T1: Managing IS Development and Operations

Information Systems Development (ISD) is concerned with the creation of new Information Systems (IS), comprising processes, people and technologies. More than just dealing with typical technical software development activities, ISD is eminently sociotechnical.

More recently, ISD is facing two major challenges: dealing with the increasing incorporation of artificial intelligence (AI) in the software solutions and with the increasing cyberattacks that call for more robust security from the design phase. Both will have considerable implications in future DevOps pipelines. We expect to foster the discussion about the evolution of ISD to address emerging trends.

Track topics include (but not limited to):

  • Dealing with the incorporation of AI in software
  • Security in the software development pipeline
  • Security by design
  • AI regulations and software development
  • Security regulations and software development
  • Validation challenges
  • Developing for multiple heterogenous cloud environments
  • Monitoring and auditing in the cloud
  • Developing for the cloud-edge continuum
  • Maturity models for software development
  • DevOps
  • Software development models and methods
  • Requirements engineering
  • New generation tools to support software development pipelines
  • Continuous integration and continuous delivery in IS development
  • Infrastructure as Code and IS
  • Microservices in IS development
  • Social and cultural aspects in continuous IS development
  • Interdisciplinary problems in managing IS development
  • Project management
  • Model-driven development and technologies for ISD
  • Quality of IS models and design
  • Emerging issues in managing IS development

Track Chairs

Juan Manuel Vara, University Rey Juan Carlos, Spain
Paulo Rupino da Cunha, University of Coimbra, Portugal

T2: Information Systems Modelling

It appears that “digital” is all around us, both in our personal and work lives. The growing popularity of approaches like model-driven development and low-code development, which involve code generation, has made modelling more relevant than ever in information systems development.

Professionals have sometimes been reluctant to create models as part of their work but that attitude is slowly changing. In agile information systems development, the traditional reluctance to use software models has been replaced by a more practical approach, recognizing the value that models derived from user stories and other requirements artefacts can provide in ensuring the timely delivery of high-quality systems. Data scientists are also increasingly using domain models to make sense of the data in their pipelines, which are used to build, train, evaluate, and deploy machine learning models. Overall, there is a renewed appreciation for the role of information system models, including conceptual or domain models, requirements models, and software models, leading to the question of how these modelling approaches can be improved or innovated to better support new approaches to information systems development.

Track topics include (but not limited to):

  • Model-driven information systems development
  • Conceptual modelling for information systems development
  • The use of models in agile information systems development
  • Domain modelling for data analytics applications
  • Information systems requirements modelling
  • The transformation of models into code
  • The transformation of text into models
  • Dialogic approaches to information systems modelling
  • Naturalistic information systems modelling environments
  • Ontology-driven conceptual modelling
  • Enterprise modelling
  • Reference models for information systems development
  • Generic information system models
  • Reusing information system models
  • Storing information system models in repositories
  • Assessing the quality of information system models

Track Chairs

Geert Poels, Ghent University, Belgium
Bas van Gils, Antwerp Management School, Belgium

T3: User Interface and Customer Experience

IS development and operations must ensure that systems are designed and implemented for users and therefore should take into account the users’ needs, values, characteristics, and contexts of use throughout the system’s life cycle. Seamless human-technology interaction through good user interface design and good level of usability is the overall goal of system development; the developed system should help users to achieve specified individual and/or organizational goals in a specified context of use, as well as to facilitate a good customer experience. Good usability is achieved by adopting a user-centred design approach to IS development. User interface (UI) design, user experience (UX), Human-Computer Interaction (HCI), and Interaction Design (IxD) are related concepts.

Customer experience in IS (development and operations) is another important goal that characterizes the advancement of the socio-technical landscape. Customer Experience (CX) is the result of every interaction a customer has with an organization as a whole, which goes beyond interacting merely with the IS of this organization. In order to achieve high-quality UX/CX in an organization’s offerings, there must be a seamless merging of multiple disciplines, including marketing, graphical design, and interface development life cycle.

In this track, we approach the socio-technical landscape from individual, organizational, business, political, and societal perspectives. We emphasize the importance of the human and social dimensions and explore how we as IS research community can contribute to the development of better practices, policies, and cultures of IS development and operations. Furthermore, we want to also highlight the ethical aspects of human-technology interaction design and the rise of the “dark side” of design, where principles and methods of good design are used to develop unethical, deceptive and misleading user interfaces.

The track welcomes original contributions about user interfaces, usability, human-technology interaction, customer experience and related topics in IS development. Authors are invited to submit papers of either practical or theoretical nature.

Track topics include (but not limited to):

  • User interface
    • User interface and usability (UI, UX, HCI, IxD) models, methods, tools and practices in IS development lifecycle
    • New contributions to user interface and usability (UI, UX, HCI, IxD) theories, methods, and metrics
    • Human agency and empowerment in IS development, operations, and use
    • Accessibility
    • Ethical aspects in human-technology interaction design
    • Dark side of design
    • IS design (Participatory design, User-centred design, Service design, Politics of design)
    • Bridging the gap between satisfying organizational needs and supporting human users
    • Information visualization and analytics in IS: Human-centred perspectives
    • Usability cost-benefit analysis
  • Customer experience
    • factors along with evaluation techniques and measures
    • design for continuous IS delivery
    • in continuously deployed systems
    • design practices and guidelines in DevOps environments
    • in specific domains (e.g., healthcare, ambient assisted living, automotive systems, autonomous cars)
    • in multi-, cross- and omni-channel experiences

Track Chairs

Mikko Rajanen, University of Oulu, Finland
Thiago Rocha Silva, University of Southern Denmark, Denmark

T4: Data Science and Machine Learning

Information system development and management is increasingly benefiting from advances in Artificial Intelligence (AI). On the one hand, AI can provide robust approaches for software development, in order to analyze and evaluate complex software, its development processes, and its proper configuration. Repository mining, machine learning, big data analytics, and visualization can enable targeted insights and powerful predictions for software quality, software development, and software project management. These techniques are nowadays used by large companies to perform all the steps necessary for software development (requirements, design, implementation, testing, or deployment) faster, better, and at a lower cost.

On the other hand, many information systems have components that use AI to cluster, classify, or predict. We refer here primarily to components that employ data science and machine learning methods in the analysis of tabular data, but we do not exclude components that use computer vision or natural language processing. These components are used in a variety of applications, changing how many industries perform and conduct their day-to-day operations, from manufacturing and logistics, to modernizing government, finance, and healthcare streams.

Track topics include (but not limited to):

  • Data Science and Machine Learning for Customer Support and Service Management
  • Data Science and Machine Learning for IT Operations and for Managing IT Infrastructures
  • Data Science and Machine Learning for Business Process Automation
  • Data Science and Machine Learning for Fraud Detection
  • Data Science and Machine Learning for Software Development and Testing
  • Data Science and Machine Learning for Project Management
  • Applications of AI within Domain-Specific Information Systems (e.g., handling Geographic, Health, Procurement, Finance, Legal, or other Types of Information)
  • Other applications of AI in Information Systems

Track Chairs

Bruno Martins, University of Lisboa, Portugal
Diego Seco Naveiras, University of A Coruña, Spain

T5: Ontologies and Knowledge Management

Knowledge management is of strategic importance to organisations. The effective management of knowledge tends to enhance an organisation’s potential for innovation, competitiveness, growth, and overall performance. The challenges and complexities in managing knowledge have long been recognised. Among these challenges is the ability to represent knowledge, with its underlying data/information, in ways that it accurately maps to real-world problem domains while providing a sound basis for integrating heterogenous knowledge content derived from increasingly disparate information systems.

Ontology is acknowledged by both the research and practitioner communities as an effective means of precise representation of reality as well as a facilitator of semantic integration and interoperability between information systems and the knowledge embedded within these systems. A key role is played by foundational ontologies which provide the theoretical, as well as the practical, basis to represent knowledge via common semantics and generalised patterns of representation.

We invite submissions from researchers and practitioners on topics related to the area of Ontologies and Knowledge Management with a specific focus on how common semantic models can assist organisations to overcome the challenges of managing knowledge, information, and data within the context of an ever-increasing digitalisation of the business and its processes.

Track topics include (but not limited to):

  • Ontology in knowledge representation
  • Semantic integration of knowledge, information and/or data
  • Foundational ontologies
  • Domain ontologies
  • Ontological patterns and anti-patterns
  • Semantic tools and technologies
  • Ontology-driven conceptual modelling
  • Ontology in artificial intelligence
  • Ontology-driven information systems development
  • Semantic rules-based system
  • Semantic reasoning
  • Digital twins
  • Knowledge-based systems
  • Intelligent information retrieval
  • Role of ontology and knowledge management in digital transformation
  • Tacit and explicit knowledge
  • Methodologies for knowledge engineering

Track Chairs

Sergio De Cesare, University of Westminster, United Kingdom
Tiago Prince Salles, University of Twente, The Netherlands

T6: Learning, Education, and Training

This track focuses on a broad area of information systems development education and training. The goal is to create a forum of discussion and dissemination of novel, relevant and rigorous research as well as professional and practical experiences that address the challenges and opportunities in the education of IS specialists. This year, as previously, we strongly encourage contributions to advance the foundations of IS development methodologies.

The track invites submissions on: theoretical foundations and best practices related to the design, implementation, evaluation, adoption, and use of IS in formal and informal educational contexts in IS development; theoretical and empirical contributions to understanding and shaping methodological and educational aspects in IS development; and methodological contributions to IS development and IS development education.

Track topics include (but not limited to):

  • Activity theory approaches to IS development education
  • Case studies of IS and socio-technical systems design and development
  • Computer supported collaborative learning
  • Creativity and innovation in IS development education
  • Creativity and innovation in methodologies for IS development
  • Curriculum development, including local implementation of AIS/IEEE/ACM curricula
  • Digital literacy
  • Education for IS development
  • Education Management IS
  • Educational systems design, development, and evaluation
  • Ethical aspects related to IS education
  • HCI issues in IS development for education
  • Instructional design
  • Integrated IS application in education
  • IS development and teaching of programming
  • IS development education in developing regions
  • IS for online education
  • Learning platforms: mobile apps, MOOC
  • Longitudinal and comparative studies of learning
  • Open educational resources in IS development education
  • Serious games, gamification, and virtual worlds for learning
  • Social and crowd computing in educational contexts
  • Social media and learning
  • Socio-constructivism in IS development education
  • User generated content in IS development education
  • Work-integrated learning

Track Chairs

Mariia Rizun, University of Economics in Katowice, Poland
Pedro Barbosa Cabral, Universidade Aberta, Portugal

T7: Risk, Security, and Resilience

The emerging digital technologies such as artificial intelligence (AI), the internet of things (IoT), and blockchain technology are rapidly reshaping and transforming the evolving nature of our daily lives, business, and society. While these emerging technologies are getting popular, we are also witnessing many unexpected negative consequences related to the use and adoption of these technologies. From an information security perspective, the proliferation of digital technologies intensifies the concerns of data breaches. Cyber attackers are finding new ways online to conduct different attacks such as phishing, online fraud, identity theft, and so on. Moreover, cyber attackers are increasingly targeting human vulnerabilities with the use of various information systems in organizations. And the consequences of a successful cyberattack can have long-lasting effects on organizations.

One of the common ways to reduce and mitigate damages resulted from cyberattacks is through information security risk management. As a result, organizations are actively seeking solutions to conduct risk assessments, develop information security policies, and address cybersecurity related issues in an effective and efficient manner. This would be helpful for the resilience of individuals, business, and society during unexpected disruptions (e.g., COVID-19).

The aim of this track is to bring together academics, researchers, research scholars, industry players, stakeholders and the general public to share their research results and best practices related to Risk, Security, and Resilience. We welcome all aspects of research related to Risk, Security, and Resilience and are open to all types of research methods (e.g., literature review, case studies, survey, experimentation, action research, etc.). Practice-based research is also appreciated.

Track topics include (but not limited to):

  • Information security policy compliance/ non-compliance
  • Data Security and breaches
  • Information security management
  • Risk assessment
  • Risk management
  • Security policy development
  • Information systems security
  • Information security in digital transformation
  • Security and risk issues with emerging technologies
  • Information security awareness
  • Information systems resilience
  • Human aspects of information security
  • Vulnerabilities with the use of information systems
  • Security resilience
  • Challenges associated with resilience during major disruptions
  • Information security aspects of information systems development

Track Chairs

Marko Niemimaa, University of Agder, Norway
Shang Gao, Örebro University, Sweden

T8: New Topics in IS Development

The information systems scientific area continues to change at an almost instantaneous pace, making it challenging to keep up with the latest trends. Nevertheless, understanding these latest technological trends is significant for businesses and individuals who want to stay in the vanguard. The dynamic scientific area of Information Systems (IS) is full of new technologies, tools, software frameworks, and innovative ideas. Being so, it is important for researchers as well as for professionals to be informed of these recent emerging trends and all that they entail.

Today, the IS discipline faces new challenges. Emerging technologies as well as matured approaches to the social, technical, and developmental role of IS provide a new context for the evolution of the discipline over the next few years.

We look forward to receiving research papers from multidisciplinary areas that intersect with IS, specifically, but not restricted to, main trends in the context of Information Systems development and application field:

  • Artificial intelligence and machine learning
  • Edge computing and quantum computing
  • Cybersecurity
  • Blockchain
  • Virtual reality and augmented reality
  • Intelligent process automation

Track Chairs

Henrique Mamede, Universidade Aberta, Portugal
Tomas Skersys, Kaunas University of Technology, Lithuania