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<!DOCTYPE html><html lang="en-US"><head><meta charSet="utf-8"/><title>Leonardo Guerreiro Azevedo - IBM Research</title><meta name="description" content="Leonardo G. Azevedo has been Research Scientist within IBM Research Brazil since 2013. He is Ph.D. (2005) and MSc. 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style="--top:0px;--top-offset:0rem"></a><div class="p7tK8"><div class="_4s3yP"><h1 class="eoFfr">Leonardo Guerreiro Azevedo</h1><div class="BAYxB"><section><h2 class="TD6HM">Title</h2><div class="QxXJo">Staff Research Scientist, Knowledge Engineer and Distributed Service Architect</div></section></div></div><div class="wEd95"><div class="epsPr"><span style="box-sizing:border-box;display:block;overflow:hidden;width:initial;height:initial;background:none;opacity:1;border:0;margin:0;padding:0;position:absolute;top:0;left:0;bottom:0;right:0"><img alt="Leonardo Guerreiro Azevedo" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover"/><noscript><img alt="Leonardo Guerreiro Azevedo" loading="lazy" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover" sizes="(min-width: 99rem) calc((99rem - 50rem) * 0.25 + 9rem), (min-width: 82rem) calc((100vw - 50rem) * 0.25 + 9rem), (min-width: 66rem) calc((100vw - 49rem) * 0.25 + 9rem), (min-width: 42rem) calc(((100vw - 27rem) * 0.375 + 6rem) + 3rem), 400px" srcSet="https://research.ibm.com/api/image/leonardo-guerreiro-azevedo.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F2024&w=16&q=75 16w, https://research.ibm.com/api/image/leonardo-guerreiro-azevedo.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F2024&w=32&q=75 32w, 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src="https://research.ibm.com/api/image/leonardo-guerreiro-azevedo.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F2024&w=3840&q=75"/></noscript></span></div></div></div></section><section class="H2eT0"><div class="pjmlR"><a class="xHBSN" name="bio" style="--top:0px;--top-offset:0rem"></a><h2 class="Ji5Eq">Bio</h2><div class="r_AIv"><p class="eBWTD EihHw">Leonardo G. Azevedo has been Research Scientist within IBM Research Brazil since 2013. He is Ph.D. (2005) and MSc. (2001) from PESC/COPPE/UFRJ and Bachelor in Informatics from UFRJ (Rio de Janeiro-Brazil). He was a professor within UniRio (2006 to 2018) and a researcher of the Graduate Program in Informatics (PPGI/UniRio) (2009 to 2018). He has more than 20 years of experience in system development and applied research, working on projects for national and international organizations. His research areas are Distributed Sytems, Service-Oriented Architecture (SOA), Microservices Architecture (MSA), Databases, Provenance, Data Integration, Polystore, Knowledge Engineering, Ontologies, and Business Process Management (BPM).</p><p class="eBWTD">homepage: <a href="http://ibm.biz/leonardo" class="bx--link _7_4F7 bx--link--inline">http://ibm.biz/leonardo</a> and</p><p class="eBWTD DMxM7">CNPq Lattes: <a href="http://lattes.cnpq.br/7214791464543522" class="bx--link _7_4F7 bx--link--inline">http://lattes.cnpq.br/7214791464543522</a>.</p></div></div></section><section class="_9O_DZ cOi2S"><a class="xHBSN" name="patents" style="--top:0px;--top-offset:0rem"></a><a class="xHBSN" name="publications" style="--top:0px;--top-offset:0rem"></a><div class="EECWT PCata bx--tabs--scrollable"><button aria-hidden="true" aria-label="Scroll left" class="bx--tab--overflow-nav-button--hidden" tabindex="-1" type="button"><svg focusable="false" preserveAspectRatio="xMidYMid meet" 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height="16" viewBox="0 0 16 16" aria-hidden="true"><path d="M11 8L6 13 5.3 12.3 9.6 8 5.3 3.7 6 3z"></path></svg></button></div><div role="tabpanel" class="bx--tab-content" selected="" tabindex="0"></div><div role="tabpanel" hidden="" class="bx--tab-content" tabindex="0"></div></section><section class="_2CLlr cOi2S"><h2 class="Ji5Eq CvY_O">Publications</h2><div class="_8ooYo"><ul><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/an-appraisal-of-automated-tools-for-fairness-evaluation">An Appraisal of Automated Tools for FAIRness Evaluation</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/leonardo-guerreiro-azevedo">Leonardo Guerreiro Azevedo</a></li><li class="_8MUnA">Gabriel Banaggia</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2024</li><li class="EEJK9 XuP8p">ESWC 2024</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/analysis-of-automated-tools-for-fairness-evaluation-a-literature-perspective">Analysis of Automated Tools for FAIRness Evaluation: A Literature Perspective</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/leonardo-guerreiro-azevedo">Leonardo Guerreiro Azevedo</a></li><li class="_8MUnA">Gabriel Bannagia</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2024</li><li class="EEJK9 XuP8p">ESWC 2024</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/hkpoly-a-polystore-architecture-to-support-data-linkage-and-queries-on-distributed-and-heterogeneous-data">HKPoly: A Polystore Architecture to Support Data Linkage and Queries on Distributed and Heterogeneous Data</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/leonardo-guerreiro-azevedo">Leonardo Guerreiro Azevedo</a></li><li class="_8MUnA">Renan Souza</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2024</li><li class="EEJK9 XuP8p">SBSI 2024</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/integrating-adme-tox-properties-of-pfas-described-in-public-and-private-knowledge-bases-using-wikidata">Integrating ADME-Tox properties of PFAS described in public and private knowledge bases using Wikidata</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/guilherme-augusto-ferreira-lima">Guilherme Augusto Ferreira Lima</a></li><li class="_8MUnA"><a class="WvbPS" href="/people/marcelo-machado">Marcelo Machado</a></li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2024</li><li class="EEJK9 XuP8p">ACS Spring 2024</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/applying-a-fairness-questionnaire-to-characterize-materials-databases">Applying a FAIRness questionnaire to characterize Materials databases</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/leonardo-guerreiro-azevedo">Leonardo Guerreiro Azevedo</a></li><li class="_8MUnA">Julio Cesar Cardoso Tesolin</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2023</li><li class="EEJK9 XuP8p">ACS Fall 2023</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/epa-compositions-on-realtime-streaming-analytics">EPA Compositions on Realtime Streaming Analytics</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA">Henrique Villaça</li><li class="_8MUnA">Sean Siqueira</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2023</li><li class="EEJK9 XuP8p">SBSI 2023</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/epacomp-an-architectural-model-for-epa-composition">EPAComp: An Architectural Model for EPA Composition</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA">Luís Henrique Neves Villaça</li><li class="_8MUnA">Sean Wolfgand Matsui Siqueira</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2023</li><li class="EEJK9 XuP8p">SBSI 2023</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/an-improved-questionnaire-for-fair-characterization">An Improved Questionnaire for FAIR Characterization</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/leonardo-guerreiro-azevedo">Leonardo Guerreiro Azevedo</a></li><li class="_8MUnA">Julio Cesar Cardoso Tesolin</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2023</li><li class="EEJK9 XuP8p">ESWC 2023</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/position-paper-on-dataset-engineering-to-accelerate-science">Position Paper on Dataset Engineering to Accelerate Science</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/emilio-ashton-vital-brazil">Emilio Ashton Vital Brazil</a></li><li class="_8MUnA"><a class="WvbPS" href="/people/eduardo-soares">Eduardo Almeida Soares</a></li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2023</li><li class="EEJK9 XuP8p">AAAI 2023</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="vGCFo"><article class="PpV0z _4VvpY ywX4g"><h3 class="d0naJ jjmX_"><a class="_1kOEn" href="/publications/owl-ontology-evolution-understanding-and-unifying-the-complex-changes">OWL ontology evolution: Understanding and unifying the complex changes</a></h3><ul class="VgSQD"><li class="EEJK9"><ul class="_8ydsY"><li class="_8MUnA"><a class="WvbPS" href="/people/viviane-torres-da-silva">Viviane Torres Da Silva</a></li><li class="_8MUnA">Jéssica Soares Dos Santos</li><li class="_8MUnA">et al.</li></ul></li><li class="EEJK9">2022</li><li class="EEJK9 XuP8p">Knowledge Engineering Review</li></ul><div class="FN4MA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="UI7HX QQGoa"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li></ul><div class="hjuch"><nav aria-label="pagination" class="Pvkvw mbGgE"><ul class="tgnrU"><li><a aria-current="location" class="QCIlI" href="/people/leonardo-guerreiro-azevedo">1</a></li><li><a class="QCIlI" href="/people/leonardo-guerreiro-azevedo?publications-page=2">2</a></li><li><div class="JGYxh">...</div></li><li><a class="QCIlI" href="/people/leonardo-guerreiro-azevedo?publications-page=5">5</a></li><li><a class="mTtGB" aria-label="Next page" href="/people/leonardo-guerreiro-azevedo?publications-page=2"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M22 16L12 26 10.6 24.6 19.2 16 10.6 7.4 12 6z"></path></svg></a></li></ul></nav></div></div></section><section class="_15LJA QbN3g cOi2S"><h2 class="Ji5Eq CvY_O">Patents</h2><div class="sXOwP"><ul class="_wrOu"><li class="J0_xW"><article class="u8xcP HepWi"><ul class="f7xyQ"><li class="U4UFg"><time dateTime="2024-05-20T00:00:00.000Z">20 May 2024</time></li><li class="U4UFg">US</li><li class="U4UFg">11989628</li></ul><div class="UvF6F"><h3 class="euhTO"><a class="q8YpP" href="https://patents.google.com/patent/US11989628/en">Machine Teaching Complex Concepts Assisted By Computer Vision And Knowledge Reasoning</a></h3></div><div class="lzakT"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="_1nFq8 _DIFW"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="J0_xW"><article class="u8xcP HepWi"><ul class="f7xyQ"><li class="U4UFg"><time dateTime="2021-06-28T00:00:00.000Z">28 Jun 2021</time></li><li class="U4UFg">US</li><li class="U4UFg">11048877</li></ul><div class="UvF6F"><h3 class="euhTO"><a class="q8YpP" href="https://patents.google.com/patent/US11048877/en">System And Method For Generating Ontologies Using Natural Language Utterances</a></h3></div><div class="lzakT"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="_1nFq8 _DIFW"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li><li class="J0_xW"><article class="u8xcP HepWi"><ul class="f7xyQ"><li class="U4UFg"><time dateTime="2021-03-22T00:00:00.000Z">22 Mar 2021</time></li><li class="U4UFg">US</li><li class="U4UFg">10958531</li></ul><div class="UvF6F"><h3 class="euhTO"><a class="q8YpP" href="https://patents.google.com/patent/US10958531/en">On-demand Remote Predictive Monitoring For Industrial Equipment Analysis And Cost Forecast</a></h3></div><div class="lzakT"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="_1nFq8 _DIFW"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li></ul></div></section><section class="aHjNh cOi2S"><a class="xHBSN" name="projects" style="--top:0px;--top-offset:0rem"></a><h2 class="Ji5Eq">Projects</h2><ul><li style="--delay:0ms"><article class="I_MPR DVTXV ilhsR enHrJ _6Nrej"><div class="YlPdB slA_i"><div class="Bsl82"><span style="box-sizing:border-box;display:block;overflow:hidden;width:initial;height:initial;background:none;opacity:1;border:0;margin:0;padding:0;position:absolute;top:0;left:0;bottom:0;right:0"><img alt="ProvLake.jpg" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover"/><noscript><img alt="ProvLake.jpg" loading="lazy" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover" sizes="(min-width: 99rem) calc(max(calc((99rem - 50rem) * 0.1875 + 6rem), ((calc((99rem - 50rem) * 0.1875 + 6rem)) * (1 / 2)) * (1920 / 1080))), (min-width: 82rem) calc(max(calc((100vw - 50rem) * 0.1875 + 6rem), ((calc((100vw - 50rem) * 0.1875 + 6rem)) * (1 / 2)) * (1920 / 1080))), (min-width: 66rem) calc(max(calc((100vw - 49rem) * 0.1875 + 6rem), ((calc((100vw - 49rem) * 0.1875 + 6rem)) * (1 / 2)) * (1920 / 1080))), (min-width: 42rem) calc(max(calc((100vw - 27rem) * 0.25 + 3rem), ((calc((100vw - 27rem) * 0.25 + 3rem)) * (1 / 2)) * (1920 / 1080))), 16px" srcSet="https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=16&q=75 16w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=32&q=75 32w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=48&q=75 48w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=64&q=75 64w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=96&q=75 96w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=128&q=75 128w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=256&q=75 256w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=384&q=75 384w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=640&q=75 640w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=750&q=75 750w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=828&q=75 828w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=1080&q=75 1080w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=1200&q=75 1200w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=1920&q=75 1920w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=2048&q=75 2048w, https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=3840&q=75 3840w" src="https://research.ibm.com/_next/image?url=https%3A%2F%2Fresearch-website-prod-cms-uploads.s3.us.cloud-object-storage.appdomain.cloud%2FProv_Lake_0cd2dc8521.jpg&w=3840&q=75"/></noscript></span></div></div><div class="T_pPI"><h3 class="SgrkM jKy5y"><a class="cH14s rXxOh" href="/projects/provlake">ProvLake</a></h3></div><div class="hds47"><p class="s_ZJX">A lineage data management system for tracking data in hybrid cloud deployments.</p></div><div class="knsmA"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 24 24" aria-hidden="true" class="xLQbV ixOkQ urFNk"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article></li></ul></section><section class="_5QLND cOi2S"><a class="xHBSN" name="collaborators" style="--top:0px;--top-offset:0rem"></a><h2 class="Ji5Eq">Top collaborators</h2><div class="YT7ZZ" style="--column-count-sm:4;--item-span-sm:2;--column-count-md:8;--item-span-md:4;--column-count-lg:12;--item-span-lg:3;--column-count-xlg:12;--item-span-xlg:3;--column-count-max:12;--item-span-max:3"><article class="_4ygEB ALUAy wjYBe _2099_"><div class="_7JblE" style="--diameter-sm:128px;--diameter-md:128px;--diameter-lg:128px;--diameter-xlg:128px;--diameter-max:128px"><div class="_32VBU">RM</div><div class="Hf3tG"><span style="box-sizing:border-box;display:block;overflow:hidden;width:initial;height:initial;background:none;opacity:1;border:0;margin:0;padding:0;position:absolute;top:0;left:0;bottom:0;right:0"><img alt="Raphael Melo Thiago" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover"/><noscript><img alt="Raphael Melo Thiago" loading="lazy" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover" sizes="128px" srcSet="https://research.ibm.com/api/image/raphael-melo-thiago.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F2341&w=16&q=75 16w, https://research.ibm.com/api/image/raphael-melo-thiago.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F2341&w=32&q=75 32w, 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Engineer</div></div></article><article class="_4ygEB ALUAy wjYBe _2099_"><div class="_7JblE" style="--diameter-sm:128px;--diameter-md:128px;--diameter-lg:128px;--diameter-xlg:128px;--diameter-max:128px"><div class="_32VBU">VT</div><div class="Hf3tG"><span style="box-sizing:border-box;display:block;overflow:hidden;width:initial;height:initial;background:none;opacity:1;border:0;margin:0;padding:0;position:absolute;top:0;left:0;bottom:0;right:0"><img alt="Viviane Torres Da Silva" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:cover"/><noscript><img alt="Viviane Torres Da Silva" loading="lazy" decoding="async" data-nimg="fill" 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https://research.ibm.com/api/image/viviane-torres-da-silva.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F4368&w=2048&q=75 2048w, https://research.ibm.com/api/image/viviane-torres-da-silva.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F4368&w=3840&q=75 3840w" src="https://research.ibm.com/api/image/viviane-torres-da-silva.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F4368&w=3840&q=75"/></noscript></span></div></div><div><h3 class="qS8LQ"><a class="MhAku" href="/people/viviane-torres-da-silva">Viviane Torres Da Silva</a></h3><div class="TNwAp">Senior Research Scientist, Manager</div></div></article><article class="_4ygEB ALUAy wjYBe _2099_"><div class="_7JblE" style="--diameter-sm:128px;--diameter-md:128px;--diameter-lg:128px;--diameter-xlg:128px;--diameter-max:128px"><div class="_32VBU">EA</div><div 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https://research.ibm.com/api/image/eduardo-soares.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F693&w=3840&q=75 3840w" src="https://research.ibm.com/api/image/eduardo-soares.webp?url=https%3A%2F%2Fresearch-website-prod-ibmers-images.s3.us-east.cloud-object-storage.appdomain.cloud%2F693&w=3840&q=75"/></noscript></span></div></div><div><h3 class="qS8LQ"><a class="MhAku" href="/people/eduardo-soares">Eduardo Soares</a></h3><div class="TNwAp">Research Scientist</div></div></article></div></section></div><aside class="LJZuv"><nav aria-label="breadcrumbs" class="tZXIS r3uz9"><ol><li><a class="bx--link" href="/">Home</a></li><li><span class="aEWzI" aria-hidden="true">↳ </span><a class="bx--link" href="/people">People</a></li></ol></nav><div class="nOFOI dD1Aj"><section class="k1mVB"><h2 class="z4nnO">Work location</h2><p class="tyKJu">IBM Research - Brazil Rio de Janeiro, Brazil</p></section></div><div class="fV3Nx d7U6s"><section 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Several tools have been developed to assess the FAIRness of data digital objects in support of enacting the FAIR Principles. This work offers an appraisal of tools that evaluate the FAIRness of such objects, focusing on fully automated solutions. We conduct a literature review about existing tools, extract from it a set of requirements they aim to fulfill, and assess how each one fares considering this ensemble. \nOur results help researchers, developers, and data stewards with an overview of the tools, including an analysis of tools' fulfillment to the elicited requirements, making explicit existing gaps, and giving directions to improvements needed.","linkCode":null,"source":{"__ref":"Source:24305"},"sourceInstance":{"__ref":"SourceInstance:21936"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:219033"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:205343"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46441"},"affiliations":[{"__ref":"Affiliation:73"}]}]},"Source:70":{"__typename":"Source","id":"70","longName":"Brazilian Symposium on Information Systems","shortName":"SBSI","type":"CONFERENCE"},"SourceInstance:20703":{"__typename":"SourceInstance","id":"20703","name":"SBSI 2024"},"Author:178426":{"__typename":"Author","id":"178426","ibmer":null},"AuthorName:205342":{"__typename":"AuthorName","id":"205342","firstName":"Renan","firstNameInitials":null,"lastName":"Souza","author":{"__ref":"Author:178426"}},"Author:20053":{"__typename":"Author","id":"20053","ibmer":{"__ref":"Ibmer:1043"}},"AuthorName:16581":{"__typename":"AuthorName","id":"16581","firstName":"Elton","firstNameInitials":null,"lastName":"Figueiredo de Souza Soares","author":{"__ref":"Author:20053"}},"Author:20135":{"__typename":"Author","id":"20135","ibmer":{"__ref":"Ibmer:2341"}},"AuthorName:16603":{"__typename":"AuthorName","id":"16603","firstName":"Raphael","firstNameInitials":null,"lastName":"Melo Thiago","author":{"__ref":"Author:20135"}},"Author:178428":{"__typename":"Author","id":"178428","ibmer":null},"AuthorName:205344":{"__typename":"AuthorName","id":"205344","firstName":"Anna","firstNameInitials":null,"lastName":"Oliveira","author":{"__ref":"Author:178428"}},"Author:178429":{"__typename":"Author","id":"178429","ibmer":null},"AuthorName:205345":{"__typename":"AuthorName","id":"205345","firstName":"Marcio","firstNameInitials":null,"lastName":"Moreno","author":{"__ref":"Author:178429"}},"Publication:149296":{"__typename":"Publication","id":"149296","slug":"hkpoly-a-polystore-architecture-to-support-data-linkage-and-queries-on-distributed-and-heterogeneous-data","title":"HKPoly: A Polystore Architecture to Support Data Linkage and Queries on Distributed and Heterogeneous Data","type":{"__typename":"PublicationType","displayValue":"Conference paper"},"published":"2024-05-20","publishedMeta":{"__typename":"PublishedMeta","source":"SBSI 2024","year":"2024"},"abstract":"Context: Modern information systems commonly manipulate heterogeneous data and schemas fragmented in the data stores that best fit their storage and access requirements. Besides, different organizations’ business processes independently consume these fragments without explicit links between the employed data.\nProblem: Supporting heterogeneous and not explicitly connected data residing in distinct data repositories is a big challenge.\nSolution: This work proposes HKPoly: a federated architecture that encapsulates data heterogeneity, location, and linkage.\nIS Theory: We employed the Representation theory to create the models of the architecture and its components.\nMethod: Architecture implementation, its application in an Oil \u0026 Gas scenario, and its comparison to a multi-database system.\nResults: The proposal allows query writing to be two times less complex than the one written for the relational multi-database system, adding an excess of about 30% in query processing time.\nContributions: An architecture to query heterogeneous data, the requirements and components for its implementation, and an implementation example using the stated-of-the-art concepts.","linkCode":null,"source":{"__ref":"Source:70"},"sourceInstance":{"__ref":"SourceInstance:20703"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:205342"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16581"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16603"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:205343"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:205344"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:205345"},"affiliations":[{"__ref":"Affiliation:3020"}]}]},"Source:455":{"__typename":"Source","id":"455","longName":"American Chemical Society (ACS) Spring Meeting","shortName":"ACS Spring","type":"CONFERENCE"},"SourceInstance:10465":{"__typename":"SourceInstance","id":"10465","name":"ACS Spring 2024"},"Ibmer:1586":{"__typename":"Ibmer","id":"1586","slug":"guilherme-augusto-ferreira-lima","displayName":"Guilherme Augusto Ferreira Lima"},"Author:20148":{"__typename":"Author","id":"20148","ibmer":{"__ref":"Ibmer:1586"}},"AuthorName:16605":{"__typename":"AuthorName","id":"16605","firstName":"Guilherme Augusto","firstNameInitials":null,"lastName":"Ferreira Lima","author":{"__ref":"Author:20148"}},"Ibmer:3620":{"__typename":"Ibmer","id":"3620","slug":"marcelo-machado","displayName":"Marcelo de Oliveira Costa Machado"},"Author:20054":{"__typename":"Author","id":"20054","ibmer":{"__ref":"Ibmer:3620"}},"AuthorName:16582":{"__typename":"AuthorName","id":"16582","firstName":"Marcelo","firstNameInitials":null,"lastName":"Machado","author":{"__ref":"Author:20054"}},"Ibmer:3503":{"__typename":"Ibmer","id":"3503","slug":"sandro-rama-fiorini","displayName":"Sandro Rama Fiorini"},"Author:2632":{"__typename":"Author","id":"2632","ibmer":{"__ref":"Ibmer:3503"}},"AuthorName:2680":{"__typename":"AuthorName","id":"2680","firstName":"Sandro Rama","firstNameInitials":"S.R.","lastName":"Fiorini","author":{"__ref":"Author:2632"}},"Author:3161":{"__typename":"Author","id":"3161","ibmer":{"__ref":"Ibmer:4368"}},"AuthorName:3138":{"__typename":"AuthorName","id":"3138","firstName":"Viviane T.","firstNameInitials":"V.T.","lastName":"Silva","author":{"__ref":"Author:3161"}},"Publication:86705":{"__typename":"Publication","id":"86705","slug":"integrating-adme-tox-properties-of-pfas-described-in-public-and-private-knowledge-bases-using-wikidata","title":"Integrating ADME-Tox properties of PFAS described in public and private knowledge bases using Wikidata","type":{"__typename":"PublicationType","displayValue":"Talk"},"published":"2024-03-17","publishedMeta":{"__typename":"PublishedMeta","source":"ACS Spring 2024","year":"2024"},"abstract":"Knowledge Integration Framework (KIF) is able to construct a unified view and common query interface to integrate heterogeneous data coming from public and private knowledge bases. These include, for instance, Wikidata, PubChem, IBM CIRCA, and CSV files produced by predictive AI methods. Wikidata is a public repository of general knowledge (the structured counterpart of Wikipedia), PubChem is one of the largest collections of chemical data on the Web, and IBM CIRCA is a research platform aggregating chemically-annotated data from patents and other sources. We propose the use of KIF to integrate ADME-Tox properties of PFAS (Per- and polyfluoroalkyl substances) described in heterogeneous knowledge bases.\n\nBoth Wikidata and PubChem are accessed through their SPARQL interfaces, while IBM CIRCA and the CSV files are accessed through SQL interfaces. One differentiator of our knowledge integration framework, KIF, is that it adopts Wikidata's data model and vocabulary as the lingua franca. At query time, user-provided mappings are used to translate the data model and vocabulary of the underlying bases to that of Wikidata. This means that the integrated result can be accessed as if it were Wikidata itself, i.e., a single knowledge base which \"speaks\" the RDF dialect of Wikidata. In the translation process, we leverage Wikidata's data model support for qualifiers to attach contextual information to statements. For example, a value of LD50 is accompanied not only by its unit (mg/kg) but also by a description of the animal tested, route of administration, etc. We also leverage Wikidata's data model support for references to keep track of the provenance (origin) of each statement produced by the integration layer. We expect that KIF will allow the construction of an integrated knowledge base about ADME-Tox properties of PFAS with higher F.A.I.R. properties. In the talk, we discuss KIF, this particular instantiation, applications, and future plans.","linkCode":null,"source":{"__ref":"Source:455"},"sourceInstance":{"__ref":"SourceInstance:10465"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16605"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16582"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16581"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16603"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:2680"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:3138"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46441"},"affiliations":[{"__ref":"Affiliation:73"}]}]},"Source:454":{"__typename":"Source","id":"454","longName":"American Chemical Society (ACS) Fall Meeting","shortName":"ACS Fall","type":"CONFERENCE"},"SourceInstance:5427":{"__typename":"SourceInstance","id":"5427","name":"ACS Fall 2023"},"Author:58829":{"__typename":"Author","id":"58829","ibmer":null},"AuthorName:51055":{"__typename":"AuthorName","id":"51055","firstName":"Julio Cesar","firstNameInitials":null,"lastName":"Cardoso Tesolin","author":{"__ref":"Author:58829"}},"Publication:22066":{"__typename":"Publication","id":"22066","slug":"applying-a-fairness-questionnaire-to-characterize-materials-databases","title":"Applying a FAIRness questionnaire to characterize Materials databases","type":{"__typename":"PublicationType","displayValue":"Short paper"},"published":"2023-08-13","publishedMeta":{"__typename":"PublishedMeta","source":"ACS Fall 2023","year":"2023"},"abstract":"The FAIR principles guidelines aim to enhance the discovery and usage of digital objects by humans and computational agents. They are formulated at a high level and, as such, are differently interpreted and implemented by distinct communities of practice, which often have to collaborate, such as in the context of the use of chemicals in scientific discovery.\nPractical approaches outlining FAIR-related characteristics of digital objects are few and far between, and most of these are domain-agnostic, i.e., they do not consider scientific communities’ varied needs and require specific implementations and combinations for better estimation.\nQuestionnaires have been considered the main mechanism to systematically capture the implementation choices corresponding to each FAIR principle. However, existing questionnaires focus on FAIR assessment using identical questions for distinct communities, i.e., evaluating the digital objects in the same way and usually reckoning that the digital objects have passed through a FAIRification process. In other words, they do not aim at characterizing digital objects, which would give a current overview of the properties that most contribute to their FAIRness.\nThis work builds on the FAIR principles while considering distinct proposed metrics and tools for manual, automated, and semi-automated FAIRness assessment, like a questionnaire specifically designed to assess a plurality of interrelated scientific domains and their possible integration. It reports on applying an improved questionnaire aiming to characterize digital objects’ properties towards their FAIRification on two Materials databases: Materials Cloud and PubChem.\nWe investigate the hypothesis that this questionnaire instills digital objects’ characteristics with a richness of details about their current properties and outlines their main elements for FAIRification. We demonstrate that the improved questionnaire is a more suitable tool for both domain specialists and data stewards to investigate digital objects’ characteristics and improve on them.","linkCode":null,"source":{"__ref":"Source:454"},"sourceInstance":{"__ref":"SourceInstance:5427"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:51055"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:51056"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46441"},"affiliations":[{"__ref":"Affiliation:73"}]}]},"SourceInstance:5286":{"__typename":"SourceInstance","id":"5286","name":"SBSI 2023"},"Author:57425":{"__typename":"Author","id":"57425","ibmer":null},"AuthorName:49651":{"__typename":"AuthorName","id":"49651","firstName":"Henrique","firstNameInitials":null,"lastName":"Villaça","author":{"__ref":"Author:57425"}},"Author:57426":{"__typename":"Author","id":"57426","ibmer":null},"AuthorName:49652":{"__typename":"AuthorName","id":"49652","firstName":"Sean","firstNameInitials":null,"lastName":"Siqueira","author":{"__ref":"Author:57426"}},"Publication:20759":{"__typename":"Publication","id":"20759","slug":"epa-compositions-on-realtime-streaming-analytics","title":"EPA Compositions on Realtime Streaming Analytics","type":{"__typename":"PublicationType","displayValue":"Conference paper"},"published":"2023-05-29","publishedMeta":{"__typename":"PublishedMeta","source":"SBSI 2023","year":"2023"},"abstract":"Context: Complex Event Processing (CEP) architectures present high applicability in Realtime Streaming Analytics (RTSA) scenarios by the extraction and generation of valuable information from continuous data feeds, like in stock markets, traffic, and patient monitoring.\n\nProblem: Although guidelines and models for CEP architectures have been proposed in academia and industry, the composition of its inter-operable elements in charge of processing events, known as Event Processing Agent (EPA), remains a recurring challenge for software architects.\n\nSolution: This work proposes EPAComp, a model that covers this gap and addresses large-scale processing requirements through features such as stream-based constructions and specialized EPAs (e.g., for pattern detection).\n\nIS Theory: We employed Representation theory in this work towards creating a model that represents information system for event processing.\n\nMethod: The model was applied in a real case experiment to create a solution to collect user requests, as streams of events, from around 200 systems, and to provide a dashboard for monitoring their usage. Besides, industry experts qualitatively evaluated the proposal.\n\nResults: The experiment results show an application of the model to handle heterogeneous data in a scalable and efficient manner according to indicators regarding performance, assertiveness of processed output, and degree of cohesion, and coupling of components. In the qualitative results presents that experts asserted EPAComp capabilities fits RTSA requirements.\nContributions: The main contributions is an architectural model for EPA composition that enhances the literature by representing static and dynamic EPA compositions through arrangements of specific aggregation structures; representing state of the art event processing strategies in CEP; and, organize hierarchy of EPA types.","linkCode":null,"source":{"__ref":"Source:70"},"sourceInstance":{"__ref":"SourceInstance:5286"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:49651"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:49652"},"affiliations":[{"__ref":"Affiliation:3020"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]}]},"Author:1039":{"__typename":"Author","id":"1039","ibmer":null},"AuthorName:1035":{"__typename":"AuthorName","id":"1035","firstName":"Luís Henrique Neves","firstNameInitials":"L.H.N.","lastName":"Villaça","author":{"__ref":"Author:1039"}},"Affiliation:241":{"__typename":"Affiliation","id":"241","isIbm":false},"Author:1041":{"__typename":"Author","id":"1041","ibmer":null},"AuthorName:1037":{"__typename":"AuthorName","id":"1037","firstName":"Sean Wolfgand Matsui","firstNameInitials":"S.W.M.","lastName":"Siqueira","author":{"__ref":"Author:1041"}},"Affiliation:6":{"__typename":"Affiliation","id":"6","isIbm":true},"Publication:29184":{"__typename":"Publication","id":"29184","slug":"epacomp-an-architectural-model-for-epa-composition","title":"EPAComp: An Architectural Model for EPA Composition","type":{"__typename":"PublicationType","displayValue":"Conference paper"},"published":"2023-05-29","publishedMeta":{"__typename":"PublishedMeta","source":"SBSI 2023","year":"2023"},"abstract":"Context: Complex Event Processing (CEP) architectures present high applicability in Realtime Streaming Analytics (RTSA) by extracting and generating valuable information from continuous data feeds, like in stock markets, traffic, and patient monitoring. Problem: Although guidelines and models for CEP architectures have been proposed, the composition of its inter-operable elements in charge of processing events, known as Event Processing Agent (EPA), is challenging for software architects. Solution: This work proposes EPAComp, a model that covers this gap and addresses large-scale processing requirements through features such as stream-based constructions and specialized EPAs. IS Theory: We employed the Representation theory to create a model representing information systems for event processing. Method: The model was applied in a real case experiment to create a solution to collect streams of events from around 200 systems and to provide a dashboard for monitoring their usage. Besides, industry experts qualitatively evaluated the proposal. Results: The experiment results show an application of the model to handle heterogeneous data in a scalable and efficient manner according to indicators regarding performance, the assertiveness of processed output, degree of cohesion, and coupling of components. The qualitative results present that experts asserted EPAComp capabilities fit RTSA requirements. Contributions: An architectural model for EPA composition that enhances the literature by (i) representing static and dynamic EPA compositions through arrangements of specific aggregation structures; (ii) defining the state-of-the-art event processing strategies in CEP; and, (iii) organizing the hierarchy of EPA types.","linkCode":null,"source":{"__ref":"Source:70"},"sourceInstance":{"__ref":"SourceInstance:5286"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:1035"},"affiliations":[{"__ref":"Affiliation:241"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:1037"},"affiliations":[{"__ref":"Affiliation:241"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:6"}]}]},"SourceInstance:5266":{"__typename":"SourceInstance","id":"5266","name":"ESWC 2023"},"Publication:21577":{"__typename":"Publication","id":"21577","slug":"an-improved-questionnaire-for-fair-characterization","title":"An Improved Questionnaire for FAIR Characterization","type":{"__typename":"PublicationType","displayValue":"Workshop paper"},"published":"2023-05-28","publishedMeta":{"__typename":"PublishedMeta","source":"ESWC 2023","year":"2023"},"abstract":"The FAIR principles guidelines aim to enhance the discovery and usage of digital objects by humans and computational agents. They are formulated at a high level and, as such, are interpreted and implemented in different ways by communities of practice. Practical approaches outlining FAIR-related characteristics of digital objects are few and far between. This paper analyzes the FAIR principles while considering distinct proposed metrics, questionnaires, and tools for manual, automated, and semi-automated FAIR assessment. Here, we present an improved questionnaire for the FAIR characterization of digital objects. Our goal is not to give a FAIRness grade for digital objects, but to outline their properties related to the FAIR principles, at any point of their data life cycle. Different communities can use the questionnaire to characterize their assets. It is designed from the outset with the additional objective of supporting the creation of bespoke metrics and assisting in automated assessment in the future. We evaluated the questionnaire by applying it to characterize data digital objects from two data repositories of materials science, the ones from Materials Cloud and PubChem.","linkCode":null,"source":{"__ref":"Source:24305"},"sourceInstance":{"__ref":"SourceInstance:5266"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:51055"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:51056"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46441"},"affiliations":[{"__ref":"Affiliation:73"}]}]},"Source:424":{"__typename":"Source","id":"424","longName":"AAAI Conference on Artificial Intelligence","shortName":"AAAI","type":"CONFERENCE"},"SourceInstance:4782":{"__typename":"SourceInstance","id":"4782","name":"AAAI 2023"},"Ibmer:2846":{"__typename":"Ibmer","id":"2846","slug":"emilio-ashton-vital-brazil","displayName":"Emilio Vital Brazil"},"Author:53147":{"__typename":"Author","id":"53147","ibmer":{"__ref":"Ibmer:2846"}},"AuthorName:45367":{"__typename":"AuthorName","id":"45367","firstName":"Emilio","firstNameInitials":null,"lastName":"Ashton Vital Brazil","author":{"__ref":"Author:53147"}},"Author:54677":{"__typename":"Author","id":"54677","ibmer":{"__ref":"Ibmer:693"}},"AuthorName:46901":{"__typename":"AuthorName","id":"46901","firstName":"Eduardo","firstNameInitials":null,"lastName":"Almeida Soares","author":{"__ref":"Author:54677"}},"Author:3178":{"__typename":"Author","id":"3178","ibmer":null},"AuthorName:3213":{"__typename":"AuthorName","id":"3213","firstName":"Lucas C.","firstNameInitials":"L.C.","lastName":"Villa Real","author":{"__ref":"Author:3178"}},"Ibmer:1618":{"__typename":"Ibmer","id":"1618","slug":"vinicius-segura","displayName":"Vinícius Segura"},"Author:54216":{"__typename":"Author","id":"54216","ibmer":{"__ref":"Ibmer:1618"}},"AuthorName:46440":{"__typename":"AuthorName","id":"46440","firstName":"Vinicius","firstNameInitials":null,"lastName":"Segura","author":{"__ref":"Author:54216"}},"Author:54678":{"__typename":"Author","id":"54678","ibmer":null},"AuthorName:46902":{"__typename":"AuthorName","id":"46902","firstName":"Luiz","firstNameInitials":null,"lastName":"Zerkowski","author":{"__ref":"Author:54678"}},"Publication:19483":{"__typename":"Publication","id":"19483","slug":"position-paper-on-dataset-engineering-to-accelerate-science","title":"Position Paper on Dataset Engineering to Accelerate Science","type":{"__typename":"PublicationType","displayValue":"Workshop paper"},"published":"2023-02-13","publishedMeta":{"__typename":"PublishedMeta","source":"AAAI 2023","year":"2023"},"abstract":"Data is a critical element in any discovery process. In the last decades, we observed exponential growth in the volume of available data and the technology to manipulate it. However, data is only practical when one can structure it for a well-defined task. For instance, we need a corpus of text broken into sentences to train a natural language machine-learning model. In this work, we will use the token data set to designate a structured set of data built to perform a well-defined task. Moreover, the dataset will be used in most cases as a blue print of an entity that at any moment can be stored as a table. Specifically, in science, each area has unique forms to organize, gather and handle its datasets. We believe that datasets must be a first-class entity in any knowledge-intensive process, and all workflows should have exceptional attention to datasets’ lifecycle, from their gathering to uses and evolution. We advocate that science and engineering discovery processes are extreme instances of the need for such organization on datasets, claiming for new approaches and tooling. Furthermore, these requirements are more evident when the discovery workflow uses artificial intelligence methods to em-power the subject-matter expert. In this work, we discuss an approach to bringing datasets as a critical entity in the discovery process in science. We illustrate some concepts using material discovery as a use case. We chose this domain because it leverages many significant problems that can be generalized to other science fields","linkCode":null,"source":{"__ref":"Source:424"},"sourceInstance":{"__ref":"SourceInstance:4782"},"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:45367"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46901"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:3213"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46440"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46902"},"affiliations":[{"__ref":"Affiliation:73"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:46441"},"affiliations":[{"__ref":"Affiliation:73"}]}]},"Source:20409":{"__typename":"Source","id":"20409","longName":"Knowledge Engineering Review","shortName":"Knowledge Engineering Review","type":"JOURNAL"},"AuthorName:63474":{"__typename":"AuthorName","id":"63474","firstName":"Viviane","firstNameInitials":"V.","lastName":"Torres Da Silva","author":{"__ref":"Author:3161"}},"Author:24311":{"__typename":"Author","id":"24311","ibmer":null},"AuthorName:63475":{"__typename":"AuthorName","id":"63475","firstName":"Jéssica Soares","firstNameInitials":"J.S.","lastName":"Dos Santos","author":{"__ref":"Author:24311"}},"Affiliation:1082":{"__typename":"Affiliation","id":"1082","isIbm":false},"AuthorName:3951":{"__typename":"AuthorName","id":"3951","firstName":"Raphael","firstNameInitials":"R.","lastName":"Thiago","author":{"__ref":"Author:20135"}},"Author:1386":{"__typename":"Author","id":"1386","ibmer":null},"AuthorName:3950":{"__typename":"AuthorName","id":"3950","firstName":"Elton","firstNameInitials":"E.","lastName":"Soares","author":{"__ref":"Author:1386"}},"Publication:27960":{"__typename":"Publication","id":"27960","slug":"owl-ontology-evolution-understanding-and-unifying-the-complex-changes","title":"OWL ontology evolution: Understanding and unifying the complex changes","type":{"__typename":"PublicationType","displayValue":"Paper"},"published":"2022-11-21","publishedMeta":{"__typename":"PublishedMeta","source":"Knowledge Engineering Review","year":"2022"},"abstract":"Knowledge-based systems and their ontologies evolve due to different reasons. Ontology evolution is the adaptation of an ontology and the propagation of these changes to dependent artifacts such as queries and other ontologies. Besides identifying basic/simple changes, it is imperative to identify complex changes between two versions of the same ontology to make this adaptation possible. There are many definitions of complex changes applied to ontologies in the literature. However, their specifications across works vary both in formalization and textual description. Some works also use different terminologies to refer to a change, while others use the same vocabulary to refer to distinct changes. Therefore, there is a lack of a unified list of complex changes. The main goals of this paper are: (i) present the primary documents that identify complex changes; (ii) provide critical analyses about the set of the complex changes proposed in the literature and the documents mentioning them; (iii) provide a unified list of complex changes mapping different sets of complex changes proposed by several authors; (iv) present a classification for those complex changes; and (v) describe some open directions of the area. The mappings between the complex changes provide a mechanism to relate and compare different proposals. The unified list is thus a reference for the complex changes published in the literature. It may assist the development of tools to identify changes between two versions of the same ontology and enable the adaptation of artifacts that depend on the evolved ontology.","linkCode":null,"source":{"__ref":"Source:20409"},"sourceInstance":null,"authors":[{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:63474"},"affiliations":[{"__ref":"Affiliation:6"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:63475"},"affiliations":[{"__ref":"Affiliation:1082"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:3951"},"affiliations":[{"__ref":"Affiliation:6"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:3950"},"affiliations":[{"__ref":"Affiliation:6"}]},{"__typename":"PublicationHasAuthorName","authorName":{"__ref":"AuthorName:16604"},"affiliations":[{"__ref":"Affiliation:6"}]}]},"ROOT_QUERY":{"__typename":"Query","blogPostsSearch({\"filterBy\":{\"ibmerSlug\":\"leonardo-guerreiro-azevedo\"},\"limit\":4,\"start\":0})":{"__typename":"BlogPostsSearchConnection","nodes":[],"totalCount":0},"ibmersBySlug({\"slugs\":[\"leonardo-guerreiro-azevedo\"]})":[{"__ref":"Ibmer:2024"}],"patents({\"after\":\"-1\",\"filterBy\":{\"ibmerSlug\":\"leonardo-guerreiro-azevedo\"},\"first\":10,\"sortBy\":{\"direction\":\"DESC\",\"option\":\"DATE\"}})":{"__typename":"QueryPatents_Connection","nodes":[{"__typename":"Patent","num":"11989628","title":"MACHINE TEACHING COMPLEX CONCEPTS ASSISTED BY COMPUTER VISION AND KNOWLEDGE REASONING","country":"US","date":"2024-05-20"},{"__typename":"Patent","num":"11048877","title":"SYSTEM AND METHOD FOR GENERATING ONTOLOGIES USING NATURAL LANGUAGE UTTERANCES","country":"US","date":"2021-06-28"},{"__typename":"Patent","num":"10958531","title":"ON-DEMAND REMOTE PREDICTIVE MONITORING FOR INDUSTRIAL EQUIPMENT ANALYSIS AND COST FORECAST","country":"US","date":"2021-03-22"}],"totalCount":3},"publications({\"after\":\"-1\",\"filterBy\":{\"ibmerSlug\":\"leonardo-guerreiro-azevedo\"},\"first\":10,\"sortBy\":\"NEWEST\"})":{"__typename":"QueryPublications_Connection","totalCount":45,"nodes":[{"__ref":"Publication:153352"},{"__ref":"Publication:157066"},{"__ref":"Publication:149296"},{"__ref":"Publication:86705"},{"__ref":"Publication:22066"},{"__ref":"Publication:20759"},{"__ref":"Publication:29184"},{"__ref":"Publication:21577"},{"__ref":"Publication:19483"},{"__ref":"Publication:27960"}]}}},"ssrDateString":"2025-03-01T16:00:32.384Z"},"__N_SSP":true},"page":"/people/[personSlug]","query":{"personSlug":"leonardo-guerreiro-azevedo"},"buildId":"v9TvvervEOiCcTzEPxR9P","isFallback":false,"gssp":true,"locale":"en-US","locales":["en-US"],"defaultLocale":"en-US","scriptLoader":[]}</script></body></html>