skip to main content
10.1145/3528229.3529386acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
research-article

Deriving experiments from E-SECO software ecosystem in the technology transfer process for the livestock domain

Published:09 November 2022Publication History

ABSTRACT

The process of transferring technology from research institutes to industry involves benchmarking it in exhaustive experiments to assure it reaches the established quality criteria. This is also true for the livestock domain, in which the technologies developed to sustainably raise animals production are submitted to experiments while preserving their health and wellness. However, since such institutions often conduct several parallel innovation projects, the establishment of an infrastructure to support those experiments can be costly, repetitive, and error-prone. For that purpose, we developed E-SECO, a software ecosystem that encapsulates a life-cycle model for scientific experiments and its supporting platform and actors. The main contribution of this paper is presenting how the E-SECO architecture was successfully applied to create a livestock architecture (named e-Livestock architecture) from which two different (and independent) scientific experiments involving real systems were deployed and executed in the livestock domain. The first experiment involved a Compost Barn production system, i.e., the environment and surrounding technology where bovine milk production takes place; whilst the second experiment involved an automated monitoring environment for aviaries. Preliminary results showed the effectiveness of E-SECO to (i) abstract concepts of scientific experiments for livestock domain, (ii) support reuse and derivation of an architecture to support engineering real systems for different livestock sub-domains, and (iii) support the experiments towards a future transfer of technology to industry.

References

  1. Lenita Ambrósio, Heitor Linhares, José Maria N David, Regina Braga, Wagner Arbex, Mariana Magalhães Campos, and Rafael Capilla. 2021. Enhancing the Reuse of Scientific Experiments for Agricultural Software Ecosystems. Journal of Grid Computing 19, 4 (2021), 1--24.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Christiane Bahlo, Peter Dahlhaus, Helen Thompson, and Mark Trotter. 2019. The role of interoperable data standards in precision livestock farming in extensive livestock systems: A review. Computers and electronics in agriculture 156 (2019), 459--466.Google ScholarGoogle ScholarCross RefCross Ref
  3. Jan Bosch. 2009. From software product lines to software ecosystems.. In SPLC, Vol. 9. 111--119.Google ScholarGoogle Scholar
  4. Peter Buneman and Wang-Chiew Tan. 2019. Data provenance: What next? ACM SIGMOD Record 47, 3 (2019), 5--16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bin Cao, Beth Plale, Girish Subramanian, Ed Robertson, and Yogesh Simmhan. 2009. Provenance information model of karma version 3. In 2009 Congress on Services-I. IEEE, 348--351.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Tadeu Classe, Regina Braga, José Maria N David, Fernanda Campos, and Wagner Arbex. 2017. A distributed infrastructure to support scientific experiments. Journal of Grid Computing 15, 4 (2017), 475--500.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Sérgio Manuel Serra da Cruz, Marcos Bacis Ceddia, Renan Carvalho Tàvora Miranda, Gabriel Rizzo, Filipe Klinger, Renato Cerceau, Ricardo Mesquita, Ricardo Cerceau, Elton Carneiro Marinho, Eber Assis Schmitz, et al. 2018. Data Provenance in Agriculture. In International Provenance and Annotation Workshop. Springer, 257--261.Google ScholarGoogle Scholar
  8. Sérgio Manuel Serra da Cruz and José Antonio Pires do Nascimento. 2019. Towards integration of data-driven agronomic experiments with data provenance. Computers and Electronics in Agriculture 161 (2019), 14--28.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Simone da Silva Amorim, Eduardo Santana de Almeida, and John D McGregor. 2013. Extensibility in ecosystem architectures: an initial study. In Proceedings of the 2013 International Workshop on Ecosystem Architectures. 11--15.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Simone da Silva Amorim, Eduardo Santana de Almeida, and John D McGregor. 2014. Scalability of ecosystem architectures. In ICSA. IEEE, 49--52.Google ScholarGoogle Scholar
  11. Simone da Silva Amorim, John D McGregor, Eduardo Santana de Almeida, and Christina von Flach G. Chavez. 2014. Flexibility in ecosystem architectures. In ECSA Workshops. 1--6.Google ScholarGoogle Scholar
  12. Embrapa Gado de Leite. 2020. Brasil tem a primeira instalação de compost barn destinada a pesquisa. https://www.embrapa.br/busca-de-noticias/-/noticia/53360675/brasil-tem-a-primeira-instalacao-de-compost-barn-destinada-apesquisa.Google ScholarGoogle Scholar
  13. Daniel De Oliveira, Eduardo Ogasawara, Fernanda Baião, and Marta Mattoso. 2010. Scicumulus: A lightweight cloud middleware to explore many task computing paradigm in scientific workflows. In 2010 IEEE 3rd International Conference on Cloud Computing. IEEE, 378--385.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Rodrigo Pereira dos Santos, Cláudia Werner, Olavo Barbosa, and Carina Alves. 2012. Software Ecosystems: Trends and Impacts on Software Engineering. In 26th SBES. IEEE, Natal, Brazil, 206--210. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Juliana Fernandes, Valdemar Vicente Graciano Neto, and Rodrigo Pereira dos Santos. 2021. An Approach Based on Conceptual Modeling to Understand Factors that Influence Interoperability in Systems-of-Information Systems. In XX SBQS. ACM, 34:1--34:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Francisco Henrique Ferreira, Elisa Yumi Nakagawa, and Rodrigo Pereira dos Santos. 2021. Reliability in Software-intensive Systems: Challenges, Solutions, and Future Perspectives. In 47th SEAA. IEEE, Palermo, Italy, 54--61. Google ScholarGoogle ScholarCross RefCross Ref
  17. Yolanda Gil, Ewa Deelman, Mark Ellisman, Thomas Fahringer, Geoffrey Fox, Dennis Gannon, Carole Goble, Miron Livny, Luc Moreau, and Jim Myers. 2007. Examining the challenges of scientific workflows. Computer 40, 12 (2007), 24--32.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Jonas S Gomes, José Maria N David, Regina Braga, Wagner Arbex, Bryan Barbosa, Wneiton Luiz Gomes, and Leonardo M Gravina Fonseca. 2021. e-LivestockProv: An Architecture based on Provenance to Manage Traceability in Precision Livestock Farming. In Anais do I Workshop de Práticas de Ciência Aberta para Engenharia de Software. SBC, 43--48.Google ScholarGoogle Scholar
  19. Valdemar Vicente Graciano Neto, Rodrigo Pereira dos Santos, Davi Viana, and Renata Araujo. 2020. Towards a Conceptual Model to Understand Software Ecosystems Emerging from Systems-of-Information Systems. In Software Ecosystems, Sustainability and Human Values in the Social Web, Rodrigo Pereira dos Santos, Cristiano Maciel, and José Viterbo (Eds.). Springer, 1--20.Google ScholarGoogle Scholar
  20. Ian Horrocks, Peter F Patel-Schneider, Harold Boley, Said Tabet, Benjamin Grosof, Mike Dean, et al. 2004. SWRL: A semantic web rule language combining OWL and RuleML. W3C Member submission 21, 79 (2004), 1--31.Google ScholarGoogle Scholar
  21. Slinger Jansen, Anthony Finkelstein, and Sjaak Brinkkemper. 2009. A sense of community: A research agenda for software ecosystems. In 2009 31st ICSE-Companion. IEEE, 187--190.Google ScholarGoogle Scholar
  22. Sander Janssen, Erling Andersen, Ioannis N Athanasiadis, and Martin K van Ittersum. 2009. A database for integrated assessment of European agricultural systems. Environmental Science & Policy 12, 5 (2009), 573--587.Google ScholarGoogle ScholarCross RefCross Ref
  23. Clement Jonquet, Anne Toulet, Elizabeth Arnaud, Sophie Aubin, Esther Dzale Yeumo, Vincent Emonet, John Graybeal, Marie-Angélique Laporte, Mark AMusen, Valeria Pesce, et al. 2018. AgroPortal: A vocabulary and ontology repository for agronomy. Computers and Electronics in Agriculture 144 (2018), 126--143.Google ScholarGoogle ScholarCross RefCross Ref
  24. GS Karthick, M Sridhar, and PB Pankajavalli. 2020. Internet of things in animal healthcare (IoTAH): review of recent advancements in architecture, sensing technologies and real-time monitoring. SN Computer Science 1, 5 (2020), 1--16.Google ScholarGoogle ScholarCross RefCross Ref
  25. Vinícius C Lopes, Roberto Felício de Oliveira, and Valdemar Vicente Graciano Neto. 2021. Towards an IoT-Based Architecture for Monitoring andAutomated Decision-Making in an Aviary Environment. In Anais do XIII Congresso Brasileiro de Agroinformática. SBC, 320--328.Google ScholarGoogle Scholar
  26. Konstantinos Manikas. 2016. Revisiting software ecosystems research: A longitudinal literature study. Journal of Systems and Software 117 (2016), 84--103.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Paolo Missier, Khalid Belhajjame, and James Cheney. 2013. The W3C PROV family of specifications for modelling provenance metadata. In 16th EDBT. 773--776.Google ScholarGoogle Scholar
  28. Luc Moreau and Paolo Missier. 2013. PROV-DM: The prov data model. W3C recommendation. World Wide Web Consortium (2013).Google ScholarGoogle Scholar
  29. Valdemar Vicente Graciano Neto, Fábio Basso, Rodrigo Pereira dos Santos, Noor Hasrina Bakar, Mohamad Kassab, Cláudia Werner, Toacy Cavalcante de Oliveira, and Elisa Yumi Nakagawa. 2019. Model-driven engineering ecosystems. In Proceedings of the 7th SESoS and 13th WDES 2019, Montreal, QC, Canada, May 28, 2019. IEEE / ACM, 58--61. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Valdemar Vicente Graciano Neto, Rodrigo Pereira dos Santos, and Renata Mendes de Araujo. 2017. New Challenges in the Social Web: Towards Systems-of-Information Systems Ecosystems. In VIII WAIHCWS, Cristiano Maciel, José Viterbo, and Rodrigo Pereira dos Santos (Eds.), Vol. 2039. CEUR-WS.org, 1--12. http://ceur-ws.org/Vol-2039/paper01.pdfGoogle ScholarGoogle Scholar
  31. Lael Parrott, René Lacroix, and Kevin M Wade. 2003. Design considerations for the implementation of multi-agent systems in the dairy industry. Computers and electronics in agriculture 38, 2 (2003), 79--98.Google ScholarGoogle Scholar
  32. Yogesh L Simmhan, Beth Plale, Dennis Gannon, and Suresh Marru. 2006. Performance evaluation of the karma provenance framework for scientific workflows. In International Provenance and Annotation Workshop. Springer, 222--236.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Evren Sirin, Bijan Parsia, Bernardo Cuenca Grau, Aditya Kalyanpur, and Yarden Katz. 2007. Pellet: A practical owl-dl reasoner. Journal of Web Semantics 5, 2 (2007), 51--53.Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Pedro Henrique Dias Valle, Lina Garcés, and Elisa Yumi Nakagawa. 2021. Architectural strategies for interoperability of software-intensive systems: practitioners' perspective. In SAC '21, Chih-Cheng Hung, Jiman Hong, Alessio Bechini, and Eunjee Song (Eds.). ACM, 1399--1408. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Deriving experiments from E-SECO software ecosystem in the technology transfer process for the livestock domain

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        SESoS '22: Proceedings of the 10th IEEE/ACM International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems
        May 2022
        52 pages
        ISBN:9781450393348
        DOI:10.1145/3528229

        Copyright © 2022 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 9 November 2022

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate4of10submissions,40%

        Upcoming Conference

        ICSE 2025

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader