Common use of Conclusions Clause in Contracts

Conclusions. The efforts in this deliverable were turned to the definition of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At first, we performed a SotA analysis for the two visualization approaches are going to be used in PROPHESY-AR: data visualization and augmented reality. We combined the finding of the SotA analysis with requirements provided by user stories in Task 2.4 and generally by WP2, in order to achieve the general specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. After, for each approach, we defined more detailed specifications based on defined use – cases. In details we provided a methodology for defining and implementing the dashboard are going to be used for the data visualization in Task 5.2. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. X. Xxxxxxxx, "The 4+1 View Model of architecture," IEEE Softw., vol. 12, pp. 42-50, November 1995. [2] X. Xxxxxxxx and X. Xxxxx, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-Xxxxxx, 2012. [3] Deloitte, "Predictive Maintenance amd the smart factory," 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdf. [4] Xxxxx Xxxxxxx, Xxxxxx Xxxxxxxxx, Xxxxxx Xxxxxxxxxxxx, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance and the digital supply network," Deloitte, May 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.html. [5] X. Xxxxx-Xxxxxx, X. Xxxxxxxxxxx and M. ten Hompel, "Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4, Berlin, Springer, 2017, pp. 38-42. [6] X. XXXXXX-XXXXXX, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des Projekts. Integrative Softwarelösungen für ein intelligentes, befarfsorientiertes Instandhaltungsmanagement in komplexen Produktionsumgebungen," Unternehmen der Zukunft, no. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdf, pp. 30-32, 2016. [7] FRAUNHOFER FEP, "Smart Service Welt Verbundprojekt "Glass@Service"," Fraunhofer FEP, [Online]. Available: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]. [8] F.-X. XXXXXXXXXXXX and X. XXXXXXX, "Augmented Reality für den Mittelstand. Forschungsprojekt Across," IT&Production, pp. 40-41, 2018. [9] X. XXXXXX, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]. [10] DFKI, "Cognitive Workflow Capturing and Rendering with On-Body Sensor Networks," DFKI, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]. [11] PWC, Mainnovation, "Predictive Maintenance 4.0: Predict the unpredictable," PWC, Mainnovation, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdf. [12] Xxxx Xxxxxxx, Xxxxxxx Xxxxxx - Knime, "Anomaly Detection in Predictive Maintenance: Time Alignment and Visualization," 2015. [Online]. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdf. [13] Xxxxx Xxxxxx, Presenso, "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx Xxxxx, Xxxxxxx Xxxxxxxxxxxx - IBM redbooks, "IBM Predictive Maintenance and Quality 2.0 Technical Overview," June 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdf. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovae, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] Augmensys, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.

Conclusions. The efforts in In this deliverable were turned paper we demonstrated how adaptable SLA management is essential for companies that want to use Cloud services and complies with the definition Cloud Computing self-service, on-demand characteristics to change SLAs during runtime. High utilization of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At first, we performed a SotA analysis infrastructure for the two visualization approaches are going provider and an ideal pay per use basis for the companies can therefore be achieved. With A-SLO-A it is possible to be used get customer specific SLAs automated in PROPHESYacceptable conditions for both REFERENCES Xxxxxxx, X., Music, D., Xxxxxxx, P., and Xxxxxxx, S. (2009). Vieslaf framework: Enabling adaptive and versatile sla-AR: data visualization and augmented realitymanagement. We combined the finding In Proceedings of the SotA analysis with requirements provided by user stories in Task 2.4 6th Inter- national Workshop on Grid Economics and generally by WP2Business Models, in order to achieve the general specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. AfterGECON ’09, for each approach, we defined more detailed specifications based on defined use – cases. In details we provided a methodology for defining and implementing the dashboard are going to be used for the data visualization in Task 5.2. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. X. Xxxxxxxx, "The 4+1 View Model of architecture," IEEE Softw., vol. 12, pp. 42-50, November 1995. [2] X. Xxxxxxxx and X. Xxxxx, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-Xxxxxx, 2012. [3] Deloitte, "Predictive Maintenance amd the smart factory," 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdf. [4] Xxxxx Xxxxxxx, Xxxxxx Xxxxxxxxx, Xxxxxx Xxxxxxxxxxxx, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance and the digital supply network," Deloitte, May 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.html. [5] X. Xxxxx-Xxxxxx, X. Xxxxxxxxxxx and M. ten Hompel, "Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4pages 60–73, Berlin, SpringerXxxxxx- xxxx. Xxxxxxxx-Verlag. Cloud Research Center. University of Applied Science Xxxx- xxxxxx. xxxx://xxx.xxxxx.xx-furtwangen.de. Distributed Management Task Force (2010). Architecture for managing clouds. xxxx://xxxx.xxx. FOSII Team (2012). Foundations of self-governing ict infrastructures website. xxxx://xxx.xxxxxxx.xxxxxx. xx.xx/xxxxxxxxx/XXXXX. Xxxxx, 2017X., pp. 38-42. [6] X. XXXXXX-XXXXXXTheilmann, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des Projekts. Integrative Softwarelösungen für ein intelligentesX., befarfsorientiertes Instandhaltungsmanagement in komplexen Produktionsumgebungen," Unternehmen der Zukunft, no. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdf, pp. 30-32, 2016. [7] FRAUNHOFER FEP, "Smart Service Welt Verbundprojekt "Glass@Service"," Fraunhofer FEP, [Online]. Available: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]. [8] F.-X. XXXXXXXXXXXX and X. XXXXXXX, "Augmented Reality für den Mittelstand. Forschungsprojekt Across," IT&Production, pp. 40-41, 2018. [9] X. XXXXXX, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]. [10] DFKI, "Cognitive Workflow Capturing and Rendering with On-Body Sensor Networks," DFKI, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]. [11] PWC, Mainnovation, "Predictive Maintenance 4.0: Predict the unpredictable," PWC, Mainnovation, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdf. [12] Xxxx Xxxxxxx, Xxxxxxx Xxxxxx - KnimeX., "Anomaly Detection in Predictive Maintenanceand Xxxxxxx, K. (2011). Service Level Agreements for Cloud Comput- ing, chapter A Reference Architecture for Multi-Level SLA Management, pages 13–26. Springer-Verlag. ISO/IEC SC 38 Study Group (2011). Jtc 1/sc 38 study group report on cloud computing. Technical re- port, International Organization for Standardization. xxxx://xxxxx.xxx.xxx. Xxxxxxx, X. X., Xxxxxxx, X., and Xxxxxxxxxx, C. (2011). Sla*: Time Alignment An abstract syntax for service level agreements. 11th IEEE/ACM International Conference on Grid Com- puting, pages 217–224. Xxxxxxxxxx, B., Xxx, J., Xx, S., Xxxx, Y., So, N., and Visualization," 2015Un- behagen, P. (2010). [Online]Cloud reference framework. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdfTech- nical report, Internet Engineering Task Force. [13] Xxxxx http:// xxxxx.xxxx.xxx/ html/ draft-xxxxxxxxxx-cloud-reference- framework-00. Xxx, X., Xxxx, X., Xxx, X., Xxxx, X. X., Xxxxxxx, X. X., Xxx- xxx, X. X., and Xxxx, X. X. (2011). Nist cloud comput- ing reference architecture. Technical report, National Institute of Standards and Technology. Xxxxxx, PresensoX., "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx XxxxxX., Xxxxxxx Xxxxxxxxxxxx - IBM redbooksXxx, "IBM Predictive Maintenance A., Xxxx, X. X., and Quality 2.0 Technical Overview," June 2015Xxxxxx, R. (2003). [Online]Web Service Level Agreement (WSLA) Language Specification, v1.0. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdfSLA@SOI. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015SLA@SOI projekt website. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovae, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] Augmensys, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.http:// xxx-xx-xxx.xx/.

Conclusions. The efforts in In this deliverable were turned paper we demonstrated how adaptable SLA management is essential for companies that want to use Cloud services and complies with the definition Cloud Computing self-service, on-demand characteristics to change SLAs during runtime. High utilization of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At first, we performed a SotA analysis infrastructure for the two visualization approaches are going provider and an ideal pay per use basis for the companies can therefore be achieved. With A-SLO-A it is possible to be used get customer specific SLAs automated in PROPHESYacceptable conditions for both REFERENCES Brandic, I., Music, D., Xxxxxxx, P., and Dustdar, S. (2009). Vieslaf framework: Enabling adaptive and versatile sla-AR: data visualization and augmented realitymanagement. We combined the finding In Proceedings of the SotA analysis with requirements provided by user stories in Task 2.4 6th Inter- national Workshop on Grid Economics and generally by WP2Business Models, in order to achieve the general specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. AfterGECON ’09, for each approach, we defined more detailed specifications based on defined use – cases. In details we provided a methodology for defining and implementing the dashboard are going to be used for the data visualization in Task 5.2. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. X. Xxxxxxxx, "The 4+1 View Model of architecture," IEEE Softw., vol. 12, pp. 42-50, November 1995. [2] X. Xxxxxxxx and X. Xxxxx, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-Xxxxxx, 2012. [3] Deloitte, "Predictive Maintenance amd the smart factory," 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdf. [4] Xxxxx Xxxxxxx, Xxxxxx Xxxxxxxxx, Xxxxxx Xxxxxxxxxxxx, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance and the digital supply network," Deloitte, May 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.html. [5] X. Xxxxx-Xxxxxx, X. Xxxxxxxxxxx and M. ten Hompel, "Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4pages 60–73, Berlin, Xxxxxx- xxxx. Springer-Verlag. Cloud Research Center. University of Applied Science Furt- xxxxxx. xxxx://xxx.xxxxx.xx-furtwangen.de. Distributed Management Task Force (2010). Architecture for managing clouds. xxxx://xxxx.xxx. FOSII Team (2012). Foundations of self-governing ict infrastructures website. xxxx://xxx.xxxxxxx.xxxxxx. xx.xx/xxxxxxxxx/XXXXX. Xxxxx, 2017J., pp. 38-42. [6] X. XXXXXX-XXXXXXXxxxxxxxx, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des Projekts. Integrative Softwarelösungen für ein intelligentesW., befarfsorientiertes Instandhaltungsmanagement in komplexen Produktionsumgebungen," Unternehmen der Zukunft, no. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdf, pp. 30-32, 2016. [7] FRAUNHOFER FEP, "Smart Service Welt Verbundprojekt "Glass@Service"," Fraunhofer FEP, [Online]. Available: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]. [8] F.-X. XXXXXXXXXXXX and X. XXXXXXX, "Augmented Reality für den Mittelstand. Forschungsprojekt Across," IT&Production, pp. 40-41, 2018. [9] X. XXXXXX, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]. [10] DFKI, "Cognitive Workflow Capturing and Rendering with On-Body Sensor Networks," DFKI, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]. [11] PWC, Mainnovation, "Predictive Maintenance 4.0: Predict the unpredictable," PWC, Mainnovation, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdf. [12] Xxxx Xxxxxxx, Xxxxxxx Xxxxxx - KnimeA., "Anomaly Detection in Predictive Maintenanceand Xxxxxxx, K. (2011). Service Level Agreements for Cloud Comput- ing, chapter A Reference Architecture for Multi-Level SLA Management, pages 13–26. Springer-Verlag. ISO/IEC SC 38 Study Group (2011). Jtc 1/sc 38 study group report on cloud computing. Technical re- port, International Organization for Standardization. xxxx://xxxxx.xxx.xxx. Xxxxxxx, X. X., Xxxxxxx, F., and Kotsokalis, C. (2011). Sla*: Time Alignment An abstract syntax for service level agreements. 11th IEEE/ACM International Conference on Grid Com- puting, pages 217–224. Xxxxxxxxxx, B., Chu, J., Ma, S., Meng, Y., So, N., and Visualization," 2015Un- behagen, P. (2010). [Online]Cloud reference framework. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdfTech- nical report, Internet Engineering Task Force. [13] Xxxxx http:// xxxxx.xxxx.xxx/ html/ draft-xxxxxxxxxx-cloud-reference- framework-00. Liu, F., Tong, J., Mao, J., Xxxx, X. X., Xxxxxxx, X. X., Bad- ger, M. L., and Leaf, X. X. (2011). Nist cloud comput- ing reference architecture. Technical report, National Institute of Standards and Technology. Xxxxxx, PresensoH., "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx XxxxxA., Xxxxxxx Xxxxxxxxxxxx - IBM redbooksXxx, "IBM Predictive Maintenance A., Xxxx, X. X., and Quality 2.0 Technical Overview," June 2015Xxxxxx, R. (2003). [Online]Web Service Level Agreement (WSLA) Language Specification, v1.0. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdfSLA@SOI. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015SLA@SOI projekt website. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovae, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] Augmensys, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.http:// xxx-xx-xxx.xx/.

Conclusions. The efforts in objective of this deliverable were turned Deliverable was to describe the definition of what are APIs and functions which will be offered by the PROPHESY-AR layer purposes, its components and specifications of these components. At first, we performed a SotA analysis for the two visualization approaches are going to be used in PROPHESY-AR: data visualization and augmented reality. We combined the finding of the SotA analysis with requirements provided by user stories in Task 2.4 and generally by WP2, service later defined in order to achieve provide functions for look-up and discovery, context- awareness, resource repository and access control solutions, including privacy management. Specifically, this document has described an initial approach for an Open Service Layer proposed from the general specifications. Based on the general specifications an architecture IoT6 point of PROPHESYview, which offers a global discovery and look-AR is proposed within its components and interaction with other PROPHESY layers. After, for each approach, we defined more detailed specifications up platform based on defined use – casesIPv6 technologies such as DNS. In details we provided a methodology for defining This Deliverable has also described the APIs and implementing functions being offered by the dashboard are going to be used for the data visualization in Task 5.2. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance Systemaforementioned Open Service Layer. The implementation of these augmented reality solutions is part of Tasks 5.3 Deliverable also presents the interactions between local and 5.4 respectivelyglobal service discovery mechanisms that would fit in the IoT scenarios that integrates both local and global scopes to ease and homogenize the discovery task. 7 References [1] X. Xxxxxx, X. Xxxx, X. Xxxxxxxx, "The 4+1 View Model Internet of architecture," IEEE Softw.Things: A survey". Computer Networks Vol. 54, volNo. 1215, pp. 422787-502805, November 19952010. [2] X. Xxxxxxxx Xxx, and X. XxxxxXxxxxxx. “Compression Format for IPv6 Datagrams over IEEE 802.15.4- Based Network”. IETF 6LoWPAN Working Group, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-XxxxxxRFC6282, 20122011. [3] DeloitteA, "Predictive Maintenance amd X. Xxxx, M. A. Xxxxxx, and X. Xxxxxxxx, “GLoWBAL IP: an adaptive and transparent IPv6 integration in the smart factory," 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdfInternet of Things”, Mobile Information Systems, “in press”, 2012. [4] Xxxxx Xxxx, Xxxxx Xxxxxxxx, Xxxx Xxxxxxx, Xxxxxx Xxxxxxxxx. “IPv6 over MS/TP Networks”, Xxxxxx Xxxxxxxxxxxxdraft-ietf-6man-6lobac-01,6man working group, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance and the digital supply network," Deloitte, May 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.html2012. [5] X. Xxxxx-XxxxxxXxxxxxx Xxxxxxxxx, X. Xxxxxxxxxxx and M. ten HompelBACNET discovery based on DNS, "Herausforderungen und Anforderungen aus Sicht der BACnet IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4strawman proposal, Berlin, Springer, 2017, pp. 38-422009. [6] X. XXXXXX-XXXXXXXxxxxx, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des Projekts. Integrative Softwarelösungen für ein intelligentes, befarfsorientiertes Instandhaltungsmanagement in komplexen ProduktionsumgebungenEmbedded web services," Unternehmen der ZukunftWireless Communications, no. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdfIEEE, Vol.17, No.6, pp. 3052-3257, 2016. doi: 10.1109/MWC.2010.5675778, December 2010 [7] FRAUNHOFER FEPX.X. Xxxxxxx, "Smart Service Welt Verbundprojekt Discovery systems in ubiquitous computing"Glass@Service"," Fraunhofer FEP, [Online]Pervasive Computing, IEEE, Vol.5, No. Available2, pp. 70- 77, doi: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]10.1109/MPRV.2006.28, 2006. [8] F.-X. XXXXXXXXXXXX X. Xxxxxxxx, and X. XXXXXXXX. Xxxxxx. “Model for a Common Notion of Privacy Leakage on Public Database”. Journal of Wireless Mobile Networks, "Augmented Reality für den MittelstandUbiquitous Computing, and Dependable Applications (JoWUA), Vol. Forschungsprojekt Across," IT&Production2, No. 1, pp. 4050-4162, 20182011. [9] X. XXXXXXXxxxxxxx, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]X. Xxxxxxxx, “Multicast DNS”, xxxx://xxxxx.xxxx.xxx/html/draft-cheshire- dnsext-multicastdns-15, December, 2011. [10] DFKIX. Xxxxxxxx, "Cognitive Workflow Capturing and Rendering with OnX. Xxxxxxxx, “DNS-Body Sensor Networks," DFKIBased Service Discovery”, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]xxxx://xxxxx.xxxx.xxx/html/draft-cheshire-dnsext-dns-sd-10, February, 2011. [11] PWC, MainnovationX. Xxxxxx, "Predictive Maintenance 4.0: Predict the unpredictable," PWCCoRE Link Format", Mainnovationdraft-ietf-core-link-format-06, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdfIETF work in progress, June 2011. [12] Xxxx XxxxxxxXxxx, Xxxxxxx Xxxxxx - KnimeX. and X. Xxxxxx, "Anomaly Detection CoRE Link-Format to DNS-Based Service Discovery Mapping", draft-xxxx-core-discovery-mapping-01 (work in Predictive Maintenance: Time Alignment and Visualization," 2015. [Online]. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdf. [13] Xxxxx Xxxxxxprogress), Presenso, "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx Xxxxx, Xxxxxxx Xxxxxxxxxxxx - IBM redbooks, "IBM Predictive Maintenance and Quality 2.0 Technical Overview," June 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdf. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November July 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovae, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] Augmensys, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.

Conclusions. The efforts aim of our work in this deliverable were turned to the definition of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At first, we performed a SotA analysis for the two visualization approaches are going to be used in PROPHESY-AR: data visualization and augmented reality. We combined the finding context of the SotA analysis with requirements provided by user stories in Task 2.4 Ontogrid project is to develop semantic web services that can cooperate, negotiate, reach agreements and generally by WP2, self-organise in order to achieve effectively and correctly solve overall problems [6]. Having analysed exist- ing proposals for enabling negotiation between web services, we have in particular found the general OGSI WS-Agreement model to be limited and not expressive enough for profitable xxxxx- tic web service negotiation. Thus, in this paper we show our specification of negotiation actions and protocols to enable in- teraction between web services and we give an overview of our model for strategic decision making. Future work includes re- fining and implementing our specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. After, for each approach, we defined more detailed specifications based on defined use – casesthe deployment of semantic web services with negotiation capabilities. In details we provided a methodology for defining and implementing the dashboard are going to be used for the data visualization in Task 5.2. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. X. Xxxxxxxx, "The 4+1 View Model of architecture," IEEE Softw.X. Xxxxxxxxxx, volX. Xxx, and et al. 12Web Ser- vices Agreement Specification (WS-Agreement). World-Wide- Web Consortium (W3C), pp. 42-50, November 19952004. [2] X. Xxxxxxxx Xxxxxxx, X. Xxxxxxxxx, X. Xxxxxx, and X. XxxxxXxxx. Multi-agent systems for efficient quality of service routing in grids. ERCIM News, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-Xxxxxx59:39–42, 20122004. [3] DeloitteX. Xxxx, "Predictive Maintenance amd the smart factory," 2017X. Xxxxxxxx, and X. Xxxxxxx. [Online]Grid resource manage- ment using software agents. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdfERCIM News, 59:39–42, 2004. [4] Xxxxx XxxxxxxEuropean Research Consortium for Informatics and Mathemat- ics. Grids: The next generation. ERCIM News, Xxxxxx Xxxxxxxxx59:39–42, Xxxxxx Xxxxxxxxxxxx, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance and the digital supply network," Deloitte, May 2017. [Online]. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.html2004. [5] X. Xxxxx-XxxxxxXxxxxx and X. Xxxxxxxxx. The Grid2, X. Xxxxxxxxxxx and M. ten HompelBlueprint for a new com- puting infrastructure. Elsevier, "Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4, Berlin, Springer, 2017, pp. 38-422004. [6] X. XXXXXX-XXXXXX, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des ProjektsOntogrid Project. Integrative Softwarelösungen für ein intelligentes, befarfsorientiertes Instandhaltungsmanagement in komplexen Produktionsumgebungen," Unternehmen der Zukunft, noPaving the way for Knowledgeable Grid Ser- vices and Systems. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdf, pp. 30-32, 2016. xxxx://xxxxxxxx.xxx/. [7] FRAUNHOFER FEPX. Xxxxxxxxxx and X. Xxxxxxxx. Protocol engineering for web service conversations. Engineering Applications of Artificial In- telligence, "Smart Service Welt Verbundprojekt "Glass@Service"," Fraunhofer FEPSpecial Issue on Agent-oriented Software Develop- ment, [Online]. Available: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]18(2):237–254, 2005. [8] F.-X. XXXXXXXXXXXX and X. XXXXXXXXxxxxxxxxx. Perfect equilibrium in a bargaining model. Econometrica, "Augmented Reality für den Mittelstand. Forschungsprojekt Across," IT&Production50(1):97–109, pp. 40-41, 20181982. [9] X. XXXXXXX. Xxxxxx. Speech acts: An essay in the philosophy of lan- guage. Cambridge University Press, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]1969. [10] DFKIX. Xxxxx and X. Xxxxx. Service-Oriented Computing. Wiley, "Cognitive Workflow Capturing and Rendering with On-Body Sensor Networks," DFKI, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]2005. [11] PWCX. X. Xxxxx. The contract net protocol: High-level communica- tion and control in a distributed problem solver. IEEE Transac- tions on Computers, MainnovationC-29(12):1104–1113, "Predictive Maintenance 4.0: Predict the unpredictable," PWC, Mainnovation, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdf1981. [12] Xxxx Xxxxxxx, Xxxxxxx Xxxxxx - Knime, "Anomaly Detection in Predictive Maintenance: Time Alignment and Visualization," 2015. [Online]. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdf. [13] Xxxxx Xxxxxx, Presenso, "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx Xxxxx, Xxxxxxx Xxxxxxxxxxxx - IBM redbooks, "IBM Predictive Maintenance and Quality 2.0 Technical Overview," June 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdf. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovaeX. Xxx Xxxx, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] AugmensysX. Xxx Xxxxxx, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-X. Xxxxxxxxx, and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.

Conclusions. The efforts in In this deliverable were turned to the definition of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At firstpaper, we performed have focussed on enabling flexible inter- actions between web services because they are fundamen- tal if web services are to reach their full potential in fu- ture networked environments. In such environments, there are a SotA analysis for number of limitations on the two visualization approaches are going to be used in PROPHESY-AR: data visualization and augmented reality. We combined the finding applicability of the SotA analysis web service agreement (WS-Agreement) proposal. Specifically, this paper addresses the need for developers to code client and provider applications that can bind to and interact with requirements provided by user stories in Task 2.4 and generally by WP2, in order to services of a specific type. To achieve the general specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. After, for each approachthis , we defined more detailed specifications based on defined use – caseshave spec- ified speech-acts as WS-Agreement schemas in XML for richer messages in conversations than just offer and agree. In details Consequently, protocols of realistic expressiveness (such as the Contract Net, auctioning) can be specified in our WS-Agreement extended language. Finally we provided a methodology for defining and an overview of our initial attempts at implementing the dashboard are going to be used for the data visualization in Task 5.2agent web service agreements over IBM’s ETTK toolkit. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. X. Xxxxxxxx, "The 4+1 View Model of architecture," IEEE Softw.X. Xxxxxxxxxx, volX. Xxx, and et al. 12Web Services Agreement Specification (WS-Agreement). World-Wide-Web Consortium (W3C), pp. 42-50, November 19952004. [2] X. Xxxxxxxx and X. XxxxxF. for Intelligent Physical Agents. FIPA Communicative Act Library Specification. xxxx://xxx.xxxx.xxx, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-Xxxxxx, 20122002. [3] Deloitte, "Predictive Maintenance amd the smart factory," 2017Globus Alliance and IBM Software Development and Research Labs. [Online]WS-Resource Framework. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdf. xxxx://xxx.xxxxxx.xxx/wsrf/. [4] Xxxxx Xxxxxxx, Xxxxxx Xxxxxxxxx, Xxxxxx Xxxxxxxxxxxx, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance IBM Software Development and the digital supply network," Deloitte, May 2017Research Labs. [Online]Emerging Technologies Toolkit: ETTK. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.htmlxxxx://xxx.xxxxxxxxxx.xxx/tech/ettk. [5] X. Xxxxx-Xxxxxx, X. Xxxxxxxxxxx Xxx, and M. ten HompelX. Xxxxxxx. Cremona:an architec- ture and library for creation and monitoring of ws-agreements. In Proc. of 2nd International Conference on Service Oriented Computing 04, "Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4ACM, Berlinpages 65 – 74, Springer, 2017, pp. 38-422004. [6] X. XXXXXX-XXXXXX, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des ProjektsOntogrid Project. Integrative Softwarelösungen für ein intelligentes, befarfsorientiertes Instandhaltungsmanagement in komplexen Produktionsumgebungen," Unternehmen der Zukunft, noPaving the way for Knowledgeable Grid Services and Systems. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdf, pp. 30-32, 2016. xxxx://xxxxxxxx.xxx/. [7] FRAUNHOFER FEPX. Xxxxxxxxxx and X. Xxxxxxxx. Protocol engineering for web service conversations. Engineering Applications of Artificial Intelligence, "Smart Service Welt Verbundprojekt "Glass@Service"," Fraunhofer FEPSpecial Issue on Agent-oriented Software Devel- opment, [Online]. Available: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]18(2):237–254, 2005. [8] F.-X. XXXXXXXXXXXX and X. XXXXXXXX. Xxxxxx. Speech acts: An essay in the philosophy of lan- guage. Cambridge University Press, "Augmented Reality für den Mittelstand. Forschungsprojekt Across," IT&Production, pp. 40-41, 20181969. [9] X. XXXXXXXxxxxxxx, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]. [10] DFKIX. Xxx Xxxx, "Cognitive Workflow Capturing and Rendering with On-Body Sensor Networks," DFKI, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]. [11] PWC, Mainnovation, "Predictive Maintenance 4.0: Predict the unpredictable," PWC, Mainnovation, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdf. [12] Xxxx Xxxxxxx, Xxxxxxx Xxxxxx - Knime, "Anomaly Detection in Predictive Maintenance: Time Alignment and Visualization," 2015. [Online]. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdf. [13] Xxxxx X. Xxx Xxxxxx, PresensoX. Fintelman, "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx Xxxxx, Xxxxxxx Xxxxxxxxxxxx - IBM redbooks, "IBM Predictive Maintenance and Quality 2.0 Technical Overview," June 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdf. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovae, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] Augmensys, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.

Conclusions. The efforts in In this deliverable were turned to the definition of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At firstpaper, we performed have focussed on enabling flexible inter- actions between web services because they are fundamen- tal if web services are to reach their full potential in fu- ture networked environments. In such environments, there are a SotA analysis for number of limitations on the two visualization approaches are going to be used in PROPHESY-AR: data visualization and augmented reality. We combined the finding applicability of the SotA analysis web service agreement (WS-Agreement) proposal. Specifically, this paper addresses the need for developers to code client and provider applications that can bind to and interact with requirements provided by user stories in Task 2.4 and generally by WP2, in order to services of a specific type. To achieve the general specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. After, for each approachthis , we defined more detailed specifications based on defined use – caseshave spec- ified speech-acts as WS-Agreement schemas in XML for richer messages in conversations than just offer and agree. In details Consequently, protocols of realistic expressiveness (such as the Contract Net, auctioning) can be specified in our WS-Agreement extended language. Finally we provided a methodology for defining and an overview of our initial attempts at implementing the dashboard are going to be used for the data visualization in Task 5.2agent web service agreements over IBM’s ETTK toolkit. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. X. Xxxxxxxx, "The 4+1 View Model of architecture," IEEE Softw.X. Xxxxxxxxxx, volX. Xxx, and et al. 12Web Services Agreement Specification (WS-Agreement). World-Wide-Web Consortium (W3C), pp. 42-50, November 19952004. [2] X. Xxxxxxxx and X. XxxxxF. for Intelligent Physical Agents. FIPA Communicative Act Library Specification. xxxx://xxx.xxxx.xxx, "Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives," in Xxxxxxx-Xxxxxx, 20122002. [3] Deloitte, "Predictive Maintenance amd the smart factory," 2017Globus Alliance and IBM Software Development and Research Labs. [Online]WS-Resource Framework. Available: xxxxx://xxx0.xxxxxxxx.xxx/content/dam/Deloitte/us/Documents/process-and- operations/us-cons-predictive-maintenance.pdf. xxxx://xxx.xxxxxx.xxx/wsrf/. [4] Xxxxx Xxxxxxx, Xxxxxx Xxxxxxxxx, Xxxxxx Xxxxxxxxxxxx, Xx Xxxxx - Xxxxxxxx, "Making maintenance smarter Predictive maintenance IBM Software Development and the digital supply network," Deloitte, May 2017Research Labs. [Online]Emerging Technologies Toolkit: ETTK. Available: xxxxx://xxx0.xxxxxxxx.xxx/insights/us/en/focus/industry-4-0/using-predictive- technologies-for-asset-maintenance.htmlxxxx://xxx.xxxxxxxxxx.xxx/tech/ettk. [5] X. Xxxxx-Xxxxxx, X. Xxxxxxxxxxx Xxx, and M. ten HompelX. Xxxxxxx. Cremona:an architec- ture and library for creation and monitoring of ws-agreements. In Proc. of 2nd International Conference on Service Oriented Computing 04, "Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik," in Handbuch Industrie 4.0 Bd.4ACM, Berlinpages 65 – 74, Springer, 2017, pp. 38-422004. [6] X. XXXXXX-XXXXXX, "Smart Maintenance: Industrie 4.0 in der Instandhaltung - Zum aktuellen Stand des ProjektsOntogrid Project. Integrative Softwarelösungen für ein intelligentes, befarfsorientiertes Instandhaltungsmanagement in komplexen Produktionsumgebungen," Unternehmen der Zukunft, noPaving the way for Knowledgeable Grid Services and Systems. xxxxx://xxxx.xxx.xx/download/udz/udz2_2016.pdf, pp. 30-32, 2016. xxxx://xxxxxxxx.xxx/. [7] FRAUNHOFER FEPX. Xxxxxxxxxx and X. Xxxxxxxx. Protocol engineering for web service conversations. Engineering Applications of Artificial Intelligence, "Smart Service Welt Verbundprojekt "Glass@Service"," Fraunhofer FEPSpecial Issue on Agent-oriented Software Devel- opment, [Online]. Available: xxxxx://xxx.xxx.xxxxxxxxxx.xx/de/Geschaeftsfelder/Mikrodisplays_und_Sensorik/glas s-at-service.html. [Accessed 24 07 2018]18(2):237–254, 2005. [8] F.-X. XXXXXXXXXXXX and X. XXXXXXXX. Xxxxxx. Speech acts: An essay in the philosophy of lan- guage. Cambridge University Press, "Augmented Reality für den Mittelstand. Forschungsprojekt Across," IT&Production, pp. 40-41, 20181969. [9] X. XXXXXXXxxxxxxx, "SePiA Pro," 2015. [Online]. Available: xxxx://xxxxxxx-xxxxxxxx.xx. [Accessed 24 7 2018]. [10] DFKIX. Xxx Xxxx, "Cognitive Workflow Capturing and Rendering with On-Body Sensor Networks," DFKI, 2012. [Online]. Available: xxxx://xxx.xxx-xxxxxxx.xxx/. [Accessed 24 7 2018]. [11] PWC, Mainnovation, "Predictive Maintenance 4.0: Predict the unpredictable," PWC, Mainnovation, 2017. [Online]. Available: xxxxx://xxx.xxx.xx/nl/assets/documents/pwc-predictive-maintenance-4-0.pdf. [12] Xxxx Xxxxxxx, Xxxxxxx Xxxxxx - Knime, "Anomaly Detection in Predictive Maintenance: Time Alignment and Visualization," 2015. [Online]. Available: xxxxx://xxxxx.xxxxx.xxx/sites/default/files/inline- images/knime_anomaly_detection_visualization.pdf. [13] Xxxxx X. Xxx Xxxxxx, PresensoX. Xxxxxxxxx, "Functional and Non-Functional Requirements for Machine Learning Predictive Maintenance Solution," 19 October 2017. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/functional-requirements-machine-learning- predictive-maintenance. [14] Xxxxxx Xxxxxxxx, Xxxxxxxxxxxxxxxx Xxxxxxxxxxx, Xxxxx Xxxxxx, Xxxxx Xxxxx, Xxxxxxx Xxxxxxxxxxxx - IBM redbooks, "IBM Predictive Maintenance and Quality 2.0 Technical Overview," June 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx.xxx/redpapers/pdfs/redp5035.pdf. [15] Xxxxx Xxxxxxx - Gooddata, "5 Data Visualization Best Practices," Gooddata, 25 August 2015. [Online]. Available: xxxxx://xxx.xxxxxxxx.xxx/blog/5-data-visualization-best- practices. [16] Xxxxx Xxxx , "10 Golden Rules of Data Visualization," 15 November 2016. [Online]. Available: xxxx://xxx.xxxx.xxx/BigDataQuarterly/Articles/10-Golden-Rules-of-Data- Visualization-114796.aspx. [17] X. Xxxxxxx, "Basic Data Analytics, Visualizations,," 27 April 2017. [Online]. Available: Basic Data Analytics, Visualizations, . [19] X. Xxxxxxxx, "Analysts: Data visualization tools key to 'big data' analytics success," 30 November 2011. [Online]. Available: xxxxx://xxxxxxxxxxxxxxxxxxxxxxx.xxxxxxxxxx.xxx/news/2240111798/Analysts-Data- visualization-tools-key-to-big-data-analytics-success. [20] innovae, "innovae," [Online]. Available: xxxx://xxx.xxxxxxx.xx/?lang=en. [21] Augmensys, "Maintenance 4.0 | Predictive Maintenance with Augmented Reality and OCR," [Online]. Available: xxxxx://xxx.xxxxxxxxx.xxx/en/ubik-all/item/232- maintenance-4-0-predictive-maintenance-with-augmented-reality-and-ocr. [22] Valmet, "Augmented Reality Re-defines Predictive Maintenance," Valmet, [Online]. Available: xxxxx://xxx.xxxxxx.xxx/media/articles/all-articles/augmented-reality-re- defines-predictive-maintenance/. [23] Xxxxxx XxXxxxxx, SAP, "Predictive Maintenance and Service Meets Augmented Reality and Wearable Technology," SAP, 19 December 2016. [Online]. Available: xxxxx://xxxxx.xxx.xxx/2016/12/19/predictive-maintenance-and-service-meets- augmented-reality-and-wearable-technology/. [24] Datamatics, "Data Visualization & Predictive Analytics," [Online]. Available: xxxxx://xxx.xxxxxxxxxx.xxx/sites/default/files/brochure-pdf/DataVisualization- PredictiveAnalytics.pdf.

Conclusions. The efforts aim of our work in this deliverable were turned to the definition of what are the PROPHESY-AR layer purposes, its components and specifications of these components. At first, we performed a SotA analysis for the two visualization approaches are going to be used in PROPHESY-AR: data visualization and augmented reality. We combined the finding context of the SotA analysis with requirements provided by user stories in Task 2.4 Ontogrid project is to develop semantic web services that can cooperate, negotiate, reach agreements and generally by WP2, self-organise in order to achieve effectively and correctly solve overall problems [6]. Having analysed exist- ing proposals for enabling negotiation between web services, we have in particular found the general OGSI WS-Agreement model to be limited and not expressive enough for profitable xxxxx- tic web service negotiation. Thus, in this paper we show our specification of negotiation actions and protocols to enable in- teraction between web services and we give an overview of our model for strategic decision making. Future work includes re- fining and implementing our specifications. Based on the general specifications an architecture of PROPHESY-AR is proposed within its components and interaction with other PROPHESY layers. After, for each approach, we defined more detailed specifications based on defined use – casesthe deployment of semantic web services with negotiation capabilities. In details we provided a methodology for defining and implementing the dashboard are going to be used for the data visualization in Task 5.2. Finally, we presented the detailed specifications for augmented reality part which is composed with to solutions PHILIPS AR-Viewer and Remote Maintenance System. The implementation of these augmented reality solutions is part of Tasks 5.3 and 5.4 respectively. 7 References [1] X. 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