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Open Services for Lifecycle Collaboration (OSLC)

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Open Services for Lifecycle Collaboration (OSLC)

  1. 1. Open Services for Lifecycle Collaboration (OSLC) Introduction into open standards for the integration of ALM, PLM, and more CONTACT Open World 2019 Axel Reichwein, Koneksys June 27, 2019 1
  2. 2. Initially: Focus on using data standards PhD and postdoc focused on tradeoff studies Reconfiguring architecture model to then automatically sync detailed discipline-specific models Applying rule-based design in engineering 2
  3. 3. Now: Focus on using API standards API standards crucial for scalable data integration strategy API standards have longer life expectancy than data standards API standards enable new enterprise applications 3
  4. 4. Koneksys Consulting Services Connecting data using standards ● Custom software development for organizations and vendors ● Research projects 4
  5. 5. Status Quo in Information Management According to David Meza, Head of Knowledge Management at NASA ● Most engineers have to look at 13 different sources to find the information they are looking for ● 46% of workers can’t find the information about half the time ● 30% of total R&D funds are spent to redo what we’ve already done once before ● 54% of our decisions are made with inconsistent, or incomplete, or inadequate information Quote from https://www.youtube.com/watch?v=QEBVoultYJg 5
  6. 6. Crosscutting Concerns Across Disciplines 6 Requirements Engineering Design Manufacturing Operation Traceability Configuration management Change Management Reuse
  7. 7. 2 Trends increasing need for connected data IoT New feedback loops needed to make sense of recorded operational data Autonomy Explosion of number of test scenarios Need to link experienced auton. vehicle behavior (e.g. saved in data lakes) with test scenarios (e.g. saved in systems engineering applications) to assess coverage of test scenarios and overall vehicle safety Design Procurement Manufacturing Operation 7
  8. 8. From model silos to connected data 8
  9. 9. Example: SUV Rollover Engineering Domains ● Requirement ● Control System Design ● 3D Model ● Test Case ● Simulation Model ● Change Request 9
  10. 10. Example Cross-disciplinary Relationships 10 Requirement 3D model Simulation Model Controller Model Test Case
  11. 11. Engineering Change Request 11 Requirement 3D modelSimulation Model Change RequestProblem Test CaseController Model
  12. 12. Discipline-specific PLM & ALM Solutions 12 Requirement 3D modelSimulation Model Change Request Test CaseController Model ALM PLM
  13. 13. Discipline-specific Change Requests (not ideal!) 13 Requirement 3D modelSimulation ModelTest CaseController Model PLM Change RequestALM Change Request ALM PLM
  14. 14. Example ALM/PLM Integrations (based on OSLC) Linking PLM Parts with ALM requirements Linking PLM Engineering Change Requests (ECR) with ALM work items Integration from Sodius between PTC Windchill and IBM CLM: Integration from Siemens between Siemens Teamcenter and Polarion https://docs.plm.automation.siemens.com/data_services/reso urces/polarion/17.3/help/common/en_US/graphics/fileLibrary/ 17_3_pdfs/Teamcenter_Polarion_Integration_Installation.pdf OSLC API for Contact Elements ● Reference implementation in Python released as open-source soon ● OSLC API for Contact Elements can be used to connect PLM/ALM artifacts and more 14
  15. 15. What does it mean to connect data? Example: Requirement identifier <- link type -> Simulation parameter identifier Connection is between IDENTIFIERS of data Analogy: phone call between 2 persons identified by their phone number 15 Artifact ID1 Artifact ID2 Link Type ID1
  16. 16. What does it mean to connect data? Example: Requirement identifier <- link type -> Simulation parameter identifier Connection is between IDENTIFIERS of data Analogy: phone call between 2 persons identified by their phone number 16 Artifact ID1 Artifact ID2 Link Type ID1 Artifact ID2Link Type ID2 Link Type ID3
  17. 17. Application Programming Interface (API) An API can specify the interface to a database, software, dataset De facto API standard now: REST APIs 17 Facebook Google Twitter API1 API2 API3
  18. 18. REST API Example 1 18 Facebook GET "https://graph.facebook.com/{your-user-id} ?fields=id,name " { "name": "Your Name", "id": "your-user-id" }
  19. 19. REST API Example 2 19 Dropbox POST https://api.dropboxapi.com/2/users/get_account --data "{"account_id": "dbid:AAH4f99..."}" { "account_id": "dbid:AAH4f99..." }
  20. 20. Data Integration Requires Data Transformations 20 Data Repository 1 Data Repository 2 Data Repository 3 Data Integration Data Transformation Data Sources ID = 1223465 ID = http://xyz/123 ID = e0d123e5f31 Different local ID formats Data unification using data transformations
  21. 21. Other Data Aspects Requiring Data Transformations 21 Data Repository 1 Data Repository 2 Data Repository 3 Data Integration Data Transformation Data Sources Universal Data Aspects Identifier Version Change events Data model Projects Data unification using data transformations
  22. 22. Reality 22 Data Repository 1 Data Repository 2 Data Repository 3 Data Integration Data Transformation Data Sources Limited number of integrations TOO MUCH EFFORT -> Limited number of data transformations Limited data integration
  23. 23. Connecting data is currently impossible! Full connectivity CAD Software Simulation API1 API2 API3 Different APIs everywhere! 23
  24. 24. Different API = vendor lock-in Your Data Your Software Application Vendor Proprietary APIs and Data Formats $ $ 24
  25. 25. Once Upon a Time - Before the Web Different protocols to access documents on the internet (Gopher, WAIS, etc...) No connected documents (hierarchical document structure, no hyperlinks) Not many persons used the internet Hypertext existed since 1965, 25 years before the invention of the Web Lack of standards for Hypertext hindered adoption of Hypertext - no compatibility between different Hypertext systems 25
  26. 26. Lessons learned from the Web Seeds for innovation: Open standards + open-source Web not owned by a software vendor Any document can connect to any other document Improved knowledge sharing and collaboration OSLC driven by similar values than World Wide Web 26
  27. 27. Reusable Web Standards 27 Data Repository HTTP ? URL http://../req2
  28. 28. Machine-readable format for links 28 Needed: format to describe graphs Different standard data models to describe graphs Currently most used for data on the Web: Resource Description Framework (RDF) Artifact ID1 Artifact ID2 Link Type ID1 Artifact ID2Link Type ID2 Link Type ID3
  29. 29. RDF Example: Schema.org 29 Interoperability between search engines and Web content creators through schema.org
  30. 30. Standard APIs for Connecting Data 30 Requirements Test cases Simulation API1 API2 API3 Global_Id1 Global_Id2 Global_Id3 Global_Id4 Global_Id5 Global_Id6 Standard API Standard API Standard APIHTTP URLRDF
  31. 31. Open Services for Lifecycle Collaboration (OSLC) 31 From http://docs.oasis-open.org/oslc-core/oslc-core/v3.0/oslc-core-v3.0-part1-overview.html Web Standards OSLC Standards
  32. 32. OSLC Adoption By vendors mostly in ALM: IBM Jazz/CLM, Mentor Graphics, Sodius Over 50 OSLC APIs developed for different applications By universities and consultants for MBSE, simulation: https://github.com/ld4mbse + https://github.com/oslc General Motors in their MBSE efforts and vision https://koneksys.com/blog/present ation-of-oslc-at-purdue-plm-meeti ng-2018/ 32
  33. 33. Applications decoupled from data 33 Requirements Test cases Simulation API1 API2 API3 Visualization Search/Query Reporting Modular architecture Combining Applications and data through plug-n-play Standard API Standard API Standard API Machine Learning Link Management Modeling
  34. 34. Private/public Data Web Distributed Data Silos Mashup Application Example Google-like Search 34 Data Repository 1 Data Repository 2 Data Repository 3 RDF Link Link RDF
  35. 35. Discipline-specific vs. Universal Data Management Currently, we have discipline-specific data management: Simulation Data Management (SDM), Product Lifecycle Management (PLM), Application Lifecycle Management (ALM) etc., and NO Data connectivity Universal Data Management is needed ● Viewing data as a universal asset ● Viewing data as equal ● Viewing data with its context ● Viewing data as a whole ● Using open standards for creating standard APIs ● Creating applications on top of standard APIs 35
  36. 36. What now? Request better APIs from vendors Request OSLC APIs from vendors Adopt OSLC in your new integration projects Perform POC projects with OSLC Help build the OSLC community 36
  37. 37. Thanks and get in touch! axel.reichwein@koneksys.com

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