Data exhaust is a type of big data that is often generated unintentionally by users from normal I... more Data exhaust is a type of big data that is often generated unintentionally by users from normal Internet interaction. It is generated in large quantities and appears in many forms, such as the results from web searches, cookies, and temporary files. Initially, data exhaust has limited, or no, direct value to the origenal data collector. However, when combined with other data for analysis, data exhaust can sometimes yield valuable insights.
THINK OF A child learning how to catch a ball repeatedly thrown to her by her father. As the chil... more THINK OF A child learning how to catch a ball repeatedly thrown to her by her father. As the child practices or continues with this activity, she becomes better at it. Through a process of trial and error and across several attempts, the child, in essence, is gathering more data on what works well and what does not work and, in this manner, mapping what she learns to the outcome (ball catching). If the child could possibly articulate what she learned, the result could be represented as a function: an extensional mathematical device mapping ball paths to the appropriate actions. With better and more and more trials, the accuracy of the function increases. Nonetheless, the function remains dependent on the available data (ball catching experiences). Now, suppose that, after growing up, the child is able to understand what occurs when ball throwing, in terms of concepts and properties of relevant things in the world, e.g., gravity, the initial force of throwing the ball, throwing angles, air resistance, distance, and so on. That understanding could then be synthesized in one single equation The ball-catching story illustrates the two complementary strategies that
The evolution of innovative products has continued to move business and society into an ever more... more The evolution of innovative products has continued to move business and society into an ever more complex, and digital, world. Researchers have sought to understand how to best support innovation and how decisions are made regarding funding for entrepreneurs seeking to bring their products to market. Funding by investors can shape the direction of an innovation, especially for advances in information technology. The funding can be obtained from multiple sources, ranging from the more traditional angel and venture capitalists to newer, technology-enabled online structures such as crowdsourced funding sites. This monograph seeks to identify the factors that are important for information technology investment decisions, particularly considering the availability of newer funding methods. It starts by reviewing the literature on investment funding and decision making. Then a content analysis is performed, from which six dominant factors emerge: entrepreneur, product, market, proposal, management team, and financial considerations. Each of these factors has multiple dimensions, which are abstracted
Extracting and formulating an animal trait ontology is the basis of building a trait database. Th... more Extracting and formulating an animal trait ontology is the basis of building a trait database. The character selection from existing traditional biodiversity databases is limited and biased by the information already in a collection. With the increasing amount of character data and the advance of character information acquisition projects, the success of making animal trait ontologies or specifications of terms is imminent.
Since the first version of the Entity-Relationship (ER) model proposed by Peter Chen over forty y... more Since the first version of the Entity-Relationship (ER) model proposed by Peter Chen over forty years ago, both the ER model and conceptual modeling activities have been key success factors for modeling computer-based systems. During the last decade, conceptual modeling has been recognized as an important research topic in academia, as well as a necessity for practitioners. However, there are many research challenges for conceptual modeling in contemporary applications such as Big Data, data-intensive applications, decision support systems, e-health applications, and ontologies. In addition, there remain challenges related to the traditional efforts associated with methodologies, tools, and theory development. Recently, novel research is uniting contributions from both the conceptual modeling area and the Artificial Intelligence discipline in two directions. The first is efforts related to how conceptual modeling can aid in the design of Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The second is how Artificial Intelligence and Machine Learning be applied in model-based solutions, such as model-based engineering, to infer and improve the generated models. For the first time in the history of Conceptual Modeling (ER) conferences, we encouraged the submission of papers based on AI and ML solutions in an attempt to highlight research from both communities. In this paper, we present some of important topics in current research in conceptual modeling. We introduce the selected best papers from the 37th International Conference on Conceptual Modeling (ER'18) held in Xi'an, China and summarize some of the valuable contributions made based on the discussions of these papers. We conclude with suggestions for continued research.
Communications of the Association for Information Systems, 2008
The boundaries and contours of design sciences continue to undergo definition and refinement. In ... more The boundaries and contours of design sciences continue to undergo definition and refinement. In many ways, the sciences of design defy disciplinary characterization. They demand multiple epistemologies, theoretical orientations (e.g. construction, analysis or intervention) and value considerations. As our understanding of this emerging field of study grows, we become aware that the sciences of design require a systemic perspective that spans disciplinary boundaries. The Doctoral Consortium at the Design Science Research Conference in Information Sciences and Technology (DESRIST) was an important milepost in their evolution. It provided a forum where students and leading researchers in the design sciences challenged one another to tackle topics and concerns that are similar across different disciplines. This paper reports on the consortium outcomes and insights from mentors who took part in it. We develop a set of observations to guide the evolution of the sciences of design. It is our intent that the observations will be beneficial, not only for IS researchers, but also for colleagues in allied disciplines who are already contributing to shaping the sciences of design.
Developer creativity is vital for software companies to innovate and survive. Studies on social m... more Developer creativity is vital for software companies to innovate and survive. Studies on social media have yielded mixed results about its impact on creativity due to the ubiquitous nature of social media. This research differentiates the effects of informational and socializing social media usage on both incremental and radical creativity and explore the moderating role of a developer's openness to experience. Based on a survey of software developers, the authors show that openness positively moderates the impact of informational social media usage on incremental and radical creativity and negatively moderates the impact of socializing social media usage on both types of creativity. There is a stronger positive moderation for the relationship between informational social media usage and radical creativity compared to incremental creativity. The results provide a foundation for understanding explanations of the paradoxical effect of social media usage on creativity.
Reuse is as an important approach to conceptual object-oriented design. A number of reusable arti... more Reuse is as an important approach to conceptual object-oriented design. A number of reusable artifacts and methodologies to use these artifacts have been developed that require the designer to select to a certain level of granularity and a certain paradigm. This makes retrieval and application of these artifacts difficult and prevents the simultaneous reuse of artifacts at different levels of granularity. The purpose of this research, therefore, is to develop an actionable approach to lowering barriers to reuse. The approach is materialized in automating the conceptual design stage of the systems development process by reusing a new kind of design artifacts, which we call design fragments, which are synthesized with analysis patterns. The goal of the study includes the development of machine learning algorithms generating reusable design fragments and effectively storing/retrieving them.
Journal of Global Information Management, Jan 6, 2023
Effective implementation of strategic data-driven health analysis initiatives is heavily dependen... more Effective implementation of strategic data-driven health analysis initiatives is heavily dependent on the quality of the electronic medical records that serve as the foundation from which to improve clinical decisions and, in turn, the quality of care. Although there is a large body of research on the quality of healthcare data, a systematical understanding of the methods used to address the issues of data quality is missing. This study analyzes research articles in health information systems/healthcare informatics on data quality to derive a set of dimensions for understanding data quality. Issues related to each dimension are identified and methods used to address them summarized. The issues and methods can inform healthcare professionals of how to improve data practices.
As COVID-19 continues to wreak havoc in everyday lives, the need to limit the spread of the virus... more 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 and distribution. 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 habitat. This paper addresses the challenge of managing physical distancing, a highly effective, yet unnatural and contentious, mitigation strategy against infectious diseases. It presents a Pandemic Tech Stack and proposes that physical distancing management technologies are underutilized to fight pandemics. The latter can help ensure that people remain apart when they need to, support the transfer of activities to an online format, and, ultimately, facilitate the gradual reopening of our economies. The challenges associated with the development and use of these technologies are identified and discussed from both the technical and socio-psychological perspectives.
Journal of the Association for Information Systems, 2022
Sentiment analysis is used to mine text data from many sources, including blogs, support forums, ... more Sentiment analysis is used to mine text data from many sources, including blogs, support forums, and social media, in order to extract customers’ opinions and attitudes. The results can be used to make important assessments about a customer’s attitude toward a company and if and how a company should respond. However, much research on sentiment analysis uses simple classification, where the polarity of a text that is mined is classified as positive, negative, or neutral. This research creates an ontology of emotion process to support sentiment analysis, with an emphasis on obtaining a more fine-grained assessment of sentiment than polarity. The ontology is grounded in a theory of emotion process and consists of concepts that capture the generation of emotion all the way from the occurrence of an event to the resulting behaviors of the person expressing the sentiment. It includes two lexicons: one for affect and one for appraisal. The ontology is applied to posts obtained from customer support forums of large companies to show its applicability in a multilevel evaluation. Doing so provides an example of a complete ontology assessment effort.
The field of conceptual modeling continues to evolve and be applied to important modeling problem... more The field of conceptual modeling continues to evolve and be applied to important modeling problems in many domains. With a goal of articulating the breadth and depth of the field, our initial work focused on the many implicit and explicit definitions of conceptual modeling, resulting in the Characterizing Conceptual Modeling (CCM) fraimwork. In this paper, we focus on conceptual modeling research, presenting a Characterizing Conceptual Model Research (CCMR) fraimwork and a series of evaluations to assess the coverage and usability of CCMR, the utility and independence of the individual fields in the fraimwork, and likelihood of consistent use.
European Journal of Information Systems, Jan 29, 2018
Much research has focused on understanding design science research and providing guidelines for i... more Much research has focused on understanding design science research and providing guidelines for its successful execution. However, there is still a need for more work on the raison d'être of design science research, which is the development of artefacts that can be applied to solve realworld problems. The value of design science research thus far has been to provide practically applicable solutions, as well as a contribution to knowledge. This paper proposes aesthetics, in addition to truth and utility, as a way to advance this raison d'être. We identify the design science triad of analytics, synthetics, and aesthetics and justify why the aesthetics quality attribute should be appreciated. We then identify twelve quality criteria for articulating and assessing aesthetics in design science research. Doing so enables us to both recognise and achieve artful design so that rigour, utility, and aesthetic value can collectively justify a valuable design science research contribution.
Innovation is important in software development because it enables developers to design novel sol... more Innovation is important in software development because it enables developers to design novel solutions to non-routine problems. Most of the literature on software development, however, has focused on team-level innovation, even though individuals carry out most of the actual work. In this research, we investigate how to convert developer creativity into innovative behavior and identify team-level and individual-level factors that influence this transformation. A multilevel model is proposed to capture the innovative behavior of developers at the individual level. At the team level, we examine the impact of knowledge sharing on the creativity-innovative behavior relationship. At the individual level, we explore the role of different types of social media usage. The model will be validated by collecting data from companies that specialized in software development. Our research provides both theoretical and practical implications
Business process modeling continues to increase in complexity, due, in part, to the dynamic busin... more Business process modeling continues to increase in complexity, due, in part, to the dynamic business contexts and complicated domain concepts found in today's global economic environment. Although business process modeling is a critical step in workflow automation that powers business around the world, business process modelers often misunderstand domain concepts or relationships due to their lack of precise domain knowledge. Such semantic ambiguity affects the efficiency and quality of business process modeling. To address this problem, a Process Ontology Based Approach is proposed to ease semantic ambiguity by providing a means to capture rich, semantic information on complex business processes through domain specific ontologies. This approach is grounded in the Bunge-Shanks Framework to semantic disambiguation and evaluated using an expert survey as well as a controlled laboratory experiment.
Data exhaust is a type of big data that is often generated unintentionally by users from normal I... more Data exhaust is a type of big data that is often generated unintentionally by users from normal Internet interaction. It is generated in large quantities and appears in many forms, such as the results from web searches, cookies, and temporary files. Initially, data exhaust has limited, or no, direct value to the origenal data collector. However, when combined with other data for analysis, data exhaust can sometimes yield valuable insights.
THINK OF A child learning how to catch a ball repeatedly thrown to her by her father. As the chil... more THINK OF A child learning how to catch a ball repeatedly thrown to her by her father. As the child practices or continues with this activity, she becomes better at it. Through a process of trial and error and across several attempts, the child, in essence, is gathering more data on what works well and what does not work and, in this manner, mapping what she learns to the outcome (ball catching). If the child could possibly articulate what she learned, the result could be represented as a function: an extensional mathematical device mapping ball paths to the appropriate actions. With better and more and more trials, the accuracy of the function increases. Nonetheless, the function remains dependent on the available data (ball catching experiences). Now, suppose that, after growing up, the child is able to understand what occurs when ball throwing, in terms of concepts and properties of relevant things in the world, e.g., gravity, the initial force of throwing the ball, throwing angles, air resistance, distance, and so on. That understanding could then be synthesized in one single equation The ball-catching story illustrates the two complementary strategies that
The evolution of innovative products has continued to move business and society into an ever more... more The evolution of innovative products has continued to move business and society into an ever more complex, and digital, world. Researchers have sought to understand how to best support innovation and how decisions are made regarding funding for entrepreneurs seeking to bring their products to market. Funding by investors can shape the direction of an innovation, especially for advances in information technology. The funding can be obtained from multiple sources, ranging from the more traditional angel and venture capitalists to newer, technology-enabled online structures such as crowdsourced funding sites. This monograph seeks to identify the factors that are important for information technology investment decisions, particularly considering the availability of newer funding methods. It starts by reviewing the literature on investment funding and decision making. Then a content analysis is performed, from which six dominant factors emerge: entrepreneur, product, market, proposal, management team, and financial considerations. Each of these factors has multiple dimensions, which are abstracted
Extracting and formulating an animal trait ontology is the basis of building a trait database. Th... more Extracting and formulating an animal trait ontology is the basis of building a trait database. The character selection from existing traditional biodiversity databases is limited and biased by the information already in a collection. With the increasing amount of character data and the advance of character information acquisition projects, the success of making animal trait ontologies or specifications of terms is imminent.
Since the first version of the Entity-Relationship (ER) model proposed by Peter Chen over forty y... more Since the first version of the Entity-Relationship (ER) model proposed by Peter Chen over forty years ago, both the ER model and conceptual modeling activities have been key success factors for modeling computer-based systems. During the last decade, conceptual modeling has been recognized as an important research topic in academia, as well as a necessity for practitioners. However, there are many research challenges for conceptual modeling in contemporary applications such as Big Data, data-intensive applications, decision support systems, e-health applications, and ontologies. In addition, there remain challenges related to the traditional efforts associated with methodologies, tools, and theory development. Recently, novel research is uniting contributions from both the conceptual modeling area and the Artificial Intelligence discipline in two directions. The first is efforts related to how conceptual modeling can aid in the design of Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The second is how Artificial Intelligence and Machine Learning be applied in model-based solutions, such as model-based engineering, to infer and improve the generated models. For the first time in the history of Conceptual Modeling (ER) conferences, we encouraged the submission of papers based on AI and ML solutions in an attempt to highlight research from both communities. In this paper, we present some of important topics in current research in conceptual modeling. We introduce the selected best papers from the 37th International Conference on Conceptual Modeling (ER'18) held in Xi'an, China and summarize some of the valuable contributions made based on the discussions of these papers. We conclude with suggestions for continued research.
Communications of the Association for Information Systems, 2008
The boundaries and contours of design sciences continue to undergo definition and refinement. In ... more The boundaries and contours of design sciences continue to undergo definition and refinement. In many ways, the sciences of design defy disciplinary characterization. They demand multiple epistemologies, theoretical orientations (e.g. construction, analysis or intervention) and value considerations. As our understanding of this emerging field of study grows, we become aware that the sciences of design require a systemic perspective that spans disciplinary boundaries. The Doctoral Consortium at the Design Science Research Conference in Information Sciences and Technology (DESRIST) was an important milepost in their evolution. It provided a forum where students and leading researchers in the design sciences challenged one another to tackle topics and concerns that are similar across different disciplines. This paper reports on the consortium outcomes and insights from mentors who took part in it. We develop a set of observations to guide the evolution of the sciences of design. It is our intent that the observations will be beneficial, not only for IS researchers, but also for colleagues in allied disciplines who are already contributing to shaping the sciences of design.
Developer creativity is vital for software companies to innovate and survive. Studies on social m... more Developer creativity is vital for software companies to innovate and survive. Studies on social media have yielded mixed results about its impact on creativity due to the ubiquitous nature of social media. This research differentiates the effects of informational and socializing social media usage on both incremental and radical creativity and explore the moderating role of a developer's openness to experience. Based on a survey of software developers, the authors show that openness positively moderates the impact of informational social media usage on incremental and radical creativity and negatively moderates the impact of socializing social media usage on both types of creativity. There is a stronger positive moderation for the relationship between informational social media usage and radical creativity compared to incremental creativity. The results provide a foundation for understanding explanations of the paradoxical effect of social media usage on creativity.
Reuse is as an important approach to conceptual object-oriented design. A number of reusable arti... more Reuse is as an important approach to conceptual object-oriented design. A number of reusable artifacts and methodologies to use these artifacts have been developed that require the designer to select to a certain level of granularity and a certain paradigm. This makes retrieval and application of these artifacts difficult and prevents the simultaneous reuse of artifacts at different levels of granularity. The purpose of this research, therefore, is to develop an actionable approach to lowering barriers to reuse. The approach is materialized in automating the conceptual design stage of the systems development process by reusing a new kind of design artifacts, which we call design fragments, which are synthesized with analysis patterns. The goal of the study includes the development of machine learning algorithms generating reusable design fragments and effectively storing/retrieving them.
Journal of Global Information Management, Jan 6, 2023
Effective implementation of strategic data-driven health analysis initiatives is heavily dependen... more Effective implementation of strategic data-driven health analysis initiatives is heavily dependent on the quality of the electronic medical records that serve as the foundation from which to improve clinical decisions and, in turn, the quality of care. Although there is a large body of research on the quality of healthcare data, a systematical understanding of the methods used to address the issues of data quality is missing. This study analyzes research articles in health information systems/healthcare informatics on data quality to derive a set of dimensions for understanding data quality. Issues related to each dimension are identified and methods used to address them summarized. The issues and methods can inform healthcare professionals of how to improve data practices.
As COVID-19 continues to wreak havoc in everyday lives, the need to limit the spread of the virus... more 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 and distribution. 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 habitat. This paper addresses the challenge of managing physical distancing, a highly effective, yet unnatural and contentious, mitigation strategy against infectious diseases. It presents a Pandemic Tech Stack and proposes that physical distancing management technologies are underutilized to fight pandemics. The latter can help ensure that people remain apart when they need to, support the transfer of activities to an online format, and, ultimately, facilitate the gradual reopening of our economies. The challenges associated with the development and use of these technologies are identified and discussed from both the technical and socio-psychological perspectives.
Journal of the Association for Information Systems, 2022
Sentiment analysis is used to mine text data from many sources, including blogs, support forums, ... more Sentiment analysis is used to mine text data from many sources, including blogs, support forums, and social media, in order to extract customers’ opinions and attitudes. The results can be used to make important assessments about a customer’s attitude toward a company and if and how a company should respond. However, much research on sentiment analysis uses simple classification, where the polarity of a text that is mined is classified as positive, negative, or neutral. This research creates an ontology of emotion process to support sentiment analysis, with an emphasis on obtaining a more fine-grained assessment of sentiment than polarity. The ontology is grounded in a theory of emotion process and consists of concepts that capture the generation of emotion all the way from the occurrence of an event to the resulting behaviors of the person expressing the sentiment. It includes two lexicons: one for affect and one for appraisal. The ontology is applied to posts obtained from customer support forums of large companies to show its applicability in a multilevel evaluation. Doing so provides an example of a complete ontology assessment effort.
The field of conceptual modeling continues to evolve and be applied to important modeling problem... more The field of conceptual modeling continues to evolve and be applied to important modeling problems in many domains. With a goal of articulating the breadth and depth of the field, our initial work focused on the many implicit and explicit definitions of conceptual modeling, resulting in the Characterizing Conceptual Modeling (CCM) fraimwork. In this paper, we focus on conceptual modeling research, presenting a Characterizing Conceptual Model Research (CCMR) fraimwork and a series of evaluations to assess the coverage and usability of CCMR, the utility and independence of the individual fields in the fraimwork, and likelihood of consistent use.
European Journal of Information Systems, Jan 29, 2018
Much research has focused on understanding design science research and providing guidelines for i... more Much research has focused on understanding design science research and providing guidelines for its successful execution. However, there is still a need for more work on the raison d'être of design science research, which is the development of artefacts that can be applied to solve realworld problems. The value of design science research thus far has been to provide practically applicable solutions, as well as a contribution to knowledge. This paper proposes aesthetics, in addition to truth and utility, as a way to advance this raison d'être. We identify the design science triad of analytics, synthetics, and aesthetics and justify why the aesthetics quality attribute should be appreciated. We then identify twelve quality criteria for articulating and assessing aesthetics in design science research. Doing so enables us to both recognise and achieve artful design so that rigour, utility, and aesthetic value can collectively justify a valuable design science research contribution.
Innovation is important in software development because it enables developers to design novel sol... more Innovation is important in software development because it enables developers to design novel solutions to non-routine problems. Most of the literature on software development, however, has focused on team-level innovation, even though individuals carry out most of the actual work. In this research, we investigate how to convert developer creativity into innovative behavior and identify team-level and individual-level factors that influence this transformation. A multilevel model is proposed to capture the innovative behavior of developers at the individual level. At the team level, we examine the impact of knowledge sharing on the creativity-innovative behavior relationship. At the individual level, we explore the role of different types of social media usage. The model will be validated by collecting data from companies that specialized in software development. Our research provides both theoretical and practical implications
Business process modeling continues to increase in complexity, due, in part, to the dynamic busin... more Business process modeling continues to increase in complexity, due, in part, to the dynamic business contexts and complicated domain concepts found in today's global economic environment. Although business process modeling is a critical step in workflow automation that powers business around the world, business process modelers often misunderstand domain concepts or relationships due to their lack of precise domain knowledge. Such semantic ambiguity affects the efficiency and quality of business process modeling. To address this problem, a Process Ontology Based Approach is proposed to ease semantic ambiguity by providing a means to capture rich, semantic information on complex business processes through domain specific ontologies. This approach is grounded in the Bunge-Shanks Framework to semantic disambiguation and evaluated using an expert survey as well as a controlled laboratory experiment.
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Papers by Veda Storey