Transparency is a key emerging requirement in modern businesses and their information systems. Transparency refers to the information which flows amongst stakeholders for the purpose of informed decision-making and taking the right action. Transparency is generally associated with positive connotations such as trust and accountability. However, it has been shown that it could have adverse effects such as information overload and affecting decisions objectiveness. This calls for systematic approaches for transparency to ensure its cost-effectiveness and avoid such adverse side effects. This is especially true considering that the relatively few works in the literature on transparency requirements have focused mainly on making information available and accessible and have paid little focus on the information receivers’ side and making it meaningful for them. In this paper, we reflect on our previous research on transparency and its multi-faceted constructs and review multi-disciplinary conceptualisation and propose four reference models which are meant to form a holistic conceptual baseline for transparency requirements in information systems. These reference models cover transparency actors, transparency meaningfulness, transparency usefulness, and information quality in transparency. We also discuss the interdependencies amongst these four reference models and their implications for requirements engineers and information system analysts. As a proof of concept, we analyse a mainstream transparency document, the United Kingdom Freedom of Information Act, in the light of our reference models and demonstrate the need to consider transparency more holistically and the need to include the information receiver’s perspective and the inter-relations amongst various properties and constituents of transparency as well. We then highlight areas of improvement informed by our analysis.

The widespread adoption of truly portable, smart devices and Do-It-Yourself computing platforms by the general public has enabled the rise of new network and system paradigms. This abundance of well-connected, well-equipped, affordable devices, when combined with crowdsourcing methods, enables the development of systems with the aid of the crowd. In this work, we introduce the paradigm of Crowdsourced Systems, systems whose constituent infrastructure, or a significant part of it, is pooled from the general public by following crowdsourcing methodologies. We discuss the particular distinctive characteristics they carry and also provide their “canonical” architecture. We exemplify the paradigm by also introducing Crowdcloud, a crowdsourced cloud infrastructure where crowd members can act both as cloud service providers and cloud service clients. We discuss its characteristic properties and also provide its functional architecture. The concepts introduced in this work underpin recent advances in the areas of mobile edge/fog computing and co-designed/co-created systems.

Problem solving applications require users to exercise caution in their data usage practices. Prior to installing these applications, users are encouraged to read and comprehend the terms of service, which address important aspects such as data privacy, processes, and policies (referred to as information elements). However, these terms are often lengthy and complex, making it challenging for users to fully grasp their content. Additionally, existing transparency analytics tools typically rely on the manual extraction of information elements, resulting in a time-consuming process. To address these challenges, this paper proposes a novel approach that combines information visualization and machine learning analyses to automate the retrieval of information elements. The methodology involves the creation and labeling of a dataset derived from multiple software terms of use. Machine learning models, including naïve Bayes, BART, and LSTM, are utilized for the classification of information elements and text summarization. Furthermore, the proposed approach is integrated into our existing visualization tool TranspVis to enable the automatic detection and display of software information elements. The system is thoroughly evaluated using a database-connected tool, incorporating various metrics and expert opinions. The results of our study demonstrate the promising potential of our approach, serving as an initial step in this field. Our solution not only addresses the challenge of extracting information elements from complex terms of service but also provides a foundation for future research in this area.