References
- Almaleh, A, et al. 2019. Align My Curriculum: A Framework to Bridge the Gap between Acquired University Curriculum and Required Market Skills. Sustainability, 11(9): 2607. DOI: 10.3390/su11092607
- Bloom, BS. 1956. Taxonomy of educational objectives: The classification of educational goals. New York: David McKay Company.
- Boselli, R, et al. 2018. WoLMIS: a labor market intelligence system for classifying web job vacancies. Journal of Intelligent Information Systems, 51(3): 477–502. DOI: 10.1007/s10844-017-0488-x
- Breitfuss, G, et al. 2019. The Data-Driven Business Value Matrix-A Classification Scheme for Data-Driven Business Models. Bled eConference, 19. DOI: 10.18690/978-961-286-280-0.42
- Cao, L. 2017. Data science: challenges and directions. Communications of the ACM, 60(8): 59–68. DOI: 10.1145/3015456
- Dadzie, AS, et al. 2018. Structuring visual exploratory analysis of skill demand. Journal of Web Semantics, 49: 51–70. DOI: 10.1016/j.websem.2017.12.004
- Debortoli, S, Müller, O and vom Brocke, J. 2014. Comparing business intelligence and big data skills. Business & Information Systems Engineering, 6(5): 289–300. DOI: 10.1007/s12599-014-0344-2
- Djumalieva, J, Lima, A and Sleeman, C, et al. 2018. Classifying occupations according to their skill requirements in job advertisements. Economic Statistics Centre of Excellence Discussion Paper, 4: 2018.
- Donoho, D. 2017. 50 years of data science. Journal of Computational and Graphical Statistics, 26(4): 745–766. DOI: 10.1080/10618600.2017.1384734
- Harper, R. 2012. The collection and analysis of job advertisements: A review of research methodology. Library and Information Research, 36(112): 29–54. DOI: 10.29173/lirg499
- Hattingh, M, et al. 2019. Data Science Competency in Organisations: A Systematic Review and Unified Model. Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019, 1–8. DOI: 10.1145/3351108.3351110
- Khaouja, I, et al. 2019. Building a soft skill taxonomy from job openings. Social Network Analysis and Mining, 9(1): 1–19. DOI: 10.1007/s13278-019-0583-9
- Khobreh, M, et al. 2015. An ontology-based approach for the semantic representation of job knowledge. IEEE Transactions on Emerging Topics in Computing, 4(3): 462–473. DOI: 10.1109/TETC.2015.2449662
- Von Konsky, B, Miller, C and Jones, A. 2016. The skills framework for the information age: Engaging stakeholders in curriculum design. Journal of Information Systems Education, 27(1): 37.
- Lima, A, Bakhshi, B, et al. 2018. Classifying occupations using web-based job advertisements: an application to STEM and creative occupations. Economic Statistics Centre of Excellence Discussion Paper, 8: 2018.
- Mandinach, EB, et al. 2015. Ethical and appropriate data use requires data literacy. Phi Delta Kappan, 96(5): 25–28. DOI: 10.1177/0031721715569465
- Murawski, M and Bick, M. 2017. Demanded and imparted big data competences: towards an integrative analysis. In Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal,
June 5–10, 2017 , 1375–1390. - National Academies of Sciences, Engineering, Medicine (NASEM). 2018.
Envisioning the data science discipline: the undergraduate perspective: interim report . National Academies Press. - Ridsdale, C, Rothwell, J, Smit, M, Ali-Hassan, H, Bliemel, M, Irvine, D, Kelley, D, Matwin, S and Wuetherick, B. 2015.
Strategies and best practices for data literacy education. Knowledge synthesis report . SSHRC. DOI: 10.13140/RG.2.1.1922.5044 - Saltz, J, Armour, F and Sharda, M. 2018. Data science roles and the types of data science programs. Communications of the Association for Information Systems, 43(1): 33. DOI: 10.17705/1CAIS.04333
- SFIA. 2018. The global skills and competency framework for a digital world. Available at:
https://sfia-online.org/en/sfia-7 [Last accessed on 4 April 2021]. - Shirani, A. 2016. Identifying Data Science and Analytics Competencies Based on Industry Demand. Issues in Information Systems, 17(4).
- Sibarani, E, et al. 2020. Skills and Recruitment Ontology.
- Sibarani, EM, et al. 2017. Ontology-guided job market demand analysis: a cross-sectional study for the data science field. Proceedings of the 13th International Conference on Semantic Systems, 25–32. DOI: 10.1145/3132218.3132228
- Silveira, CC, et al. 2020. What is a Data Scientist? Analysis of core soft and technical competencies in job postings. Revista Inovação, Projetos e Tecnologias–IPTEC, 8(1): 25–39. DOI: 10.5585/iptec.v8i1.17263
- Wowczko, IA. 2015. Skills and vacancy analysis with data mining techniques. Informatics, 2(4): 31–49. DOI: 10.3390/informatics2040031
- Zhao, M, et al. 2015. SKILL: A system for skill identification and normalization. Proceedings of the twenty-ninth AAAI conference on artificial intelligence, 4012–4017. DOI: 10.1609/aaai.v29i2.19064
