Data Science for Social Good

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Abbasi, Ahmed; Chiang, Roger; Xu, Jennifer

Abstract: Data science has been described as the fourth paradigm of scientific discovery. ... Expand

Abstract: Data science has been described as the fourth paradigm of scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of annual citations. However, this growth has been accompanied by a diminishing emphasis on social good challenges-our analysis reveals that the proportion of data science research focusing on social good is less than it has ever been. At the same time, the proliferation of machine learning and generative AI has sparked debates about the sociotechnical prospects and challenges associated with data science for human flourishing, organizations, and society. Against this backdrop, we present a framework for "data science for social good" (DSSG) research that considers the interplay between relevant data science research genres, social good challenges, and different levels of sociotechnical abstraction. We perform an analysis of the literature to empirically demonstrate the paucity of work on DSSG in information systems (and other related disciplines) and highlight current impediments. We then use our proposed framework to introduce the articles appearing in the JAIS special issue on data science for social good. We hope that this editorial and the special issue will spur future DSSG research and help reverse the alarming trend across data science research over the past 30-plus years in which social good challenges are attracting proportionately less attention with each passing day. Collapse

Topics: societal evaluation criteria digital dashboard productivity social media pandemic

Methods: word embedding literature study literature sample longitudinal research design science

How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Abdel-Karim, Benjamin; Pfeuffer, Nicolas; Carl, K. Valerie; Hinz, Oliver

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelli ... Expand

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of MLbased decision support systems and also enriches theories on human-AI augmentation. Collapse

Topics: artificial intelligence decision making decision support system algorithmic transparency recommender system

Methods: cognitive walkthrough survey theory development qualitative interview Student's t-test

Theories: learning theory information systems theory theory of abduction

A taxonomy of data governance decision domains in data marketplaces

2023 | Electronic Markets | Citations: 0

Authors: Abraham, Rene; Schneider, Johannes; vom Brocke, Jan

Abstract: Commercializing data and data-related services has gained in importance in recen ... Expand

Abstract: Commercializing data and data-related services has gained in importance in recent years. Driven by digitalization and the Internet-of-Things (IoT), companies and individuals continuously generate vast amounts of data. Data marketplaces have emerged to support these data providers in selling their data to different data consumers. However, data marketplaces face challenges in different data governance decision domains that inhibit their adoption. To get a better understanding of how data marketplaces counteract these challenges, this paper develops a taxonomy of data governance decision domains in data marketplaces. We used a taxonomy development method to inspect 13 data marketplaces from eight countries. The resulting taxonomy shows an overview of mechanisms concerning data quality, data security, data architecture, metadata, data lifecycle, data storage, and data pricing. We discuss common instantiation patterns, highlight gaps, and propose possible solutions. The taxonomy sets a foundation for further research and theory-building on data marketplaces. Practitioners can use the taxonomy to develop customized data governance strategies for data marketplaces. Collapse

Topics: data governance price management system development method computer data storage website

Methods: design artifact data modeling design methodology design science company material

Know the Knowledge of Your Students: A Flexible Analytics Tool for Student Exercises

2023 | DESRIST | Citations: 0

Authors: Aguirre Reid, Sören; Kammer, Frank; Schüller, Daria; Siepermann, Markus; Wölfer, Jonas

Abstract: Intelligent tutoring systems (ITS) have the power to influence lecturers’ practi ... Expand

Abstract: Intelligent tutoring systems (ITS) have the power to influence lecturers’ practices in the classroom and to improve students’ learning. Many ITS provide standardized analytical methods to evaluate classroom performance or the results of the exercises. But they lack more sophisticated, flexible and individual analyses. This paper presents an e-learning Analytics Tool (EAT) for an ITS that provides a dashboard with key figures and a flexible analytics board (FAB). This enables lecturers to analyze students’ performance in detail and identify misconceptions. For instance, the FAB allows us to classify student solutions, reveal conceptual errors in exercises, and analyze each part of an exercise. By this, common mistakes can be identified, and tailored feedback can be given to the students. Following the design science approach, the platform is designed in a general way so that it can be used for different types of exercises (e.g., Math, Excel, SQL). To assess the artifact, we conducted group interviews with German University lecturers from various courses. The results show that lecturers require a good overview of the submitted student solutions to provide timely feedback. They also appreciate the flexible analytics tool for detailed analyses of student solutions to understand student mistakes better. The employed architecture allows general analyses of exercises and the content of students’ solutions. In addition, the EAT is not bound to a specific kind of exercise, but can cope with different kinds like SQL and Excel. Collapse

Topics: digital dashboard structured query language database system online learning system perceived usefulness

Methods: group interview design science design artifact survey qualitative interview

Blockchain Use Case in Ballistics and Crime Gun Tracing and Intelligence: Toward Overcoming Gun Violence

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Akello, Patricia; Vemprala, Naga; Lang Beebe, Nicole; Raymond Choo, Kim-Kwang

Abstract: In the United States and around the world, gun violence has become a long-standi ... Expand

Abstract: In the United States and around the world, gun violence has become a long-standing public safety concern and a security threat, due to violent gun-related crimes, injuries, and fatalities. Although legislators and lawmakers have attempted to mitigate its threats through legislation, research on gun violence confirms the need for a comprehensive approach to gun violence prevention. This entails addressing the problem in as many ways as possible, such as through legislation, new technological advancements, re-engineering supply, and administrative protocols, among others. The research focuses on the technological, supply, and administrative aspects, in which we propose a manner of managing gun-related data efficiently from the point of manufacture/sale, as well as at points of transfers between secondary sellers for the improvement of criminal investigation processes. Making data more readily available with greater integrity will facilitate successful investigations and prosecutions of gun crimes. Currently, there is no single and uniform platform for firearm manufacturers, dealers, and other stakeholders involved in firearm sales, dissemination, management, and investigation. With the help of Blockchain technology, gun registry, ownership, transfers, and, most importantly, investigations, when crimes occur, can all be managed efficiently, breaking the cycle of gun violence. The identification of guns, gun tracing, and identification of gun owners/possessors rely on accuracy, integrity, and consistency in related systems to influence gun crime investigation processes. Blockchain technology, which uses a consensus-based approach to improve processes and transactions, is demonstrated in this study as a way to enhance these procedures. To the best of our knowledge, this is the first study to explore and demonstrate the utility of Blockchain for gun-related criminal investigations using a design science approach. Collapse

Topics: blockchain criminality smart contract Ethereum access control

Methods: design artifact design science design process case study simulation

Knowledge contributions in design science research: Paths of knowledge types

2023 | Decision Support Systems | Citations: 0

Authors: Akoka, Jacky; Comyn-Wattiau, Isabelle; Prat, Nicolas; Storey, Veda C.

Abstract: Design science research addresses important, complex real-world problems. Althou ... Expand

Abstract: Design science research addresses important, complex real-world problems. Although well-accepted as part of research in information systems, initiating or progressing a design science research project still requires effort to describe how knowledge creation emerges and its underlying dynamics. Given the existing body of knowledge on design science research, it should be possible to learn from that knowledge to progress future work. This paper analyzes design science research projects to identify and make explicit their knowledge contributions while recognizing the plurality of a project's knowledge contributions with respect to a project's knowledge scope and knowledge goals. The construct of a path of knowledge types is introduced that represents how knowledge con­ tributions are dynamically created throughout a project. These paths form the basis for the derivation of seven design science research strategies, which lead to guidelines for initiating or progressing a project. This effort is compared to other research that analyzes the growing body of work in design science with respect to knowledge contributions and project classifications. Collapse

Topics: knowledge type decision support system IT project management innovation management anonymity

Methods: design science literature sample literature study design artifact design principle

Design Science Research: Progression, Schools of Thought and Research Themes

2023 | DESRIST | Citations: 0

Authors: Akoka, Jacky; Comyn-Wattiau, Isabelle; Storey, Veda C.

Abstract: Design science research, a well-established research approach to solving complex ... Expand

Abstract: Design science research, a well-established research approach to solving complex real-world problems, has evolved over time. This research characterizes design science research in information systems. By performing a bibliometric analysis, we show that design science research has progressed in the information systems field through three main phases, which we call periods of inquiry. A co-citation analysis shows that the progression has been largely influenced by a few main pioneering studies, leading to three schools of thought. Bibliographic coupling analysis suggests that research in design science can be classified into several distinct intellectual areas corresponding to different research themes. This bibliometric analysis proposes a broad viewpoint of design science and design research, serving as a basis for shaping further research. Collapse

Topics: blockchain database system

Methods: design science co-citation analysis literature sample bibliometric analysis cluster analysis

Capabilities and metrics in DevOps: A design science study

2023 | Information & Management | Citations: 0

Authors: Amaro, Ricardo; Pereira, Rúben; Da Silva, Miguel Mira

Abstract: Customer demands, competition, regulatory environments, and sophisticated extern ... Expand

Abstract: Customer demands, competition, regulatory environments, and sophisticated external threats have all increased the importance of DevOps in IT organizations. However, DevOps adoption is still uneven, emphasizing the need to provide management with relevant IS data and insights. Regrettably, there is a measurement inefficiency between these capabilities. Collapse

Topics: devops database system Google+ spreadsheet source code

Methods: qualitative interview personal interview literature study design science design artifact

Blockchain innovation for consent self-management in health information exchanges

2023 | Decision Support Systems | Citations: 0

Authors: Anderson, Chad; Carvalho, Arthur; Kaul, Mala; Merhout, Jeffrey W.

Abstract: With the increasing digitalization of health data, patients need to make informe ... Expand

Abstract: With the increasing digitalization of health data, patients need to make informed decisions about the online sharing of their protected health information. This necessitates a robust technical infrastructure that enables patients to self-manage consent and the trusted exchange of this information across sharing entities. Unfortu­ nately, current health information exchange systems in the U.S. are limited in both these regards. While there is recent work on digital patient consent management, there is limited work that provides effective solutions for patient self-management of consent. Further, interoperability issues in the way health information exchanges are currently architected and differences in regulations across localities exacerbate the challenges of consent man­ agement. In this research, we survey potential patients' willingness to self-manage healthcare-related consent. Having established the desire for consent self-management, we propose a solution that enables the seamless sharing of patient consent across different healthcare providers and health information exchanges. Specifically, we use a rigorous design science approach to create a blockchain-based, self-managed patient consent system and we evaluate the design through an instantiated prototype. The results of our study should be useful to researchers in healthcare information management as well as to practitioners designing consent management systems. Our research contributes to design science research with an innovative, rigorously evaluated, design principles-based artifact that addresses a critical problem of sharing protected health information. Collapse

Topics: blockchain mobile application information exchange privacy Ethereum

Methods: survey design artifact design science design process design principle

Theories: evidence-based design

Designing Culturally Appropriate Hackathons to Increase Data Literacy in Indigenous Communities

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aniceto, Janaina; Corbett, Jacqueline; Chung, Alexander

Abstract: Data literacy skills are extremely important, yet it is still lacking in many I ... Expand

Abstract: Data literacy skills are extremely important, yet it is still lacking in many Indigenous communities across Canada due to systemic barriers faced by Indigenous peoples. Hackathons have been used as a common approach to promote data literacy. However, hackathons are socio-technical innovation processes in which local cultures and values play a role in their conduct and outcomes. Hackathons that are designed with Indigenous cultures and values in mind can be more effective at promoting data literacy for Indigenous peoples, yet there is limited guidance on how to do so. In this paper, we adopt the Action Design Research approach and Indigenous research methods to collaboratively develop and deliver culturally appropriate hackathons to increase data literacy within Indigenous communities. During this process we will also co-develop a suite of design principles to guide the design of these hackathons. Collapse

Topics: data literacy systems development

Methods: action design research design science design principle theoretical contribution qualitative interview