My role is to develop a research team focussing on intelligent data analysis. Throughout Kew's history we have assembled significant global-scale datasets: we are now using these as training data inputs for machine learning applications. In addition to these data resources, we also have scientific expertise to pose relevant questions, and to interpret and validate results. This research strand contributes to Kew's strategic priorities for science: "to curate and provide data-rich evidence from Kew’s unrivalled collections as a global asset for scientific research" - by providing more efficient data mobilisation and decision support.
I am currently working on a data mining research project using data from digitised herbarium specimen collections mobilised via the GBIF network and scientific name publication data from the International Plant Names Index. The products of this data mining research are used in two ways: to advance data understanding through the development of predictive models, and to facilitate data curation via efficiencies in digitisation and linking allied data. I have a background in scientific software development and am also interested in building open source tools and techniques to make data curation more efficient and to make research reproducible.
- BSc (Hons), Botany, University of London, 1995
- MSc, Computer Science, University of Kent, 1997
Nicolson, N. & Tucker, A., (2017)
Identifying Novel Features from Specimen Data for the Prediction of Valuable Collection Trips
In International Symposium on Intelligent Data Analysis (pp. 235-246). Springer, Cham. Available online
Nicolson, N., Challis, K., Tucker, A. & Knapp, S. (2017)
Impact of e-publication changes in the International Code of Nomenclature for algae, fungi and plants (Melbourne Code, 2012) - did we need to “run for our lives”?
BMC evolutionary biology 17(1), p.116
Güntsch, A., Hyam, R., Hagedorn, G., Chagnoux, S., Röpert, D., Casino, A., Droege, G., Glöckler, F., Gödderz, K., Groom, Q., Hoffmann, J., Holleman, A., Kempa, M., Koivula, H., Marhold, K., Nicolson, N., Smith, V. S. & Triebel, D. (2017)
Actionable, long-term stable and semantic web compatible identifiers for access to biological collection objects
Database 2017(1). Available online
Lughadha, E. N., Govaerts, R., Belyaeva, I., Black, N., Lindon, H., Allkin, R., Magill, R. E. & Nicolson, N. (2016)
Counting counts: revised estimates of numbers of accepted species of flowering plants, seed plants, vascular plants and land plants with a review of other recent estimates
Phytotaxa 272(1), 82–88. Available online
Vos, R., Biserkov, J., Balech, B., Beard, N., Blissett, M., Brenninkmeijer, C., van Dooren, T., Eades, D., Gosline, G., Groom, Q., Hamann, T., Hettling, H., Hoehndorf, R., Holleman, A., Hovenkamp, P., Kelbert, P., King, D., Kirkup, D., Lammers, Y., DeMeulemeester, T., Mietchen, D., Miller, J., Mounce, R., Nicolson, N., Page, R., Pawlik, A., Pereira, S., Penev, L., Richards, K., Sautter, G., Shorthouse, D., Tähtinen, M., Weiland, C., Williams, A. & Sierra, S. (2014)
Enriched biodiversity data as a resource and service
Biodiversity Data Journal 2: e1125. Available online