This study aims to explore the influence of personal factors on information security awareness (ISA) within individuals in an organizational context. With the rise in cybersecurity threats, understanding the personal factors that contribute to an individual’s awareness and behavior regarding information security has become crucial. We propose a conceptual model that identifies key personal factors, including personality traits, prior experience, education, and motivation, that impact ISA. Using a survey of 300 individuals from various organizations, the study empirically tests these relationships. The findings suggest that education, personality traits, and personal motivation significantly influence information security awareness. These results offer practical insights for organizations aiming to improve information security practices through targeted awareness programs.

Information security awareness, personal factors, cybersecurity

Burrows T. Sharing humanities data for e-research: conceptual and technical issues. In: Thieberger N (ed.) Sustainable data from digital research: humanities perspectives on digital scholarship. Melbourne, VIC, Australia: Custom Book Centre, 2011, pp. 171–185.

Van Dijk TA. Macrostructures: an interdisciplinary study of global structures in discourse, interaction, and cognition. Hillsdale, NJ: Lawrence Erlbaum, 1980.

Superceanu R. The rhetoric of scientific articles: a genere study. Timişoara: Orizonturi Universitare, 1998.

De Waard A, Breure L, Kircz J, et al. Modeling rhetoric in scientific publications. In: International conference on multidisciplinary information sciences and technologies, InSciT2006, Barcelona, Spain, 25–28 October 2006.

De Waarde A. A pragmatic structure for research articles. In: 2nd International conference on the pragmatic web, Tilburg, 22–23 October 2007.

Kando N. Text-level structure of research papers: implications for text-based information processing systems. In: Proceedings of the 19th annual BCS-IRSG colloquium on IR research, Aberdeen, 8–9 April 1997, pp. 68–81. New York: ACM.

Kando N. Text structure analysis as a tool to make retrieved documents sable. In: Proceedings of the 4th international workshop on information retrieval with Asian languages, Taipei, November 1999, pp. 126–135. Taipei: Academia Sinica.

Ko YM, Song IS. A study on the knowledge organizing system of research papers based on semantic relation of the knowledge structure. J Korean Soc Inf Manag 2011; 28(1): 145–170.

Song MS, Ko YM. A study on the metadata based on the semantic structure of the Korean studies research articles. J Korean Libr Inf Sci Soc 2015; 46(3): 277–299.

Ko YM, Seo TS, Lim TH. A study on metadata mapping for semantic interoperability. J Korean Soc Inf Manag 2007; 24(4): 223–238.

Chan M, Zeng L. Metadata interoperability and standardization: a study of methodology (part I) achieving interoperability at the schema level. D-Lib Mag 2006; 12(6), http://www.dlib.org/dlib/june06/chan/06chan.html

Seo TS. A guide to making data interoperable. Daejeon, South Korea: Korea Institute of Science and Technology Information, 2023.

ISO/IEC 11179-33. Information technology – metadata registries (MDR) – part 33: metamodel for data set registration, 2023.

Stigler J, Steiner E. GAMS – an infrastructure for the long-term preservation and publication of research data from the humanities. Mitt Ver Österr Bibl Bibl 2018; 71: 207.

Martin-Rodilla P, Gonzalez-Perez C. Metainformation scenarios in digital humanities: characterization and conceptual modelling strategies. Inf Syst 2019; 84: 29–48.

Zhao F. A systematic review of Wikidata in digital humanities projects. Digit Scholarsh Humanit 2023; 38(2): 852–874.

Kim J, Han Y, You W, et al. A study on the design of metadata for research data management in forestry engineering. J the Korean Soc Libr Inf Sci 2020; 54(4): 169–194.

Farnel S, Shiri A. Metadata for research data. In: DCMI’14: proceedings of the 2014 international conference on Dublin core and metadata applications, Austin, TX, 8–11 October 2017, pp. 74–82. Austin, TX: DCMI.

Gómez ND, Méndez E, Hernández-Pérez T. Social sciences and humanities research data and metadata: a perspective from thematic data repositories. Prof Inf 2016; 25(4): 545–555.

re3data.org – Registry of Research Data Repositories, https://doi.org/10.17616/R3D (2012, accessed 8 October 2024).

TTAK.KO-10.0976:2017. The integrated metadata for the scientific data.

DataCite metadata schema documentation for the publication and citation of research data and other research outputs, version 4.4, 2021, https://schema.datacite.org/meta/kernel-4.4/doc/DataCite-MetadataKernel_v4.4.pdf

ARCHE. A resource centre for humanities related research in Austria, https://arche.acdh.oeaw.ac.at/browser/ (2003, accessed 25 January 2024).

Humanities Commons. Commons Open Repository Exchange, https://hcommons.org/core (2016, accessed 25 January 2024).

Korea Research Memory, https://www.krm.or.kr/ (2007, accessed 26 June 2024).

University of Michigan. Inter-university Consortium for Political and Social Research, https://www.icpsr.umich.edu (2020, accessed 25 January 2024).

UKRI. UK Data Service, https://www.ukdataservice.ac.uk/ (2012, accessed 25 January 2024).

An BG, Ko YM. A study on the metadata based on the semantic structure of the humanities research articles for research data. J Korean BIBLIA Soc Libr Inf Sci 2022; 33(1): 345–369.