Device Cloud platform with customizable Remote User Interfaces

Radovanovic, S.; Majstorovic, Bojan; Kukolj, Sandra; Bjelica, Milan Z.

doi:10.1109/icce-berlin.2014.7034231

Cited by 3 publications

(14 citation statements)

References 3 publications

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“…In [16], a device cloud platform dashboard is built based on the data model of the remote devices being monitored, but users can also customize it manually. On the other hand, Van Hoecke et al [18] use a semantic reasoner to personalize indicators from available data sources.. Santos et al [23] also proposes personalized dashboards based on knowledge graphs and indicator ontologies, but the solution allows the users to modify the dashboard recommendation to its own preferences.…”

Section: Discussionmentioning

confidence: 99%

“…The complete list of methods can be consulted in Table 7. Configuration files 3 [20] [26] [28] Model-driven 3 [12] [21] [9] Agents 2 [16] [14] SPL 2 [27] [15] Pre-defined templates 2 [25] [9] Semantic reasoner 1 [18] Inclusive user modeling 1 [30] Context-aware generator 1 [24] Indicator ontology 1 [23] Knowledge graphs 1 [23]…”

Section: Mq8 Which Methods Have Been Used For Enabling Variability?mentioning

confidence: 99%

“…The results cover from 2011 to 2018, with a work placed in 2007 [9]. A few records were published in 2011 [10; 11], 2012 [12], 2013 [13], 2014 [14][15][16] and 2016 [17; 18]. However, the majority of records are distributed between 2017 [19][20][21][22][23][24] and 2018 [25][26][27][28][29][30][31], six and seven papers respectively.…”

Section: Mq1 How Many Studies Were Published Over the Years?mentioning

confidence: 99%

“…Regarding customizable and/or personalized dashboards, it can be seen that Business Intelligence (BI) is the most common application domain (Figure 3), followed by the Internet of Things (IoT), Learning Analytics (LA), services monitoring and social science domains. IoT 2 [16] [18] Learning Analytics 2 [22] [24] Services monitoring 2 [20] [26] Disaster situations 1 [30] Economics 1 [31] Emergency management 1 [17] Energy monitoring 1 [13] Generic 1 [29] Interface evaluation 1 [28] Microservices monitoring 1 [19] Physics 1 [11] Sensor monitoring 1 [15] Social sciences 1 [27] 4.5 MQ5. Which are the factors that condition the dashboards' variability process?…”

Section: Mq4 To Which Contexts Have Been the Variability Processes Amentioning

confidence: 99%

“…The majority of the included papers make use of the user preferences as input to modify the dashboard appearance and functionality (Table 4). Business process 3 [12] [9] [21] User role 2 [21] [9] Design guidelines 2 [25] [28] Usage profiles 1 [14] Data sources 2 [16] [18] Goals 2 [12] [21] User description 1 [24] Analysis scenario 1 [24] User abilities 1 [30]…”

Section: Mq4 To Which Contexts Have Been the Variability Processes Amentioning

confidence: 99%

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Tailored information dashboards

Vázquez-Ingelmo

García-Peñalvo

Therón

2019

Proceedings of the XX International Conference on Human Computer Interaction

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Information dashboards are extremely useful tools to exploit knowledge. Dashboards enable users to reach insights and to identify patterns within data at-a-glance. However, dashboards present a series of characteristics and configurations that could not be optimal for every user, thus requiring the modification or variation of its features to fulfill specific user requirements. This variation process is usually referred to as customization, personalization or adaptation, depending on how this variation process is achieved. Given the great number of users and the exponential growth of data sources, tailoring an information dashboard is not a trivial task, as several solutions and configurations could arise. To analyze and understand the current state-of-the-art regarding tailored information dashboards, a systematic mapping has been performed. This mapping focus on answering questions regarding how existing dashboard solutions in the literature manage the customization, personalization and/or adaptation of its elements to produce tailored displays. P O S TGiven the large amount of content customization and/or personalization possibilities, and the potential misconception of those terms, this paper aims to investigate the existing literature regarding the customization, adaptation and/or personalization of information dashboards, focusing on mapping [4] the collected studies to understand the existing solutions and research lines of this area.The remainder of this paper is organized as follows. Section 2 outlines the research method followed to perform the systematic mapping. Section 3 describes the data extraction process for analyzing the collected works. Section 4 presents the results of the systematic mapping, finishing with Section 5 where the results are discussed and Section 6, where the work's conclusions are shared. RESEARCH METHODThis study is based on the guidelines suggested by Kitchenham and Charters [5] for systematic literature studies and the guidelines suggested by Petersen [6] for mapping studies. The mapping process is organized in a series of phases; first, the planning phase, where the main goals and research questions to be answered are defined. Second, the conducting phase, where the search strategy is generated and the selection, assessment and data extraction of the studies are performed. The final stage is the reporting phase, where the results are disseminated. P O S T

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Section: Discussionmentioning

confidence: 99%

Section: Mq8 Which Methods Have Been Used For Enabling Variability?mentioning

confidence: 99%

Section: Mq1 How Many Studies Were Published Over the Years?mentioning

confidence: 99%

Section: Mq4 To Which Contexts Have Been the Variability Processes Amentioning

confidence: 99%

Section: Mq4 To Which Contexts Have Been the Variability Processes Amentioning

confidence: 99%

See 3 more Smart Citations

Tailored information dashboards

Vázquez-Ingelmo

García-Peñalvo

Therón

2019

Proceedings of the XX International Conference on Human Computer Interaction

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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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Towards a Technological Ecosystem to Provide Information Dashboards as a Service: A Dynamic Proposal for Supplying Dashboards Adapted to Specific Scenarios

2021

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Data are crucial to improve decision-making and obtain greater benefits in any type of activity. However, the large amount of information generated by new technologies has made data analysis and knowledge generation a complex task. Numerous tools have emerged to facilitate this generation of knowledge, such as dashboards. Although dashboards are useful tools, their effectiveness can be affected by poor design or by not taking into account the context in which they are placed. Therefore, it is necessary to design and create custom dashboards according to the audience and data domain. This paper presents an application of the software product line paradigm and the integration of this approach into a web service to allow users to request source code for customized information dashboards. The main goal is to introduce the idea of creating a holistic ecosystem of different services to craft and integrate information visualizations in a variety of contexts. One of the contexts that can be especially favored by this approach is the educational context, where learning analytics, data analysis of student performance, and didactic tools are becoming very relevant. Three different use cases of this approach are presented to illustrate the benefits of the developed generative service.

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Device Cloud platform with customizable Remote User Interfaces

Cited by 3 publications

References 3 publications

Tailored information dashboards

Tailored information dashboards

Information Dashboards and Tailoring Capabilities - A Systematic Literature Review

Towards a Technological Ecosystem to Provide Information Dashboards as a Service: A Dynamic Proposal for Supplying Dashboards Adapted to Specific Scenarios

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