machine learning techniques. We propose that using conceptual models can improve machine learning by providing needed domain knowledge to augment training data with do...

The ER 2021 Demos and Posters track was part of the 40th International Conference on Conceptual Modeling (ER 2021) . The track aims to serve as a platform for presenting and discussing novel research ideas, addressing any ER conference topics, and new emerging topics related to conceptual modeling. We received 14 submissions, each of which was assi...

The understanding of life has always been is a challenge of Life Science. Modeling life implies the need to describe the required details of the systemic structure associated with the working mechanisms of life. In this research, we propose that conceptual modeling can play a crucial role in the modeling of life. Specifically, we introduce the noti...

The understanding of life has always been is a challenge of Life Science. Modeling life implies the need to describe the required details of the sys-temic structure associated with the working mechanisms of life. In this research, we propose that conceptual modeling can play a crucial role in the modeling of life. Specifically, we introduce the not...

Behavioral and design science research are two of the major paradigms of information systems. The two paradigms are commonly seen as complementary and distinct, differing in philosophical underpinnings, prevailing methodology and expected outputs of research. Presently, behavioral and design science communities seldomly interact and conduct project...

Artificial Intelligence is increasingly driven by powerful but often opaque machine learning algorithms. These black-box algorithms achieve high performance but are not explainable to humans in a systematic and interpretable manner, a challenge known as Explainable AI (XAI). Informed by a synthesis of two converging literature streams on informatio...

Although much research continues to be carried out on modeling of information systems, there has been a lack of work that relates the activities of modeling to human mental models. With the increased emphasis on machine learning systems, model development remains an important issue. In this research, we propose a framework for progressing from huma...

Although much research continues to be carried out on modeling of infor-mation systems, there has been a lack of work that relates the activities of modeling to human mental models. With the increased emphasis on machine learning systems, model development remains an important issue. In this re-search, we propose a framework for progressing from hu...

In an increasingly digital world, conceptual modeling research is more relevant than ever to the information systems field, but it requires an update with current theory. In [Re21] we develop a new theoretical framework of conceptual modeling to change the assumptions that govern research in this area. Our framework draws attention to the role of c...

L’ontologie générale constitue un fondement théorique important pour l’analyse, la conception et le développement dans les technologies de l’informa-tion. L’ontologie est une branche de la philosophie qui étudie ce qui existe dans la réalité. Une ontologie largement utilisée dans les systèmes d’information, en par-ticulier pour la modélisation conc...

Two Robots Explain our MISQ paper in a Youtube video: https://youtu.be/MfuCgSADeWA The paper: https://www.researchgate.net/publication/344123600_From_Representation_to_Mediation_A_New_Agenda_for_Conceptual_Modeling_Research_in_A_Digital_World

Advances in machine learning (ML) make it possible to extract useful information from large and diverse datasets. ML methods aim to identify patterns in a dataset based on the values of features and their combinations. Recent research has proposed combining conceptual modeling, specifically data models, with artificial intelligence. In this paper,...

General ontology is a prominent theoretical foundation for information technology analysis, design, and development. Ontol-ogy is a branch of philosophy which studies what exists in reality. A widely used ontology in information systems, especially for conceptual modeling, is the BWW (Bunge-Wand-Weber), which is based on ideas of the philosopher an...

Machine learning has become almost synonymous with Artificial Intelligence (AI). However, it has many challenges with one of the most important being explainable AI; that is, providing human-understandable accounts of why a machine learning model produces specific outputs. To address this challenge, we propose superimposition as a concept which use...

We live in an era defined by the explosion of artificial intelligence-AI. Commonly understood as a study and practice of making machines perform tasks typically associated with humans (e.g., problem solving, categorization, decision making, natural language processing), artificial intelligence utilizes such techniques as machine learning (wherein m...

Organizations and individuals who use crowdsourcing to collect data prefer knowledgeable contributors. They train recruited contributors, expecting them to provide better quality data than untrained contributors. However, selective attention theory suggests that, as people learn the characteristics of a thing, they focus on only those characteristi...

Research in design science has always acknowledged the need for evaluating its knowledge outcomes, with particular emphasis on assessing the efficacy and utility of the artifacts produced. However, the need to demonstrate the validity of the research process and outcomes has not received as much attention. This research examines scientific approach...

An important function of any information system is to represent an application domain. A general or foundational ontology provides a basis from which research on representational issues can be conducted. However, most efforts that develop general ontologies, have not taken a systems view. In this paper , we propose a General Systemist Ontology (GSO...

Crowdsourcing is an efficient way to engage the general public in making contributions to the production of goods and services. Studies have shown that observational crowdsourcing, as a continuous activity, has many potential benefits to society. However, a major challenge is how to model a crowdsourced activity. In this research, we provide guidel...

Machine learning has become almost synonymous with Artificial Intelligence (AI). However, it has many challenges with one of the most important being explainable AI; that is, providing human-understandable accounts of why a machine learning model produces specific outputs. To address this challenge, we propose superimposition as a concept which use...

Crowdsourcing promises to expand organizational knowledge and “sensor” networks dramatically, making it possible to engage ordinary people in large-scale data collection, often at much lower cost than that of traditional approaches to gathering data. A major challenge in crowdsourcing is ensuring that the data that crowds provide is of sufficient q...

Herein, we report the synthesis of substituted morpholino nucleoside derivatives starting from ribonucleosides. The present protocol shows high functional group tolerance, uses mild reaction conditions, and gives moderate to good yields. This transformation is based on two sequential pathways: (i) the oxidation of the ribonucleosides to the corresp...

The rapid proliferation of online content producing and sharing technologies resulted in an explosion of user-generated content (UGC), which now extends to scientific data. Citizen science, in which ordinary people contribute information for scientific research, epitomizes UGC. Citizen science projects are typically open to everyone, engage diverse...

Since the 1970s, many approaches to representing domains have been suggested. Each approach maintains the assumption that the information about the objects represented in the information system (IS) is specified and verified by domain experts and potential users. Yet, as more IS are developed to support a larger diversity of users such as customers...

Crowdsourcing promises to expand organizational knowledge and "sen-1 sor" networks dramatically, making it possible to engage ordinary people in large-2 scale data collection, often at much lower cost than that of traditional approaches 3 to gathering data. A major challenge in crowdsourcing is ensuring that the data that 4 crowds provide is of suf...

Research in design science has always acknowledged the need for evaluating its knowledge outcomes, with particular emphasis on assessing the efficacy and utility of the artifacts produced. However, the need to demonstrate the validity of the research process and outcomes has not received as much attention. This research examines scientific approach...

A prominent theoretical foundation for IT analysis, design and development is general ontology-a branch of philosophy which studies what exists in reality. A widely used general ontology is BWW (Bunge-Wand-Weber)-based on ideas of the philosopher and physicist Mario Bunge, synthesized by Wand and Weber. It is regarded as a major contribution to con...

Users of crowdsourced data expect that knowledge of the domain of a data crowdsourcing task will positively affect the data that their contributors provide, so they train potential participants on the crowdsourcing task to be performed. We carried out an experiment to test how training affects data quality and data repurposability – the capacity fo...

This study investigates the legitimation strategies adopted by information technology (IT) vendors and their respective influence on market share. We conducted an analysis of the public discourse on websites of top Electronic Medical Record (EMR) vendors in Ontario, Canada. A total of 815 segments extracted from these websites were analyzed. Our fi...

Design science research strives to be practical and relevant. Yet few have examined the extent to which practitioners can meaningfully utilize theoretical knowledge produced by design science researchers in solving concrete real-world problems. Are design theories developed by scientists readily amenable to application by practitioners? Does the ap...

Since 1970s many approaches of representing domains have been suggested. Each approach maintains the assumption that the information about the objects represented in the Information System (IS) is specified and verified by domain experts and potential users. Yet, as more IS are developed to support a larger diversity of users such as customers, sup...

The growth of online communities has resulted in an increased availability of user-generated content (UGC). Given the varied sources of UGC, the quality of information it provides is a growing challenge. While many aspects of UGC have been studied, the role of data structures in gathering UGC and nature of to-be-shared content has yet to receive at...

The on-going proliferation of online content producing and sharing technologies creates new opportunities for governments, public agencies and scientists to engage citizens in data collection, analysis, sense making, and public dialogue known as citizen science. A review of citizen science platforms indicates that despite growing popularity of citi...

An important element of rigor in the information systems (IS) discipline are research validities. Broadly, validity deals with the quality of scientific research and dependability of scientific findings. Research validities provide procedural templates to collect and analyze evidence and justify the arguments and conclusions of a research study. Th...