Taking advantage of the software product line paradigm to generate customized user interfaces for decision-making processes: a case study on university employability

Vázquez-Ingelmo, Andrea; García-Peñalvo, Francisco José; Therón, Roberto

doi:10.7717/peerj-cs.203

Cited by 21 publications

(12 citation statements)

References 37 publications

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“…These paradigms are used to finally generate a dashboard that fits the previously defined feature model, as shown in Figure 6. Regarding the solution presented in [23], it is worth to mention that an extended version of this work can be found at [42]. This last work did not appear within the selected papers because it was published after the execution of the present SLR, but in subsequent updates, it would replace the previous paper, keeping the most complete and recent version of the study.…”

Section: B Which Methods Have Been Applied To Support Tailoring Capamentioning

confidence: 99%

Information Dashboards and Tailoring Capabilities - A Systematic Literature Review

2019

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The design and development of information dashboards are not trivial. Several factors must be accounted; from the data to be displayed to the audience that will use the dashboard. However, the increase in popularity of these tools has extended their use in several and very different contexts among very different user profiles. This popularization has increased the necessity of building tailored displays focused on specific requirements, goals, user roles, situations, domains, etc. Requirements are more sophisticated and varying; thus, dashboards need to match them to enhance knowledge generation and support more complex decision-making processes. This sophistication has led to the proposal of new approaches to address personal requirements and foster individualization regarding dashboards without involving high quantities of resources and long development processes. The goal of this work is to present a systematic review of the literature to analyze and classify the existing dashboard solutions that support tailoring capabilities and the methodologies used to achieve them. The methodology follows the guidelines proposed by Kitchenham and other authors in the field of software engineering. As results, 23 papers about tailored dashboards were retrieved. Three main approaches were identified regarding tailored solutions: customization, personalization, and adaptation. However, there is a wide variety of employed paradigms and features to develop tailored dashboards. The present systematic literature review analyzes challenges and issues regarding the existing solutions. It also identifies new research paths to enhance tailoring capabilities and thus, to improve user experience and insight delivery when it comes to visual analysis.

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Section: B Which Methods Have Been Applied To Support Tailoring Capamentioning

confidence: 99%

Information Dashboards and Tailoring Capabilities - A Systematic Literature Review

2019

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“…This instance is then handed to a custom Python dashboard generator which "translates" the XMI structure into a set of software components. These components are tailored from a set of core assets developed following the SPL paradigm [65].…”

Section: Meta-model Instantiation: a Dashboard For Supporting Caregiversmentioning

confidence: 99%

A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare

Vázquez-Ingelmo

García‐Holgado

García-Peñalvo

et al. 2020

Sensors

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Knowledge management is one of the key priorities of many organizations. They face different challenges in the implementation of knowledge management processes, including the transformation of tacit knowledge—experience, skills, insights, intuition, judgment and know-how—into explicit knowledge. Furthermore, the increasing number of information sources and services in some domains, such as healthcare, increase the amount of information available. Therefore, there is a need to transform that information in knowledge. In this context, learning ecosystems emerge as solutions to support knowledge management in a different context. On the other hand, the dashboards enable the generation of knowledge through the exploitation of the data provided from different sources. The model-driven development of these solutions is possible through two meta-models developed in previous works. Even though those meta-models solve several problems, the learning ecosystem meta-model has a lack of decision-making support. In this context, this work provides two main contributions to face this issue. First, the definition of a holistic meta-model to support decision-making processes in ecosystems focused on knowledge management, also called learning ecosystems. The second contribution of this work is an instantiation of the presented holistic meta-model in the healthcare domain.

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“…Among the methods used to configure these tools, the software product lines (SPL) paradigm [4,5] and model-driven development (MDD) [6,7] can be found [8][9][10][11][12].…”

Section: P O S Tmentioning

confidence: 99%

Capturing high-level requirements of information dashboards' components through meta-modeling

Vázquez-Ingelmo

García-Peñalvo

Therón

2019

Proceedings of the Seventh International Conference on Technological Ecosystems for Enhancing Multiculturality

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Information dashboards are increasing their sophistication to match new necessities and adapt to the high quantities of generated data nowadays. These tools support visual analysis, knowledge generation, and thus, are crucial systems to assist decision-making processes. However, the design and development processes are complex, because several perspectives and components can be involved. Tailoring capabilities are focused on providing individualized dashboards without affecting the time-to-market through the decrease of the development processes' time. Among the methods used to configure these tools, the software product lines paradigm and model-driven development can be found. These paradigms benefit from the study of the target domain and the abstraction of features, obtaining highlevel models that can be instantiated into concrete models. This paper presents a dashboard meta-model that aims to be applicable to any dashboard. Through domain engineering, different features of these tools are identified and arranged into abstract structures and relationships to gain a better understanding of the domain. The goal of the meta-model is to obtain a framework for instantiating any dashboard to adapt them to different contexts and user profiles. One of the contexts in which dashboards are gaining relevance is Learning Analytics, as learning dashboards are powerful tools for assisting teachers and students in their learning activities. To illustrate the instantiation process of the presented meta-model, a small example within this relevant context (Learning Analytics) is also provided.

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Taking advantage of the software product line paradigm to generate customized user interfaces for decision-making processes: a case study on university employability

Cited by 21 publications

References 37 publications

Information Dashboards and Tailoring Capabilities - A Systematic Literature Review

Information Dashboards and Tailoring Capabilities - A Systematic Literature Review

A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare

Capturing high-level requirements of information dashboards' components through meta-modeling

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