Díaz-De-arcaya, JosuMiñón, RaúlTorre-Bastida, Ana I.Del Ser, JavierAlmeida, Aitor2020-11-24Díaz-De-arcaya , J , Miñón , R , Torre-Bastida , A I , Del Ser , J & Almeida , A 2020 , ' PADL: A Modeling and Deployment Language for Advanced Analytical Services : A modeling and deployment language for advanced analytical services ' , Sensors , vol. 20 , no. 23 , 6712 , pp. 1-28 . https://doi.org/10.3390/s20236712 , https://doi.org/10.3390/s202367121424-8220researchoutputwizard: 11556/1027Publisher Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland.In the smart city context, Big Data analytics plays an important role in processing the data collected through IoT devices. The analysis of the information gathered by sensors favors the generation of specific services and systems that not only improve the quality of life of the citizens, but also optimize the city resources. However, the difficulties of implementing this entire process in real scenarios are manifold, including the huge amount and heterogeneity of the devices, their geographical distribution, and the complexity of the necessary IT infrastructures. For this reason, the main contribution of this paper is the PADL description language, which has been specifically tailored to assist in the definition and operationalization phases of the machine learning life cycle. It provides annotations that serve as an abstraction layer from the underlying infrastructure and technologies, hence facilitating the work of data scientists and engineers. Due to its proficiency in the operationalization of distributed pipelines over edge, fog, and cloud layers, it is particularly useful in the complex and heterogeneous environments of smart cities. For this purpose, PADL contains functionalities for the specification of monitoring, notifications, and actuation capabilities. In addition, we provide tools that facilitate its adoption in production environments. Finally, we showcase the usefulness of the language by showing the definition of PADL-compliant analytical pipelines over two uses cases in a smart city context (flood control and waste management), demonstrating that its adoption is simple and beneficial for the definition of information and process flows in such environments.28662994enginfo:eu-repo/semantics/openAccessjournal article10.3390/s20236712Analytical pipelinesArtificial intelligence description languageEdge computingMachine learning life cycleAnalytical ChemistryInformation SystemsBiochemistryAtomic and Molecular Physics, and OpticsInstrumentationElectrical and Electronic EngineeringSDG 11 - Sustainable Cities and CommunitiesSDG 12 - Responsible Consumption and ProductionFunding InfoThis work was partially supported by the SPRI–Basque Government through their ELKARTEK program_x000D_ (3KIA project, ref. KK-2020/00049). Aitor Almeida’s participation was supported by the FuturAAL-Ego project_x000D_ (RTI2018-101045-A-C22) granted by the Spanish Ministry of Science, Innovation and Universities. Javier Del Ser_x000D_ also acknowledges funding support from the Consolidated Research Group MATHMODE (IT1294-19), granted by_x000D_ the Department of Education of the Basque Government.This work was partially supported by the SPRI–Basque Government through their ELKARTEK program_x000D_ (3KIA project, ref. KK-2020/00049). Aitor Almeida’s participation was supported by the FuturAAL-Ego project_x000D_ (RTI2018-101045-A-C22) granted by the Spanish Ministry of Science, Innovation and Universities. Javier Del Ser_x000D_ also acknowledges funding support from the Consolidated Research Group MATHMODE (IT1294-19), granted by_x000D_ the Department of Education of the Basque Government.http://www.scopus.com/inward/record.url?scp=85096580221&partnerID=8YFLogxK