<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>8119</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Elsevier BV</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Modelling of measuring systems – From white box models to cognitive approaches</title>
    <abstract language="eng">Mathematical models of measuring systems and processes play an essential role in metrology and practical measurements. They form the basis for understanding and evaluating measurements, their results and their trustworthiness.&#13;
Classic analytical parametric modelling is based on largely complete knowledge of measurement technology and the measurement process.&#13;
But due to digital transformation towards the Internet of Things (IIoT) with an increasing number of intensively and flexibly networked measurement systems and consequently ever larger amounts of data to be processed, data-based modelling approaches have gained enormous importance.&#13;
This has led to new approaches in measurement technology and industry like Digital Twins, Self-X Approaches, Soft Sensor Technology and Data and Information Fusion.&#13;
In the future, data-based modelling will be increasingly dominated by intelligent, cognitive systems. Evaluating of the accuracy, trustworthiness and the functional uncertainty of the corresponding models is required.&#13;
This paper provides a concise overview of modelling in metrology from classical white box models to intelligent, cognitive data-driven solutions identifying advantages and limitations. Additionally, the approaches to merge trustworthiness and metrological uncertainty will be discussed.</abstract>
    <parentTitle language="eng">Measurement: Sensors</parentTitle>
    <identifier type="issn">2665-9174</identifier>
    <identifier type="doi">10.1016/j.measen.2024.101503</identifier>
    <enrichment key="opus_import_data">{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,30]],"date-time":"2024-12-30T13:10:03Z","timestamp":1735564203004,"version":"3.32.0"},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Measurement: Sensors"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1016\/j.measen.2024.101503","type":"journal-article","created":{"date-parts":[[2024,12,30]],"date-time":"2024-12-30T12:33:13Z","timestamp":1735561993000},"page":"101503","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modelling of measuring systems \u2013 From white box models to cognitive approaches"],"prefix":"10.1016","author":[{"given":"Nadine","family":"Schiering","sequence":"first","affiliation":[]},{"given":"Sascha","family":"Eichst\u00e4dt","sequence":"additional","affiliation":[]},{"given":"Michael","family":"Heizmann","sequence":"additional","affiliation":[]},{"given":"Wolfgang","family":"Koch","sequence":"additional","affiliation":[]},{"given":"Linda-Sophie","family":"Schneider","sequence":"additional","affiliation":[]},{"given":"Stephan","family":"Scheele","sequence":"additional","affiliation":[]},{"given":"Klaus-Dieter","family":"Sommer","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.measen.2024.101503_bib1","unstructured":"BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP, and OIML, Guide to the expression of uncertainty in measurement \u2014 Part 6: developing and using measurement models, Joint Committee for Guides in Metrology, GUM-6: 2020."},{"key":"10.1016\/j.measen.2024.101503_bib2","article-title":"Modelling of networked measuring systems -- from white-box models to data based approaches","author":"Sommer","year":"2023","journal-title":"arXiv:2312.13744"},{"key":"10.1016\/j.measen.2024.101503_bib3","unstructured":"L.-S. Schneider, P. Krauss, N. Schiering, C. Syben, R. Schielein, A. Maier, Data-driven modeling in metrology \u2013 a short introduction, Current Developments and Future Perspectives, De Gruyter J., in publication process."},{"issue":"2","key":"10.1016\/j.measen.2024.101503_bib4","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1515\/teme-2015-0126","article-title":"Modellbildung in der Mess- und Automatisierungstechnik","volume":"83","author":"Heizmann","year":"2016","journal-title":"TM - Tech. Mess."},{"key":"10.1016\/j.measen.2024.101503_bib5","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1088\/0026-1394\/43\/4\/S06","article-title":"Systematic approach to the modelling of measurements for uncertainty evaluation","volume":"43","author":"Sommer","year":"2006","journal-title":"Metrologia"},{"key":"10.1016\/j.measen.2024.101503_bib6","article-title":"International vocabulary of metrology \u2013 basic and general concepts and associated terms, Joint Committee for Guides in Metrology","volume":"200","year":"2012","journal-title":"JCGM"},{"key":"10.1016\/j.measen.2024.101503_bib7","article-title":"Evaluation of measurement data \u2014 guide to the expression of uncertainty in measurement, joint committee for guides in metrology","volume":"100","year":"2008","journal-title":"JCGM"},{"key":"10.1016\/j.measen.2024.101503_bib8","series-title":"2007 Workshop &amp; Symposium Metrology's Impact on Products and Services July 29 \u2013 August 2","article-title":"Systematic modelling of measurements and sensor signal processing for uncertainty analysis","author":"Sommer","year":"2007"},{"key":"10.1016\/j.measen.2024.101503_bib9","series-title":"Employing Discretised State-Space Forms","article-title":"Modelling of dynamic measurements for uncertainty analysis","author":"Sommer","year":"2008"},{"key":"10.1016\/j.measen.2024.101503_bib10","unstructured":"K.-D. Sommer, M. Heizmann, R. Kessel, A. Sch\u00fctze, R. Kacker, Future modelling challenges to measurement and for evaluating measurement results, 2018 Measurement Science Conference Anaheim, California."},{"issue":"52","key":"10.1016\/j.measen.2024.101503_bib11","first-page":"224","article-title":"A systematic approach to the modelling of measurements for uncertainty evaluation","volume":"13","author":"Sommer","year":"2005","journal-title":"J. Phys.: Conf. Ser."},{"key":"10.1016\/j.measen.2024.101503_bib12","series-title":"NCSL International Workshop &amp; Symposium, August 3-7","article-title":"A bayesian approach to information fusion for sensor networks","author":"Stiller","year":"2008"},{"key":"10.1016\/j.measen.2024.101503_bib13","article-title":"Moderne Ans\u00e4tze zur Bewertung der Messunsicherheit","volume":"8","author":"Sommer","year":"2005","journal-title":"Universit\u00e4t der Bundeswehr M\u00fcnchen"},{"issue":"3","key":"10.1016\/j.measen.2024.101503_bib14","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1524\/teme.2007.74.3.93","article-title":"Informationsfusion \u2013 eine \u00fcbersicht (information fusion \u2013 an overview)","volume":"74","author":"Ruser","year":"2007","journal-title":"TM - Tech. Mess."},{"issue":"6","key":"10.1016\/j.measen.2024.101503_bib15","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1515\/auto-2020-0059","article-title":"Metrology for heterogeneous sensor networks and Industry 4.0","volume":"68","author":"Eichst\u00e4dt","year":"2020","journal-title":"at - Automatisierungstechnik"},{"key":"10.1016\/j.measen.2024.101503_bib16","series-title":"Informationsfusion in der Mess- und Sensortechnik, J. Beyerer, F. Puente Le\u00f3n, K.-D. Sommer (Hrsg.)","article-title":"Evidenztheorie: Ein Vergleich zwischen Bayes- und Dempster Shafer Methoden","author":"Dietmayer","year":"2006"},{"issue":"4","key":"10.1016\/j.measen.2024.101503_bib17","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1515\/teme-2022-0036","article-title":"Measurement systems and sensors with cognitive features","volume":"89","author":"Sommer","year":"2022","journal-title":"TM - Tech. Mess."},{"issue":"3","key":"10.1016\/j.measen.2024.101503_bib18","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1515\/teme-2022-0094","article-title":"Perspectives on AI-driven systems for multiple sensor data fusion","volume":"90","author":"Koch","year":"2023","journal-title":"TM - Tech. Mess."},{"issue":"3","key":"10.1016\/j.measen.2024.101503_bib19","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1524\/teme.2007.74.3.103","article-title":"Bayes'sche Methodik zur lokalen Fusion heterogener Informationsquellen (Bayesian Methodology for the Local Fusion of Heterogeneous Information Sources)","volume":"74","author":"Beyerer","year":"2007","journal-title":"TM - Tech. Mess."},{"key":"10.1016\/j.measen.2024.101503_bib20","article-title":"Fusion heterogener informationsquellen","author":"Beyerer","year":"2006","journal-title":"Informationsfusion in der Mess- und Sensortechnik. Hrsg.: J. Beyerer, Universit\u00e4tsverlag Karlsruhe"},{"key":"10.1016\/j.measen.2024.101503_bib21","series-title":"Digital twin \u2013 concepts and terminology, edition 1.0","year":"2023"},{"key":"10.1016\/j.measen.2024.101503_bib22","author":"Stark"},{"issue":"13","key":"10.1016\/j.measen.2024.101503_bib23","article-title":"How to tell the difference between a model and a digital twin","volume":"7","author":"Wright","year":"2020","journal-title":"Adv. Model. and Simul. In Eng. Sci."},{"key":"10.1016\/j.measen.2024.101503_bib24","article-title":"How much can i trust you?","author":"Bykov","year":"2020","journal-title":"quantifying uncertainties in explaining neural networks"},{"key":"10.1016\/j.measen.2024.101503_bib25","doi-asserted-by":"crossref","DOI":"10.3389\/fcomp.2023.1132580","article-title":"Addressing uncertainty in the safety assurance of machine-learning","volume":"5","author":"Burton","year":"2023","journal-title":"Front. Comput. Sci."},{"issue":"3","key":"10.1016\/j.measen.2024.101503_bib26","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10994-021-05946-3","article-title":"Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods","volume":"110","author":"H\u00fcllermeier","year":"2021","journal-title":"Mach. Learn."},{"key":"10.1016\/j.measen.2024.101503_bib27","unstructured":"J. Deuschel, A. Foltyn, K. Roscher, S. Scheele, The role of uncertainty quantification for trustworthy AI, in publication process."},{"key":"10.1016\/j.measen.2024.101503_bib28","article-title":"A survey of uncertainty in deep neural networks","author":"Gawlikowski","year":"2021","journal-title":"arXiv preprint arXiv:2107.03342"},{"key":"10.1016\/j.measen.2024.101503_bib29","series-title":"Aleatoric and Epistemic Uncertainty in Machine Learning","author":"H\u00fcllermeier","year":"2021"},{"key":"10.1016\/j.measen.2024.101503_bib30","article-title":"A survey on uncertainty reasoning and quantification for decision making: belief theory meets deep learning","author":"Guo","year":"2022","journal-title":"arXiv preprint arXiv:2206.05675"}],"container-title":["Measurement: Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2665917424004793?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2665917424004793?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,12,30]],"date-time":"2024-12-30T12:33:20Z","timestamp":1735562000000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2665917424004793"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":30,"alternative-id":["S2665917424004793"],"URL":"https:\/\/doi.org\/10.1016\/j.measen.2024.101503","relation":{},"ISSN":["2665-9174"],"issn-type":[{"value":"2665-9174","type":"print"}],"subject":[],"published":{"date-parts":[[2024,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Modelling of measuring systems \u2013 From white box models to cognitive approaches","name":"articletitle","label":"Article Title"},{"value":"Measurement: Sensors","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.measen.2024.101503","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"simple-article","name":"content_type","label":"Content Type"},{"name":"copyright","label":"Copyright"}],"article-number":"101503"}}</enrichment>
    <enrichment key="local_crossrefLicence">https://www.elsevier.com/tdm/userlicense/1.0/</enrichment>
    <enrichment key="local_import_origin">crossref</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">doi-import</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Nadine Schiering</author>
    <author>Sascha Eichstädt</author>
    <author>Michael Heizmann</author>
    <author>Wolfgang Koch</author>
    <author>Linda-Sophie Schneider</author>
    <author>Stephan Scheele</author>
    <author>Klaus-Dieter Sommer</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
</export-example>
