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An ontological model to support citizen science in the field of invasive species research Cover

An ontological model to support citizen science in the field of invasive species research

Open Access
|Jun 2022

References

  1. [1]. Groom, Q.J.; Adriaens, T.; Desmet, P.; Simpson, A.; De Wever, A.; Bazos, I.; Cardoso, A. C.; Charles, L.; Christopoulou, A.; Gazda, A.; Helmisaari, H.; Hobern, D.; Josefsson, M.; Lucy, F.; Marisavljevic, D.; Oszako, T.; Pergl, J.; Petrovic-Obradovic, O.; Prévot, C.; Ravn H-P.; Richards, G.; Roques, A.; Roy, H. E.; Rozenberg, M-AA.; Scalera, R.; Tricarico, E.; Trichkova, T.; Vercayie, D.; Zenetos, A.;Vanderhoeven, S., Seven Recommendations to Make Your Invasive Alien Species Data More Useful. Front. Appl. Math. Stat., 2017, 3, 13. DOI: 10.3389/fams.2017.00013.
  2. [2]. Bordogna, G.; Fugazza, C.; Oggioni, A., VGI Imperfection in Citizen Science Projects and Its Representation and Retrieval Based on Fuzzy Ontologies and Level-Based Approximate Reasoning. 2018, DOI: 10.1007/978-3-319-70878-2_10.
  3. [3]. Eitzel, M.; Cappadonna, J.; Lang, C.; Duerr, R.; Virapongse, A.; West, S.; Maximillian-Kyba, C.; Bowser, A.; Cooper, C.; Sforzi, A.; Metcalfe, A.; Harris, E.; Thiel, M.; Haklay, M.; Ponciano, L.; Roche, J.; Ceccaroni, L.; Shilling, F.; Dörler, D.; Heigl, F.; Kiessling, T.; Davis, B.; Jiang. Q. Citizen Science Terminology Matters: Exploring Key Terms. Citizen Science: Theory and Practice, 2017, 2(1), 1–20, DOI: https://doi.org/10.5334/cstp.96.
  4. [4]. McGeoch, M.; Spear, D.; Kleynhans, E.; Marais, E., Uncertainty in invasive alien species listing. Ecological applications: a publication of the Ecological Society of America. 2012, 22, 959-971. DOI: 10.2307/23213930.
  5. [5]. Lemmens R.; Falquet G.; Tsinaraki C.; Klan F.; Schade S.; Bastin L.; Piera J.; Antoniou V.; Trojan J.; Ostermann F.; Ceccaroni L., A Conceptual Model for Participants and Activities in Citizen Science Projects. In: Vohland, K. et al. (eds). The Science of Citizen Science. Springer, Cham. 2021, DOI: https://doi.org/10.1007/978-3-030-58278-4_9.
  6. [6]. Musen, M. A., The Protégé project: A look back and a look forward. AI Matters. Association of Computing Machinery Specific Interest Group in Artificial Intelligence, 2015, 1(4), DOI: 10.1145/2557001.25757003.
  7. [7]. Wagenknecht, K.; Woods, T,; García Sanz, F.; Gold, M,; Bowser, A.; Rüfenacht, S.; Ceccaroni, L.; Jaume Piera, J., EU-Citizen. Science: A Platform for Mainstreaming Citizen Science and Open Science in Europe. Data Intelligence, 2021, 3(1), 136–149. DOI: https://doi.org/10.1162/dint_a_00085.
  8. [8]. Sharma, N.; Greaves, S.; Siddharthan, A.; Anderson, H. B.; Robinson, A.; Colucci-Gray, L.; Wibowo, A. T.; Bostock, H.; Salisbury, A.; Roberts, S.; Slawson, D.; van der Wal, R., From citizen science to citizen action: analysing the potential for a digital platform to cultivate attachments to nature. JCOM, 2019, 18 (01), A07. https://doi.org/10.22323/2.18010207.
  9. [9]. de Sherbinin, A.; Bowser, A.; Chuang, T-R.; Cooper, C;. Danielsen, F.; Edmunds, R.; Elias, P.; Faustman, E.; Hultquist, C.; Mondardini, R.; Popescu, I.; Shonowo, A.; Sivakumar, K., The Critical Importance of Citizen Science Data. Front. Clim., 2021, 3, 650760. DOI: 10.3389/fclim.2021.650760.
  10. [10]. Beck, H.; Morgan, K.; Jung, Y.; Grunwald, S.; Kwon, H.; Wu, J., Ontology-based simulation in agricultural systems modeling. Agricultural Systems. 2010, 103, 463-477. DOI: 10.1016/j.agsy.2010.04.004.
  11. [11]. Tengö, M.; Austin, B. J.; Danielsen, F.; Fernández-Llamazares, A., Creating Synergies between Citizen Science and Indigenous and Local Knowledge, BioScience, 2021, 71(5), 503–518, DOI: https://doi.org/10.1093/biosci/biab023.810699633986633
  12. [12]. Ahsan, M.; Motla, Y. H.; Asim, M., Knowledge modeling fore-agriculture using ontology. International Conference on Open Source Systems & Technologies, 2014, 112-122, DOI: 10.1109/ICOSST.2014.7029330.
  13. [13]. Goldstein, A.; Fink, L.; Ravid, G., A Framework for Evaluating Agricultural Ontologies. Sustainability. 2021, 13(11), 6387. DOI: https://doi.org/10.3390/su13116387.
  14. [14]. Rodríguez-García, M. Á.; García-Sánchez, F., CropPestO: An Ontology Model for Identifying and Managing Plant Pests and Diseases. In: Valencia-García, R.; Alcaraz-Marmol, G.; Del Cioppo-Morstadt, J.; Vera-Lucio, N.; Bucaram-Leverone, M. (eds) Technologies and Innovation. CITI 2020, Communications in Computer and Information Science, vol. 1309. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-62015-8_2.
  15. [15]. Bonacin, R.; Fernanda, O.; Pierozzi, I., Ontology models of the impacts of agriculture and climate changes on water resources: Scenarios on interoperability and information recovery, Future Generation Computer Systems. 2016, 54, 423–434, DOI: https://doi.org/10.1016/j.future.2015.04.010.
DOI: https://doi.org/10.2478/asn-2022-0003 | Journal eISSN: 2603-347X | Journal ISSN: 2367-5144
Language: English
Page range: 23 - 32
Published on: Jun 18, 2022
Published by: Konstantin Preslavski University of Shumen
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Radoslav Milchev, Galin Milchev, Rumen Tomov, published by Konstantin Preslavski University of Shumen
This work is licensed under the Creative Commons Attribution 3.0 License.