02711naa a2200349 a 450000100080000000500110000800800410001902400540006010000140011424500980012826000090022652017370023565000220197265000170199465000140201165000160202565000180204165000140205965300170207365300220209065300260211265300170213865300130215570000160216870000250218470000200220970000140222970000170224370000150226070000230227577300630229821544332023-08-22       2023    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1016/j.infsof.2023.1072402DOI1 aGOMES, J.  aA scientific software ecosystem architecture for the livestock domain.h[electronic resource]  c2023  aContext: In the livestock domain, technologies are developed to sustainably raise animal production. However, the domain is critical, since animals are very sensitive to variables such as temperature and humidity, which can cause diseases and consequent production losses and discomfort. Livestock production systems then demand monitoring, reasoning, and acting on the environment so that the levels of those variables are preserved in pre-established intervals and undesired conditions are predicted, avoided, and mitigated with automated actions. Objective: The main contribution of this article is presenting E-SECO, a software ecosystem platform, and its evolution that encapsulates a new self-adaptive component to tackle animal production decisions, named e-Livestock architecture. Method: Two case studies were conducted involving a real system derived from the E-SECO platform encompassing a Compost Barn production system, i.e., the environment and surrounding technology where bovine milk production takes place. Results: Results showed the effectiveness of E-SECO to (i) abstract disruptive technologies based on the Internet of Things (IoT) and Artificial Intelligence and accommodate them in a single architecture for that specific domain, (ii) support reuse and derivation of a self-adaptive architecture to support engineering a complex system for a livestock sub-domain (milk production), and (iii) support empirical studies in a real smart farm towards a future transfer of technology to industry. Conclusion: The results showed that the E-SECO platform, which encompasses e-livestock architecture, can support monitoring, reasoning, prediction, and automated actions in a milk production/Compost Barn environment.  aComputer software  aDairy cattle  aLivestock  aCompostagem  aGado Leiteiro  aPecuária  aCompost barn  aDados de sensores  aSelf-adaptive systems  aSensors data  aSoftware1 aESTEVES, I.1 aGRACIANO NETO, V. V.1 aDAVID, J. M. N.1 aBRAGA, R.1 aARBEX, W. A.1 aKASSAB, M.1 aOLIVEIRA, R. F. de  tInformation and Software Technologygv. 160, 107240, 2023.