{"id":103271,"date":"2024-04-15T12:00:00","date_gmt":"2024-04-15T10:00:00","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&p=103271"},"modified":"2025-02-04T16:59:38","modified_gmt":"2025-02-04T15:59:38","slug":"european-cybersecurity-certified","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/european-cybersecurity-certified\/","title":{"rendered":"The Utopia of European Cybersecurity Certifications"},"content":{"rendered":"

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Interoperable automation can benefit cybersecurity certification processes that result from the EU Cybersecurity Act (e.g. EUCS) so that they represent less overhead for the stakeholders involved. The development of key standardization efforts involving relevant stakeholders (e.g. regulators) is needed to fully realize these benefits. EU projects like H2020 MEDINA, HEU COBALT and communities such as EUROSCAL are well on the way to achieving this goal. However, more practical experience is needed to make continuous certification with automation a reality.<\/p>\n

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\n\n\n\n<\/thead>\n\n\n\n\n\n\n\n\n<\/tbody>\n<\/table>\n

Subscription<\/th>\nincluded<\/th>\nPurchase<\/th>\n
without<\/td>\n−<\/td>\n29,00 \u20ac<\/td>\n
Digital<\/td>\n−<\/td>\n27,55 \u20ac<\/td>\n
Expert<\/td>\n−<\/td>\n26,10 \u20ac<\/td>\n
Professional<\/td>\n✓<\/span><\/td>\n0,00 \u20ac<\/td>\n
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\t\t

Serious Gaming and the Energy Transition<\/h4>\n
Collaborative knowledge generation and interactive understanding of complex interrelationships<\/div>
Janine Gondolf<\/a> \n \"ORCID<\/a>, Gert Mehlmann<\/a>, J\u00f6rn Hartung<\/a>, Bernd Schweinshaut<\/a>, Anne Bauer<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Conveying the complexity and multifaceted nature of the energy transition to a broad audience is a challenge. This article demonstrates how interactive serious games on a multitouch table can help make connections tangible and comprehensible. The games and the table were used in various conversational contexts. These are presented here in three case vignettes based on participant observation of the different applications, as well as situated and shared reflection. The vignettes demonstrate how interaction can trigger epistemic processes, enable shifts in perspective, and foster collective thinking, all of which are necessary for shaping the future of society as a whole. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 2 | Pages 62-69<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Building\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Building the Future Workforce Today<\/h4>\n
Trendiation as a strategic framework for employee qualification and training<\/div>
J\u00fcrgen Fritz<\/a>, Sebastian Busse<\/a>, Ingo Dieckmann<\/a>, Torsten Laub<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n As Industry 4.0 and artificial intelligence reshape organizational capabilities, traditional training systems struggle to keep pace with evolving skill requirements. This paper introduces Trendiation\u2014a structured methodology for translating emerging trends into actionable strategies\u2014as a systematic approach to this challenge. Through a workshop-based application examining Edutainment, Human-Centered Design, and Workforce Transformation, we demonstrate how organizations can move from abstract trend identification to concrete qualification requirements and prioritized training initiatives. The method produces a traceable artifact chain spanning trend framing, capability-gap assessment, and implementation roadmaps. Participant evaluations indicate high perceived clarity and practical utility. By bridging foresight analysis with participatory design, Trendiation enables organizations to proactively cultivate adaptive capabilities and build learning cultures aligned with future work ... <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 2 | Pages 22-29 | DOI 10.30844\/I4SE.26.2.22<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Operationalizing\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Operationalizing Ethical AI with tachAId<\/h4>\n
Validating an interactive advisory tool in two manufacturing use cases<\/div>
Pavlos Rath-Manakidis<\/a>, Henry Huick<\/a>, Bj\u00f6rn Kr\u00e4mer<\/a> \n \"ORCID<\/a>, Laurenz Wiskott<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Integrating artificial intelligence (AI) into workplace processes promises significant efficiency gains, yet organizations face numerous ethical challenges that stakeholders are often initially unaware of\u2014from opacity in decision-making to algorithmic bias and premature automation risks. This paper presents the design and validation of tachAId, an interactive advisory tool aimed at embedding human-centered ethical considerations into the development of AI solutions. It reports on a validation study conducted across two distinct industrial AI applications with varying AI maturity. tachAId successfully directs attention to critical ethical considerations across the AI solution lifecycle that might be overlooked in technically-focused development. However, the findings also reveal a central tension: while effective in raising awareness, the tool\u2019s non-linear design creates significant usability challenges, indicating a user preference for more structured, linear guidance, especially ... <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 1 | Pages 50-59 | DOI 10.30844\/I4SE.26.1.48<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"XAI\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

XAI for Predicting and Nudging Worker Decision-Making<\/h4>\n
Feasibility and perceived ethical issues<\/div>
Jan-Phillip Herrmann<\/a> \n \"ORCID<\/a>, Catharina Baier<\/a>, Sven Tackenberg<\/a> \n \"ORCID<\/a>, Verena Nitsch<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Explainable artificial intelligence (XAI)-based nudging, while ethically complex, may offer a favorable alternative to rigid, algorithmically generated schedules that simultaneously respects worker autonomy and improves overall scheduling performance on the shop floor. This paper presents a controlled laboratory study demonstrating the successful nudging of 28 industrial engineering students in a job shop simulation. The study shows that the observed concordance between students\u2019 sequencing decisions and a predefined target sequence increases by 9% through nudging. This is done by using XAI to analyze students\u2019 preferences and adjusting task deadlines and priorities in the simulation. The paper discusses the ethical issues of nudging, including potential manipulation, illusory autonomy, and reducing people to numbers. To mitigate these issues, it offers recommendations for implementing the XAI-based nudging approach in practice and highlights its strengths relative to rigid, ... <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 1 | Pages 70-78<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Improving\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Improving Documentation Quality and Creating Time for Core Activities<\/h4>\n
Success factors for implementing AI-based documentation systems in nursing care<\/div>
Sophie Berretta<\/a> \n \"ORCID<\/a>, Elisabeth Liedmann<\/a> \n \"ORCID<\/a>, Paul-Fiete Kramer<\/a> \n \"ORCID<\/a>, Anja Gerlmaier<\/a>, Christopher Schmidt<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Demographic change is accompanied by both a growing demand for care and a shortage of qualified nursing staff. Consequently, AI-based technologies are increasingly becoming a focus of care-related innovations. Their aim is to reduce workload pressure, save time, and enhance the attractiveness of the nursing profession. Using the example of AI-supported documentation systems for admission interviews, this article examines to what extent such systems can contribute to improvements in work processes and care quality, focusing on the perspectives of nursing professionals and nursing experts. The results indicate potential for workload relief, enhanced documentation quality, and the reallocation of time resources toward direct patient care. However, realizing these potentials requires a human-centered and context-sensitive implementation approach. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 1 | Pages 154-160 | DOI 10.30844\/I4SE.26.1.146<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"JOCAT\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

JOCAT (Job Change Acceptance Toolbox)<\/h4>\n
A change management approach for implementing AI systems ethically and sustainably<\/div>
Sophie Berretta<\/a> \n \"ORCID<\/a>, Pauline Nolte<\/a>, Annette Kluge<\/a> \n \"ORCID<\/a>, Skrolan Kopka<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n AI systems challenge conventional change management due to their dynamic, opaque, and ethically sensitive nature. This article applies insights from established change models to AI-specific challenges, illustrated by a real-world use case. The resulting propositions are substantiated by six expert interviews, which integrate practical perspectives. Together, they inform the development of the Job Change Acceptance Toolbox (JOCAT), a modular, practice-oriented resource designed to support the implementation of human-centered, ethical, and sustainable AI-related change processes. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | Edition 1 | Pages 80-91 | DOI 10.30844\/I4SE.26.1.74<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

Interoperable automation can benefit cybersecurity certification processes that result from the EU Cybersecurity Act (e.g. EUCS) so that they represent less overhead for the stakeholders involved. The development of key standardization efforts involving relevant stakeholders (e.g. regulators) is needed to fully realize these benefits. EU projects like H2020 MEDINA, HEU COBALT and communities such as EUROSCAL are well on the way to achieving this goal. However, more practical experience is needed to make continuous certification with automation a reality.<\/p>\n","protected":false},"featured_media":107472,"menu_order":0,"template":"","categories":[79167,67575,79298],"tags":[68764,79457,68762],"product_cat":[3300],"topic":[68005,79491,79210,79352,79208],"technology":[67790,76354,79215,79493,71297,67596],"knowhow":[],"industry":[79353,79220,79354],"writer":[83622,83723],"content-type":[],"potential":[67651,68923,67652],"solution":[69028,78380,69029],"glossary":[],"class_list":{"0":"post-103271","1":"article","2":"type-article","3":"status-publish","4":"has-post-thumbnail","6":"category-design-en","7":"category-design","8":"category-typeset","9":"tag-standardisation","10":"tag-standardisierung-en","11":"tag-standardisierung","12":"product_cat-article","13":"topic-automation","14":"topic-change-management-en","15":"topic-change-management","16":"topic-data-privacy","17":"topic-datenschutz","18":"technology-artificial-intelligence","19":"technology-blockchain-en","20":"technology-digitalisierung","21":"technology-digitalization","22":"technology-machine-learning","23":"technology-software-en","24":"industry-information-security","25":"industry-manufacturing","26":"industry-smart-objects","27":"writer-alexander-lawall-en","28":"writer-jesus-luna-garcia-en","29":"potential-dienstleistungen","30":"potential-dynamics","31":"potential-services","32":"solution-anlaufmanagement","33":"solution-procurement","34":"solution-start-up-management","35":"product","36":"first","37":"instock","38":"downloadable","39":"virtual","40":"sold-individually","41":"taxable","42":"purchasable","43":"product-type-article"},"uagb_featured_image_src":{"full":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min.jpeg",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-150x150.jpeg",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-666x375.jpeg",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-768x432.jpeg",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-1024x576.jpeg",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-1032x320.jpeg",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-764x376.jpeg",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-392x320.jpeg",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-608x496.jpeg",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-640x325.jpeg",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-274x376.jpeg",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-514x292.jpeg",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-320x440.jpeg",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-514x289.jpeg",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-196x180.jpeg",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min.jpeg",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min.jpeg",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-510x510.jpeg",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-510x287.jpeg",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-100x100.jpeg",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/04\/AdobeStock_565594360-min-64x36.jpeg",64,36,true]},"uagb_author_info":{"display_name":"Florian Goldmann","author_link":"https:\/\/industry-science.com\/en\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Interoperable automation can benefit cybersecurity certification processes that result from the EU Cybersecurity Act (e.g. EUCS) so that they represent less overhead for the stakeholders involved. The development of key standardization efforts involving relevant stakeholders (e.g. regulators) is needed to fully realize these benefits. EU projects like H2020 MEDINA, HEU COBALT and communities such as…","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/103271","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/types\/article"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media\/107472"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=103271"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=103271"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=103271"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=103271"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=103271"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=103271"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=103271"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=103271"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=103271"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=103271"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=103271"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=103271"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=103271"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}