prikaz prve stranice dokumenta Data Quality in the Context of Longitudinal Research Studies
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Scientific paper - Preliminary note / Short communication
Data Quality in the Context of Longitudinal Research Studies
In: NFuture2019: Knowledge in the Digital Age. / Bago, Petra; Hebrang Grgić, Ivana; Ivanjko, Tomislav; Juričić, Vedran; Miklošević, Željka; Stublić, Helena (Ed.). Zagreb: Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press, 2019. pp. 98-104. https://doi.org/10.17234/INFUTURE.2019.12
Carić, Tonko; Kocijan, Kristina

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Carić, T. & Kocijan, K. (2019). Data Quality in the Context of Longitudinal Research Studies. In P. Bago, (Ed.), I. Hebrang Grgić, (Ed.), T. Ivanjko, (Ed.), V. Juričić, (Ed.), Ž. Miklošević, (Ed.), H. Stublić, (Ed.), NFuture2019: Knowledge in the Digital Age (pp. 98-104). Zagreb: Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press. doi: 10.17234/INFUTURE.2019.12

Carić, Tonko and Kristina Kocijan. "Data Quality in the Context of Longitudinal Research Studies." NFuture2019: Knowledge in the Digital Age, edited by Petra Bago, edited by Ivana Hebrang Grgić, edited by Tomislav Ivanjko, edited by Vedran Juričić, edited by Željka Miklošević, edited by Helena Stublić, Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press, 2019, pp. 98-104. https://urn.nsk.hr/urn:nbn:hr:131:091189

Carić, Tonko and Kristina Kocijan. "Data Quality in the Context of Longitudinal Research Studies." In NFuture2019: Knowledge in the Digital Age, 98-104. Zagreb: Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press, 2019. Accessed 2024 April 20. https://urn.nsk.hr/urn:nbn:hr:131:091189

Carić, T. and Kocijan, K. (2019) 'Data Quality in the Context of Longitudinal Research Studies', in Bago, P. (ed.), Hebrang Grgić, I. (ed.), Ivanjko, T. (ed.), Juričić, V. (ed.), Miklošević, Ž. (ed.), Stublić, H. (ed.), NFuture2019: Knowledge in the Digital Age, Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press, Zagreb, pp. 98-104. Available at: https://urn.nsk.hr/urn:nbn:hr:131:091189 (Accessed 20 April 2024)

Carić T, Kocijan K. Data Quality in the Context of Longitudinal Research Studies. In: P. Bago, ed., I. Hebrang Grgić, ed., T. Ivanjko, ed., V. Juričić, ed., Ž. Miklošević, ed., H. Stublić, ed. NFuture2019: Knowledge in the Digital Age. Zagreb: Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press; 2019. Pp. 98-104. [cited 2024 April 20] Available at: https://urn.nsk.hr/urn:nbn:hr:131:091189

T. Carić and K. Kocijan, "Data Quality in the Context of Longitudinal Research Studies", NFuture2019: Knowledge in the Digital Age, P. Bago et al., Eds. Zagreb: Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press, 2019. [Online] Available at: https://urn.nsk.hr/urn:nbn:hr:131:091189 [Accessed: 20 April 2024]

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Metadata
Title (english)Data Quality in the Context of Longitudinal Research Studies
AuthorTonko Carić
AuthorKristina Kocijan
EditorPetra Bago
EditorIvana Hebrang Grgić
EditorTomislav Ivanjko
EditorVedran Juričić
EditorŽeljka Miklošević
EditorHelena Stublić
Author's institutionUniversity of Zagreb
Faculty of Humanities and Social Sciences
(Department of information and Communication sciences)
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract (english)
This paper discusses the concept of data quality in the context of longitudinal research. By deconstructing quality assurance process and data collection strategies through a case study of the “Croatian Birth Cohort Study“, we try to define causes and sources of poor data quality in the context of longitudinal studies. Besides the problems discussed throughout the known literature (panel conditioning, sample attrition, recall bias, temporal and financial demands), we introduce singlesource problems, multi-source problems, security problems, design questionnaire problems and QA workflow problems as important aspects in the domain of the possible sources of errors. Additionaly we propose models for eliminating the errors through prevention and detection in order to improve data quality.
Keywords (english)
Languageenglish
Publication typeScientific paper - Preliminary note / Short communication
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Publication titleNFuture2019: Knowledge in the Digital Age
Numberingpp. 98-104
e-ISSN2706-3518
DOIhttps://doi.org/10.17234/INFUTURE.2019.12
URN:NBNurn:nbn:hr:131:091189
Publication2019-11
ConferenceTitle: INFuture2019: Knowledge in the Digital Age
Acronym: INFuture2019
Location: Zagreb, Croatia
Organizer: Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb
Start date: 2019-11-21
End date: 2019-11-22
Assembly type: Lecture
Document URLhttps://infoz.ffzg.hr/infuture/images/papers/INFuture%202019%20Proceedings.pdf
Type of resourceText
PublisherDepartment of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb and FF press
Publishing placeZagreb
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-11-26 12:40:24