Abstract
Atmospheric electric fields (AEFs) are produced by both natural processes and electrical infrastructure and are increasingly recognized to influence and interfere with various organisms and biological processes, including human well-being. Atmospheric electric fields, in particular electromagnetic fields (EMFs), currently attract a lot of scientific attention due to emerging technologies such as 5G and satellite internet. However, a broader retrospective analysis of available data for both natural and artificial AEFs and EMFs is hampered due to a lack of a semantic approach, preventing data sharing and advancing our understanding of its intrinsic links. Therefore, here we create an ontology (ENET_Ont) for existing (big) data on AEFs within the context of biological systems that is derived from different disciplines that are distributed over many databases. Establishing an environment for data sharing provided by the proposed ontology approach will increase the value of existing data and facilitate reusability for other communities, especially those focusing on public health, ecology, environmental health, biology, climatology as well as bioinformatics.
Similar content being viewed by others
References
AEM (Atmospheric Electricity network), https://dataspace.atmospheric-electricity-net.eu/variables, Accesses 2.10.2020
Apollonio F, Liberti M, Paffi A, Merla C, Marracino P, Denzi A, Marino C, d’Inzeo G (May 2013) Feasibility for microwaves energy to affect biological systems via nonthermal mechanisms: a systematic approach. IEEE Transact Microwave Theory Techn 61(5):2031–2045. https://doi.org/10.1109/TMTT.2013.2250298
Bandeira J, et al., FOCA: a methodology for ontology evaluation, arXiv:1612.03353v2 [cs.AI] 2 Sep 2017
Barouki R, Audouze K, Coumoul X, Demenais F, Gauguier D (2018) Integration of human exposome with the human genome to advance medicine. Biochimie 152:155–158
Barry S, Michael A, Cornelius R, Jonathan B, William B, Ceusters W, Louis J (2007) Goldberg, et al.: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25:1251–1255
Bór J, Zelkó Z, Hegedüs T, Jäger Z, Mlynarczyk J, Popek M, Betz HD (2018) On the series of +CG lightning strokes in dancing sprite events. J Geophys Res: Atmos 123. https://doi.org/10.1029/2017JD028251
Boyles RR, Thessen AE, Waldrop A, Haendel MA (2019)Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67–74. https://doi.org/10.1016/j.cotox.2019.05.005
Card SK, Mackinlay JD, Shneiderman B (1999) Information visualization: using vision to think. Morgan-Kaufmann, San Francisco
Cheatham M et al. (2017) Special issue on ontology and linked data matching. pp 2. https://doi.org/10.3233/SW-160251
CHEBI, https://www.ebi.ac.uk/chebi/, Accessed 10.1.2020
Chi Ed H, Riedl JT (1998) An operator interaction framework for visualization systems. Symposium on Information Visualization (InfoVis ‘98), Research Triangle Park, North Carolina pp 63–70
Cifra M, Fields JZ, Farhadi A (2011) Electromagnetic cellular interactions. Prog Biophys Mol Biol 105(3):223–246. https://doi.org/10.1016/j.pbiomolbio.2010.07.003
Clarke D, Whitney H, Sutton G, Robert D (2013) Detection and learning of floral electric fields by bumblebees. Science 340(6128):66–69
Conceição R, Silva HG, Bennett A, Salgado R, Bortoli D, Costa MJ, Pereira MC (2018)High-frequency response of the atmospheric electric potential gradient under strong and dry boundary-layer convection. Bound-Layer Meteorol 166:69–81
Dagnino S, Macherone A (Editors) (2019) Unraveling the exposome, a practical view, ISBN 978-3-319-89320-4 ISBN 978-3-319-89321-1(eBook)https://doi.org/10.1007/978-3-319-89321-1, Springer
Dimitrievski A, Savoska S, Chorbev I, Ristevski B, Trajkovik V (2019) Data processing within ambient assisted living system, In IX International Conference on Applied Internet and Information Technologies (AIIT 2019), Zrenjanin, Serbia, pp. 65–69, ISBN 978-86-7672-327-0
ECA data, https://dataspace.atmospheric-electricity-net.eu/, Accessed 10.10.2019
ECA link, https://www.atmospheric-electricity-net.eu/. Accessed 28.9.2019
ECA-CP Electronet cost action – Common projects, https://atmospheric-electricity-net.eu/sites/default/files/2017-07/gapg3.pdf, Accessed 29.9.2019
ECA-LAD, Electronet cost action - List of available data, https://atmospheric-electricity-net.eu/node/113, Accessed 1.10.2019
El-Sappagh S, Kwak D, Ali F et al (2018) DMTO: a realistic ontology for standard diabetes mellitus treatment. J Biomed Semant 9:8. https://doi.org/10.1186/s13326-018-0176-y
(EMF DB) EMF Studies Database, http://ieee-emf.com/, Accessed 5.10.2019
EnvO, Environmental Ontology -http://www.ontobee.org/ontology/ENVO, https://www.ebi.ac.uk/ols/ontologies/envo. Accessed 21.1.2020
Fankam C. OntoDB2: Support of multiple ontology models within ontology based database, EDBT2008, Ph.D Workshop’08 March 25, 2008, Nantes, France, ACM 978-1-59593-926-5/08/0003
Fdez-Arroyabe P, Kourtidis K, Haldoupis C. et al (2020) Glossary on atmospheric electricity and its effects on biology. Int J Biometeorol. https://doi.org/10.1007/s00484-020-02013-9
Fernandez J et al (2018) Selenium at the redox interface of the genome, metabolome and exposome. Free Radic Biol Med 127:215–227
Ferrario R, Grȕninger M (eds) (2017) Applied ontology: a forward by the new Editors-in-Chief. Appl Ontol 12:1–4. https://doi.org/10.3233/AO-170178 IOS Press
Gawich M et al (2012) A methodology for ontology building. Int J Comput Appl 56(2):0975–8887
GLOCAEM (n.d.) https://glocaem.wordpress.com/, https://gtr.ukri.org/projects?ref=NE%2FN013689%2F1. Accessed 20 Dec 2019
GO, Gene Ontology, https://genome.cshlp.org/content/11/8/1425.short, Accessed 10.1.2020
Go Y-M, Jones DP (2014) Redox biology: interface of the exposome with the proteome, epigenome and genome. Redoc Biol 2:358–360
Greggers U, Koch G, Schmidt V, Dürr A, Floriou-Servou A, Piepenbrock D, Göpfert MC, Menzel R (2013) Reception and learning of electric fields in bees. Proc R Soc B Biol Sci 280(1759):20130528
Gruber Thomas R (1995) Toward principles for the design of ontologies used for knowledge sharing? Int J Hum Comput Stud 43:907–928
Haldoupis C (2018) Is there a conclusive evidence on lightning-related effects on sporadic E layers? J Atmos Sol Terr Phys 172:117–121
Hartman S. et al., Ontology consolidation in bioinformatics, In Proc. 7th Asia-Pacific Conference on Conceptual Modeling (APCCM 2010), Brisbane, Australia
Hayakawa M, Hattori K, Ando Y (2004) Natural electromagnetic phenomena and electromagnetic theory: a review. IEEJ Trans Fundam Mater 124(1):72–79. https://doi.org/10.1541/ieejfms.124.72
Househ M, Kushniruk AW, Borycki EM (eds) (2019) Big Data, Big Challenges: a healthcare perspective: background, issues, solutions and research. In: Martin-Sanchez F (ed) Big Data challenges from an integrative exposome/expotype perspective. Springer, pp 127–142
Hunting ER, Harrison RG, Bruder A, van Bodegom PM, van der Geest HG, Kampfraath AA, Vorenhout M, Admiraal W, Cusell C, Gessner MO (2019) Atmospheric electricity influencing biogeochemical processes in soils and sediments. Front Physiol. https://doi.org/10.3389/fphys.2019.00378
Hunting ER, Matthews J, de Arróyabe Hernáez PF, England SJ, Kourtidis K, Koh K, Nicoll K, Harrison RG, Manser K, Price C, Dragovic S, Cifra M, Odzimek A, Robert D (2020) Challenges in coupling atmospheric electricity with biological systems. Int J Biometeorol. https://doi.org/10.1007/s00484-020-01960-7
Karagodin A, Rozanov E, Mareev E, Mironova I, Volodin E, Golubenko K (2019) The representation of ionospheric potential in the global chemistry-climate model SOCOL. Sci Total Environ 697(2019):134172
Katifori A, Lepouras G, Vassilakis C, Giannopoulou E (2007) Ontology visualization methods—a survey, ACM Computing Surveys, Vol. 39, No. 4, Article 10, Publication date: October
Komisar A, Fox MS (2017) An Energy Ontology for Global City Indicators (ISO37120). Technical report, University of Toronto, https://doi.org/10.13140/RG.2.2.27553.43368
Krotkiewicz M. and Wojtkiewicz K., An introduction to ontology based structured knowledge system: knowledge acquisition module, ACIIDS 2013, Part I, LNAI7802, pp. 479–506, 2013
Lacasta J, Nogueras-Iso J, Zarazoga-Soria FJ (2010) Terminological ontology, design, management and practical applications, Springer. DOI https://doi.org/10.1007/978-1-4419-6981-1
Lassila O, MacGuinness D (2001) The role of frame-based representations on the semantic web. Technical Report KSL-01-02, Knowledge Systems Laboratory, Standford University, Standford, California
Li T, Chubak P, Lakshmanan L, Pottinger R (2012) Efficient Extraction of Ontologies from Domain Specific Text Corpora. In: CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management, pp 1537–1541. https://doi.org/10.1145/2396761.2398468
Lindlay J, et al. (2017) Why the Internet of Things needs object oriented ontology, The Design Journal, Volume 20, 2017 - Design for Next: Proceedings of the 12th European Academy of Design Conference, Sapienza University of Rome, 12–14 April 2017, ISBN 978-1-138-09023-1
Lopez-Campos G et al (2017) Biomedical informatics and the digital component of the exposeome. MEDINFO. https://doi.org/10.3233/978-1-61499-830-3-496
Ming T, Kaoru O, Dong M (2017)Ontology-based data semantic management and application in IoT- and cloudenabled smart homes. Future Gener Comput Syst 76:528–539
Mironova I, Bazilevskaya G, Kovaltsov G, Artamonov A, Rozanov E, Mishev A, Makhmutov V, Karagodin A, Golubenko K (2019) Spectra of high energy electron precipitation and atmospheric ionization rates retrieval from balloon measurements. Sci Total Environ 693:133242. https://doi.org/10.1016/j.scitotenv.2019.07.048
MobApp -Mobile Application OxiAlert-Beta (n.d.) https://play.google.com/store/apps/details?id=es.geobiomet.oxyalert&hl=es. Accessed 28 Sep 2019
Morley EL, Robert D (2018) Electric fields elicit ballooning in spiders. Curr Biol 28(14):2324–2330
Muller H et al. (2009) “Connecting genes with diseases,” 2009 13th International Conference Information Visualisation, Barcelona, pp. 323–330, doi: https://doi.org/10.1109/IV.2009.86
Nicoll KA, Harrison RG, Barta V, Bor J, Brugge R, Chillingarian A, Chum J, Georgoulias AK, Guha A, Kourtidis K, Kubicki M, Mareev E, Matthews J, Mkrtchyan H, Odzimek A, Raulin J-P, Robert D, Silva H, Tacza J, Yair Y, Yaniv R (2019) A global atmospheric electricity monitoring network for climate and geophysical research. J Atmos Sol Terr Phys 184:18–29. https://doi.org/10.1016/j.jastp.2019.01.003
NLDN project (n.d.) https://www.vaisala.com/en/products/data-subscriptions-and-reports/data-sets/nldn. Accessed 20 Oct 2020
Noy N, Kunnatur S, Klein M, Musen M (2004) Tracking changes during ontology evolution. In: McIlraith SA, Plexousakis D, van Harmelen F (eds) The Semantic Web – ISWC 2004. ISWC 2004. Lecture Notes in Computer Science, vol 3298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30475-3_19
Patience B, Noyes Pamela D, Casey Warren M, Dix David J (2017) Application of adverse outcome pathways to U.S. EPA’s endocrine disruptor screening program. Environ Health Perspect 125:096001
Poole D, Smyth C, Sharma R (2009) Ontology design for scientific theories that make probabilistic predictions, IEEE Computer Society, 1541–1672/09
Pathak J, Kiefer RC, Bielinski SJ,Chute CG (2012) Mining the human phenome using semantic web technologies: a case study for type 2 Diabetes. AMIA ... Annual symposium proceedings/AMIA symposium. AMIA Symposium 2012. pp 699–708
Pöschl U (2005) “Atmospheric aerosols: composition, transformation, climate and health effects.” AngewandteChemie International Edition 44, no. 46: 7520–40. https://doi.org/10.1002/anie.200501122
Prácser E, Bozóki T, Sátori G, Williams E, Guha A, Yu H (2019) Reconstruction of global lightning activity based on Schumann resonance measurement: model description and synthetic tests. Radio Sci 54:254–267
Protégée, https://webprotege.stanford.edu/#projects/2f49d021-41f9-4bd3-a8d8-6a577e3ddcb7/edit/Classes?selection=Class(owl:Thing), Accessesed 25.10.2020
Repacholi MH, Greenebaum B (1999) Interaction of static and extremely low frequency electric and magnetic fields with living systems: health effects and research needs. Bioelectromagnetics 20(3):133–160
Rooney Andrew A, Boyles Abee L, Wolfe Mary S, Bucher John R, Thayer Kristina A (2014) Systematic review and evidence integration for literature-based environmental health science assessments. Environ Health Perspect 122:711–718
ROSHYDROMET (n.d.) http://global-climate-change.ru/index.php/en/roshydromet. Accessed 10 Oct 2020
Saad A, Shaharin S (2016) The methodology for ontology development in lesson plan domain. Int J Adv Comput Sci Appl 7(4)
Salari V, Barzanjeh SH, Cifra M, Simon C, Scholkmann F, Alirezaei Z, Tuszynski JA (2018) Electromagnetic fields and optomechanics in cancer diagnostics and treatment. Front Biosci Landmark 23:1391–1406
Savoska S et al., “Towards integration exposome data and personal health records in the age of IoT”, In the 11th ICT Innovations Conference 2019 Web Proceedings, EMBNet Workshop, Ohrid, Republic of North Macedonia, October, 2019, pp. 237–246, ISSN 1857-7288
Smith B, Ashburner M, Rosse C, Bard J, Bug W, Werner C, Louis J, Goldberg, et al (2017) The OBO Foundry: coordinated evolution of ontologies to supportbiomedical data integration. Nat Biotechnol 25:1251–1255
Shu G, Avis NJ, Rana OF (2006) Investigating visualization ontologies. Presented at: UK e-Science All Hands Meeting 2006, Nottingham, UK, 18th - 21st September 2006. Published in: Cox, Simon J. ed. Proceedings of the UK e-Science All Hands Meeting 2006. Edinburgh, UK: National e-Science Centre, pp 249–256
Sureephong P et al (2008) An ontology-based knowledge management system for industry clusters. In: Yan XT, Ion WJ, Eynard B (eds) Global design to gain a competitive edge. Springer, London. https://doi.org/10.1007/978-1-84800-239-5_33
Tsong TY, Astumian RD (1986)863—Absorption and conversion of electric field energy by membrane bound ATPases. Bioelectrochem Bioenerg 15(3):457–476
UBE- UBERON Ontology, http://www.ontobee.org/ontology/UBERON, Accessed 10.1.2020
Ushold M, King M (n.d.) Towards a methodology for building ontologies. In: workshop on basic ontological issues in knowledge sharing, held in conjunction with IJCAI-95
Web Protegee, Stanford university, https://webprotege.stanford.edu, Accessed 4.10.2019
Wild CP (2005) Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomark Prev 14:1847–1850
Wild CP (2012) The exposome: from concept to utility. Int.J.Epidemiol. 41:23–32
WWLLNN (n.d.) project, http://wwlln.net/
Yair Y, Reuveni Y, Katz S, Price C, Yaniv R (2019) Strong electric fields observed during snow storms on Mt. Hermon, Israel. Atmos Res 215:208–213
Funding
This article is based upon work from COST Action Electronet (CA15211), supported by COST (European Cooperation in Science and Technology).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Savoska, S., Fdez-Arroyabe, P., Cifra, M. et al. Toward the creation of an ontology for the coupling of atmospheric electricity with biological systems. Int J Biometeorol 65, 31–44 (2021). https://doi.org/10.1007/s00484-020-02051-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00484-020-02051-3