Megatrend and Intervention Impact Analyzer for Jobs: A Visualization Method for Labor Market Intelligence

Open access


This article presents a visual method for representing the complex labor market internal structure from the perspective of similar occupations based on shared skills; and a prototype tool for interacting with the visualization, together with an extended description of graph construction and the necessary data processing for linking multiple heterogeneous data sources. Since the labor market is not an isolated phenomenon and is constantly impacted by external trends and interventions, the presented method is designed to enable adding extra layers of external information. For instance, what is the impact of a megatrend or an intervention on the labor market? Which parts of the labor market are the most vulnerable to an approaching megatrend or planned intervention? A case study analyzing the labor market together with the megatrend of job automation and computerization is presented. The source code of the prototype is released as open source for repeatability.

Amar, R., J. Eagan, and J. Stasko. 2005. “Low-level components of analytic activity in information visualization.” IEEE Symposium on Information Visualization, 2005. INFOVIS 2005, October 23–25 2005. 111–117. Minneapolis, MN, U.S.A. IEEE.

Arntz, M., T. Gregory, and U. Zierahn. 2016. “The Risk of Automation for Jobs in OECD Countries.” OECD Social, Employment and Migration Working Papers. Doi:

Battista, G.D., P. Eades, R. Tamassia, and I.G. Tollis. 1998. Graph Drawing: Algorithms for the Visualization of Graphs. Englewood Cliffs, NJ: Prentice Hall.

Bostock, M., V. Ogievetsky, and J. Heer. 2011. “D3: Data-Driven Documents.” IEEE transactions on visualization and computer graphics (Proc. InfoVis). Available at: (accessed April 2017).

Briscoe, G. and C. Mulligan. 2014. “Digital Innovation”: The Hackathon Phenomenon. Creative works London Working Paper. Queen Mary University of London. Available at: (accessed December 2017).

Burt, R.S. 1984. “Network items in the general social survey.” Social Networks 6: 293–339. Doi:

European Commission. 2013. ESCO – European Classification of Skills/Competences, Qualifications and Occupations – The first public release. Luxembourg: Publications Office of the European Union. Available at: (accessed April 2017).

European Commission. 2017a. Description of the European Big Data Hackathon. Eurostat. Available at: (accessed December 2017).

European Commission. 2017b. European Big Data Hackathon. Eurostat. Available at: (accessed December 2017).

European Commission. 2017c. Hackathon Data Catalogue. Eurostat. Available at: (accessed December 2017).

European Commission. 2017d. Panel of evaluators. Eurostat. Available at: (accessed December 2017).

Frey, C.B. and M.A. Osborne. 2016. “The future of employment: How susceptible are jobs to computerisation?” Technological Forecasting and Social Change 114: 254–280. Doi:

Frey, C.B. and M.A. Osborne. 2018. Automation and the Future of Work – Understanding the Numbers. Available at: (accessed April 2018).

Ghoniem, M., J.D. Fekete, and P. Castagliola. 2005. “On the readability of graphs using node-link and matrix-based representations: a controlled experiment and statistical analysis.” Information Visualization 4(2): 114–135. Doi:

Hardy, W., D. Autor, and D. Acemoglu. 2016. “Occupation classifications crosswalks – from O*NET- SOC to ISCO.” [Online]. Available at: (accessed April 2017).

Hu, Y. 2005. “Efficient, high-quality force-directed graph drawing.” Mathematica Journal 10(1): 37–71. Available at: (accessed October 2018).

Huai, Y., A. Chauhan, A. Gates, G. Hagleitner, E.N. Hanson, O. O’Malley, J. Pandey, Y. Yuan, R. Lee, and X. Zhang. 2014. “Major technical advancements in apache hive.” In Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, June 2014: 1235–1246. New York. NY, U.S.A., ACM.

International Labour Organization. 2008. ISCO – International Standard Classification of Occupations. Switzerland Geneva: International Labour Office. Available at: (accessed April 2017).

Jones, C. 1997. The Year 2000 Software Problem: Quantifying the Costs and Assessing the Consequences. ACM Press/Addison-Wesley Publishing Co. Available at: (accessed December 2017).

Kandel, S., J. Heer, C. Plaisant, J. Kennedy, F. van Ham, N.H. Riche, C. Weaver, B. Lee, D. Brodbeck, and P. Buono. 2011. “Research directions in data wrangling: Visualizations and transformations for usable and credible data.” Information Visualization 10(4) : 271–288. Doi:

LeCun, Y., Y. Bengio, and G. Hinton. 2015. “Deep learning.” Nature 521(7553): 436–444. Doi:

Lerman, R.I. and S.R. Schmidt. 2005. Trends and challenges for work in the 21st century. Future Work, US Dept. of Labor, The Urban Institute, Washington DC. Available at: (accessed April 2017).

Merluzzi, J. and R.S. Burt. 2013. “How many names are enough? Identifying network effects with the least set of listed contacts.” Social Networks 35(3): 331–337. Doi:

Mitchell, T. and E. Brynjolfsson. 2017. “Track how technology is transforming work.” Nature 544(7650): 290. DOI:

Mogensen, K.A., K. Brown, A.D. Baedkel, K. Gu, M. Fert-Malka, N.T. Hemmingsen, L. Borgstrom-Hansen, C.S. Petersen, and O. Denysenko. 2014. Trends for Tomorrow. Member’s Report 4/2014. Copenhagen Institute for Futures Studies. Available at: (accessed October 2018).

Opik, R. 2017a. “The prototype.” Available at: (accessed October 2018).

Opik, R. 2017b. “The source code of the prototype.” Available at: (accessed October 2018).

Peixoto, T.P. 2014. “The graph-tool python library.” figshare. Doi:

Smith, G. 2010. PostgreSQL 9.0: High Performance. Packt Publishing Ltd.

Stasko, J. 2014. “Value-driven evaluation of visualizations.” In Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization. (pp. 46–53). ACM.

Thusoo, A., J.S. Sarma, N. Jain, Z. Shao, P. Chakka, S. Anthony, H. Liu, P. Wyckoff, and R. Murthy. 2009. “Hive: a warehousing solution over a map-reduce framework.” Proceedings of the VLDB Endowment 2(2): 1626–1629. Doi:

West, D.B. 2001. Introduction to Graph Theory. New York: Prentice Hall.

Wieling, M., and L. Borghans. 2001. “Descrepancies between supply and demand and adjustment processes in the labour market.” Labour 15(1): 33–56. Doi:

U.S. Bureau of Labor Statistics. 2010. Standard Occupational Classification. Washington DC: Bureau of Labor Statistics. Available at: (accessed April 2018).

U.S. Department of Labor/Employment and Training Administration. 2010. The O*NETSOC Taxonomy. Available at: (accessed December 2017).

Zukin, S. and M. Papadantonakis. 2017. “Hackathons as Co-optation Ritual: Socializing Workers and Institutionalizing Innovation in the ‘New’ Economy.” In Precarious Work. (pp. 157–181). Emerald Publishing Limited.

Journal of Official Statistics

The Journal of Statistics Sweden

Journal Information

IMPACT FACTOR 2017: 0.662
5-year IMPACT FACTOR: 1.113

CiteScore 2017: 0.74

SCImago Journal Rank (SJR) 2017: 1.158
Source Normalized Impact per Paper (SNIP) 2017: 0.860


All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 450 450 120
PDF Downloads 355 355 63