Evaluation of the Impact of the Colombian Scientific Productivity on the Fulfillment of the Sustainable Development Goals

  • Olga Lucía OSTOS-ORTIZ Research University Santo Tomás, Colombia
  • Rafael RENTERÍA-RAMOS National Open and Distance University UNAD, Colombia
  • Favio CALA-VITERY University Jorge Tadeo Lozano, Colombia


This research presents the development of an instrument for the evaluation of the contributions of scientific production in Colombia to the development of the main needs of the Sustainable Development Goals (SDG) throughout the country. A data set of national and international science and technology repositories was configured, including those recognized for hosting products highly related to the topics required by the SDGs. Afterward, a topic model was built, in which for each of the sources considered in each SDG, the importance of the number of topics or categories and the distribution of the concepts in each of them was evaluated based on indicators such as perplexity and coherence. Among the most important results, the synchronization of the scientific products related to the objectives “Fin de la pobreza”, “Cero Hambre” and “Salud y Bienestar” stands out, however, despite this decisive result for the fulfillment of the SDGs, the lack of scientific development throughout the national territory limits the impact of the results for the attainment of the agenda for 2030.


[1] Alkire, S., et al. 2015. Multidimensional poverty measurement and analysis. Oxford University Press, USA.
[2] Blei, DM, Jordan, MI. Modeling annotated data. Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval 2003, 127-134.
[3] Blei, DM, Ng, AY, Jordan, MI. 2003. Latent Dirichlet Allocation. Journal of Machine Learning Research, 3: 993-1022.
[4] Blesh, J., et al. 2019. Development pathways toward “zero hunger”. World Development, 118: 1-14.
[5] Bornmann, L, et al. 2020. “Efficiency of universities and research-focused institutions worldwide: An empirical DEA investigation based on institutional publication numbers and estimated academic staff numbers”. CESifo working paper no. 8157 2020.
[6] Cuesta, J., and Pico, J. 2020. The gendered poverty effects of the COVID-19 pandemic in Colombia.The European journal of development research, 32(5): 1558-1591.
[7] Deerwester, S, et al. 1990. Indexing by Latent Semantic Analysis. J Am Soc Inform Sci., 41 (6): 391-407. DOI: 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9
[8] Diderichsen, F., Hallqvist, J. and Whitehead, M. 2019. Differential vulnerability and susceptibility: how to make use of recent development in our understanding of mediation and interaction to tackle health inequalities. International Journal of Epidemiology, 48(1): 268-274.
[9] Duran, D. C., Artene, A., Gogan, L. M., and Duran, V. 2015. The objectives of sustainable development-ways to achieve welfare. Procedia Economics and Finance, 26: 812-817.
[10] Griffiths, T.L. and Steyvers, M. 2004. Finding scientific topics. Proc Natl Acad Sci U S A, 101(Suppl 1): 5228-5235.
[11] Hofmann, T. 1999. Probabilistic latent semantic indexing. Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval. 50-57.
[12] Hofmann, T. 2001. Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42 (1-2): 177-196.
[13] Hong, L., Frias-Martinez, E., and Frias-Martinez, V. 2016. Topic models to infer socio-economic maps. In Thirtieth AAAI Conference on Artificial Intelligence.
[14] Jacobi, C., Van Atteveldt, W. and Welbers, K. 2016. Quantitative analysis of large amounts of journalistic texts using topic modelling. Digital journalism, 4(1): 89-106.
[15] Khanal, U., et al. 2021. Smallholder farmers’ adaptation to climate change and its potential contribution to UN’s sustainable development goals of zero hunger and no poverty. Journal of Cleaner Production, 281, 124999.
[16] Li, X. and Lei, L. 2021. A bibliometric analysis of topic modelling studies (2000–2017). Journal of Information Science, 47(2): 161-175.
[17] Manzano-Nunez, R., et al. 2022. Emergency surgery workforce and its inverse relationship with multidimensional poverty in Colombia. European Journal of Trauma and Emergency Surgery, 48(2): 1159-1165.7
[18] Mei, Q., Shen, X., and Zhai, C. 2007. Automatic labeling of multinomial topic models. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 490-499).
[19] Palma, H. G. H., Núñez, W. N. and Cárdenas, M. J. 2019. Sistema de salud colombiano: integración para la calidad. Criterio Libre, 18(31): 149-163.
[20] Paul, M. J., and Dredze, M. 2014. Discovering health topics in social media using topic models. PloS one, 9(8), e103408.
[21] Pinilla-Roncancio, M. 2018. The reality of disability: Multidimensional poverty of people with disability and their families in Latin America. Disability and health journal, 11(3): 398-404.
[22] Ramage, D., et al. (2009, December). Topic modeling for the social sciences. In NIPS 2009 workshop on applications for topic models: text and beyond (Vol. 5, pp. 1-4).
[23] Ramírez, J. M., Díaz, Y., and Bedoya, J. G. 2017. Property tax revenues and multidimensional poverty reduction in Colombia: A spatial approach. World Development, 94: 406-421.
[24] Rentería-Ramos, R.; Hurtado-Heredia, R. and Urdinola, B.P. 2019. Morbi-Mortality of the Victims of Internal Conflict and Poor Population in the Risaralda Province, Colombia. Int. J. Environ. Res. Public Health, 16, 1644. DOI: https://doi.org/10.3390/ijerph16091644
[25] Rogers, S., Girolami, M., Campbell, C. and Breitling, R. 2005. The latent process decomposition of cDNA microarray data sets. IEEE/ACM transactions on computational biology and bioinformatics, 2(2): 143-156.
[26] Roncancio, D.J., Cutter, S.L. and Nardocci, A. C. 2020. Social vulnerability in Colombia. International Journal of Disaster Risk Reduction, 50, 101872.
[27] Sunderland, T. et al. 2019. SDG2: Zero hunger: Challenging the hegmony of monoculture agriculture for forests and people. Sustainable Development Goals: Their Impacts on Forests and People; Pierce Colfer, CJ, Winkel, G., Galloway, G., Pacheco, P., Katila, P., de Jong, W., Eds, 48-71.
[28] DNP, Documento CONPES 4069 Política Nacional de Ciencia, Tecnología e Innovación 2022 - 2031. Available at: https://www.dnp.gov.co/Paginas/CONPES-aprobo-politica-de-ciencia-tecnologia-e-innovacion-CTI.aspx
[29] Instituto Complutense de Estudios Internacionales ICEI. 2020. Ciencia, tecnología e innovación para el cumplimiento de los objetivos de desarrollo sostenible en Iberoamérica. Available at: https://www.ucm.es/data/cont/media/www/27289//Relatori%CC%81a-CTI_12enero_2020.pdf
[30] Unesco (2015). La Agenda del desarrollo sostenible 2030. Available at: https://es.unesco.org/creativity/sites/creativity/files/247785sp_1_1_1.compressed.pdf
How to Cite
OSTOS-ORTIZ, Olga Lucía; RENTERÍA-RAMOS, Rafael; CALA-VITERY, Favio. Evaluation of the Impact of the Colombian Scientific Productivity on the Fulfillment of the Sustainable Development Goals. Journal of Environmental Management and Tourism, [S.l.], v. 13, n. 5, p. 1512 - 1519, sep. 2022. ISSN 2068-7729. Available at: <https://journals.aserspublishing.eu/jemt/article/view/7220>. Date accessed: 02 oct. 2022. doi: https://doi.org/10.14505/jemt.v13.5(61).26.