Visualizing the Provenance of Personal Data Using Comics

Schreiber, Andreas; Struminski, Regina

doi:10.3390/computers7010012

Cited by 9 publications

(18 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…All 17 studies were found in the SLR process together with the snowball technique, which are [ 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 ] and are focused on managing provenance data in HISs. In Table 10 , the similarities of the 17 studies are observed in the following characteristics that contribute to the management of provenance data in HISs: use of models from the W3C PROV family; use of different models from the W3C PROV family; use of provenance techniques with blockchain; and use of provenance techniques with middleware.…”

Section: Similarities Of the Selected Studiesmentioning

confidence: 99%

“…We highlight the data provenance models indicated by the W3C implemented through computational tools in different types of HISs. The models indicated by the W3C that appeared the most were as follows: PROV [ 91 , 96 , 98 , 99 , 103 , 105 , 106 ] applied in HISs (EHRs, PHRs, the LHS, the CRIS, and the HIS); PROV-O [ 91 , 95 , 96 , 98 , 99 ] applied in EHRs, PHRs, the LHS, and the CRIS; OPM [ 97 , 98 , 100 , 101 ] applied in HISs (PHR and LHS); PROV-DM [ 91 , 96 , 99 , 101 ] applied in HISs (HER, PHRs, and the CRIS); and PROV-N [ 98 , 99 ] applied in HISs (PHRs and the LHS). These models appear more frequently because they are application-specific models of data provenance recommended by the W3C, capable of describing the entities and processes involved in the production of a resource.…”

Section: Systematic Literature Review Reportmentioning

confidence: 99%

See 1 more Smart Citation

Provenance Data Management in Health Information Systems: A Systematic Literature Review

Sembay

Macedo

Júnior

et al. 2023

JPM

View full text Add to dashboard Cite

Aims: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. Method: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. Results: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. Conclusion: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs.

show abstract

Section: Similarities Of the Selected Studiesmentioning

confidence: 99%

Section: Systematic Literature Review Reportmentioning

confidence: 99%

Provenance Data Management in Health Information Systems: A Systematic Literature Review

Sembay

Macedo

Júnior

et al. 2023

JPM

View full text Add to dashboard Cite

show abstract

“…Maka disimpulkan bahwa komik mampu membantu siswa menaikkan literasi sains (Riwanto & Budiarti, 2020). Hal ini mampu ditunjukkan dari gambaran visual secara ikonik pada media komik (Schreiber & Struminksi, 2018). Sehingga peserta didik tidak langsung belajar memakai media konkret melainkan menggunakan gambar kartun yang menarik sebagai topik materi pembelajaran (Hartel & Dunst, 2019).…”

Section: Pendahuluanunclassified

Pengembangan Komik dengan Pendekatan Culturally Responsive Teaching untuk Menumbuhkan Literasi Sains pada Kelas V SDN Kalicari 01 Semarang

Priyangga

Mushafanah

Listyarini

et al. 2023

Jurnal Kridatama Saintek

View full text Add to dashboard Cite

This research is a comic development with a Culturally Responsive Teaching approach to foster scientific literacy. Learning media can help achieve learning objectives. This study aims to develop amusing learning media with a Culturally Responsive Teaching approach to foster scientific literacy in fifth-grade elementary schools. The type of research used is Research and Development with the ADDIE development model, namely Analyze, Design, Development, Implementation, and Evaluation. This study used test subjects by carrying out validity tests on media experts, material experts, learning experts, and the responses of ten fifth-grade elementary school students—data collection using a questionnaire instrument. Research data were analyzed through descriptive quantitative and descriptive qualitative. The results of the media expert validator are categorized as very valid. The results of the material expert validator are classified as very accurate. The results of the expert learning validator are categorized as very accurate as well as the results of the responses of ten fifth-grade elementary school students who were categorized as very valid. The overall results of the validator test are can be used as an alternative for teachers in adding a variety of learning media, it can increase understanding of concepts because the media helps students in improving scientific attitudes, remembering material and learning is more fun in class V SD. Keywords: ADDIE, media expert, scientific literacy, natural science.

show abstract

“…In another study [18], each comic character forms the strip, which is represented as an activity, and the overall visualization was created by recording the provenance graphs. Data citation and provenance relationship, distinguished by a certain model to represent views of the citation, and their relation in query construct is presented in [19], followed by another paper, where authors presented an application that uses the combination of the provenance values and trust values of other observations to personalize their website content, hence creating a two-leveled model, by including provenance trust and observations of the system as well [20].…”

Section: Publications' Review and Research Findingsmentioning

confidence: 99%

Provenance and social network analysis for recommender systems: a literature review

Rrmoku

Selimi²,

Ahmedi³

2022

IJECE

View full text Add to dashboard Cite

<span>Recommender systems (RS) and their scientific approach have become very important because they help scientists find suitable publications and approaches, customers find adequate items, tourists find their preferred points of interest, and many more recommendations on domains. This work will present a literature review of approaches and the influence that social network analysis (SNA) and data provenance has on RS. The aim is to analyze differences and similarities using several dimensions, public datasets for assessing their impacts and limitations, evaluations of methods and metrics along with their challenges by identifying the most efficient approaches, the most appropriate assessment data sets, and the most appropriate assessment methods and metrics. Hence, by correlating these three fields, the system will be able to improve the recommendation of certain items, by being able to choose the recommendations that are made from the most trusted nodes/resources within a social network. We have found that content-based filtering techniques, combined with term frequency-inverse document frequency (TF-IDF) features are the most feasible approaches when combined with provenance since our focus is to recommend the most trusted items, where trust, distrust, and ignorance are calculated as weight in terms of the relationship between nodes on a network.</span>

show abstract

Visualizing the Provenance of Personal Data Using Comics

Cited by 9 publications

References 35 publications

Provenance Data Management in Health Information Systems: A Systematic Literature Review

Provenance Data Management in Health Information Systems: A Systematic Literature Review

Pengembangan Komik dengan Pendekatan Culturally Responsive Teaching untuk Menumbuhkan Literasi Sains pada Kelas V SDN Kalicari 01 Semarang

Provenance and social network analysis for recommender systems: a literature review

Contact Info

Product

Resources

About