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Engineering Research Information Management The ERIM Project

Managing Data in the Innovative Design & Manufacturing Research Centre at the University of Bath. Engineering Research Information Management The ERIM Project. Alex Ball, Steve Culley, Mansur Darlington , Michael Day, Tom Howard, Liz Lyon & Chris McMahon.

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Engineering Research Information Management The ERIM Project

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  1. Managing Datain theInnovative Design & Manufacturing Research Centreat the University of Bath Engineering Research Information Management The ERIM Project Alex Ball, Steve Culley, Mansur Darlington, Michael Day, Tom Howard, Liz Lyon & Chris McMahon

  2. Engineering Research Information Management • To better understand the research data that are collected, generated and used in engineering research activities. • To better understand the context in which the data are collected, generated and used. • To inform the way that the data can be managed so that they are more easily used, re-used and ‘re-purposed’. • To increase their value to the research community.

  3. ERIM Research Tasks • Characterize Engineering Research Data • Characterize how it is used and managed now. • Propose better data management methods and approaches to deal with it for: Data use, re-use and re-purposing

  4. CHALLENGES for Engineering Research Information Management

  5. IdMRC Research Themes research programme divided into four complementary themes: 10 year research lifespan 16 Academics 65 Researchers 60 Research Students 700 Journal & Conference Papers

  6. Engineering Research Project Diversity CNC Machine Measurement Information Management Tool Large-Scale Metrology Shared Resources ERIM Airframe Stress Data Reuse Form-fill-feed Packaging Modelling Aerospace Cost Forecasting Design Activity & Knowledge Capture Snow Mobile Design Observation Service Design Research Understanding the Learning Organization Knowledge- Enhanced Notes Cryogenic Machining

  7. CRYogenic MAchiNing (CRYMAN) FreezeBillet Material CryogenicCooled Fixture MachineSoles Advanced Machining Processes & Systems PersonalisedSoles CAD/CAM for a Customised Sole Machining through cryogenic cooling of soft materials • Understand how to freeze soft plastics (polymers) so they are hard. • Understand the machining requirements of freeze-hardened polymers. ILLUSTRATIVE USE

  8. CRYogenic MAchiNing (CRYMAN) Advanced Machining Processes & Systems Research Data Store: • 3 Folder Levels • 27 folders, 498 files in L1 • 79 folders, 2632 files in L2 • 19 folder, 144 files in L3 • 126 Folders • 3288 Files • 49 File types; of which 22 unknown • Physical entities Highly Diverse: content representations file formats complex relations

  9. Current Data Management Policy • Compliance: Make sure its managed according to UK Law and research funder requirements. • Security: All research data relating to live projects must be managed securely. • Responsible management: Research data management and archiving is the responsibility of the principal investigator (PI) for each project and must be considered from the outset of new projects. • Archiving: All digital primary research data should be deposited in the University’s research data archive as soon as practical once projects are completed • Retention: Suitable retention periods must be established and implemented for all archived data.

  10. Solutions for Engineering Research Information Management

  11. Key Research Findings • Poor framework for: • data management during the research. • during-project data management for post-project re-use. • Poor knowledge of context in which data were generated: • Engineering research data are very diverse. • Large number of diverse research data records. • Relations between data records complex. • Knowing the context is vital for understanding data.

  12. Multi-level ERDMP Best-Practice Guidance Principles for Engineering Research Data Management. (erim6rep101028mjd) 1. Improving the DMP Framework Being a specification for2 Engineering Research Data Management Plan Requirement Specification (erim6rep100901ab) 1 Being an implementation of1 The Draft IdMRC Projects Data Management Plan (erim6rep101015mjd) 2 RAID Associative Tool Requirements Specification (erim6rep101111mjd11)

  13. Engineering Research Data Management Plan Requirement Specification 1. PROJECT RECORD MANIFEST Describe the method by which Data Records and the relationships between them will be/were recorded in a project record manifest. Present this manifest (once it exists), or otherwise indicate how it may be accessed. 2. DATA GENERATION AND MANIPULATION Give a detailed account of how the data will be/were generated and manipulated, including the methods, technology, conventions, coding schemes, etc. that will be/were used. 3. DATA ORGANIZATION Describe how the data will be/have been organized. 4. DATA STRUCTURES AND FORMATS Specify the information, tools or resources that would be needed to manipulate or render the Data Records, along with any special instructions. Provide an explanation of why a particular format has been selected for use. 5. DATA SEMANTICS Provide any additional information that would be needed to understand the Data Records, once rendered. Provide justification for the conventions used.

  14. Multi-level ERDMP Best-Practice Guidance Principles for Engineering Research Data Management. (erim6rep101028mjd) Being a specification for2 Engineering Research Data Management Plan Requirement Specification (erim6rep100901ab) 1 Being an implementation of1 The Draft IdMRC Projects Data Management Plan (erim6rep101015mjd) 2 2. & 3. Recording the Context RAID Associative Tool Requirements Specification (erim6rep101111mjd11)

  15. Desirable Features in an Associative Tool • Automatic association of data records. • Allow manual associations and annotations of data assets. • Produce a graphical representation of the associations of selected data records. • Log date and time stamp of association. • Enable the re-user to find the source (copy side) of associated data. • Enable user to see the target (paste side) of associated data. • Log modifications and manipulations to data (track changes). • Automatically associate the data within the records.

  16. Capturing the Context (RAID) CRYMAN PROJECT

  17. And Finally: ERIM Implications for the future • Change in Culture. • Culture change reflected in funding and resources made available: • Provision of institutional and departmental infrastructure. • Appropriate methods and good-practice guidelines. • Appropriate and non-invasive tools • Personnel and training

  18. Data Management for the IdMRC The CRYMAN Project

  19. The 12 Principles of ERDM • ERDM should be informed by the more generalPrinciples of Engineering Information Management. • ERDM should be consistent with the approach outlined in the DCC Charter and Statement of Principles. • RDM should reflect the need for and provide guidance to support research data reproducibility. • The notions of re-usability and re-purposing should be supported by the use of generic or standard data generation and manipulation tools. • All DMPs should contains aspects which explicitly set out to help 'supporting data re-use' and re-purposing. • The data objects associated with a research activity should be considered to be and managed as a mutually explanatory set.

  20. The Twelve Principles of ERDM • The data objects associated with a research activity should be associated explicitly by the use of contextual information. • The specification of the contextualizing methods should be made available, to aid their interpretation. • Any agreement on the confidentiality or otherwise of research data should be as permissive as can be negotiated. • Due consideration should be given in research project planning to the role of data management and its cost. • Requirements specified in data management plans for the activities of 'supporting re-use' and 're-purposing' should hinder use activities as little as possible. • Data management tools should be simple, engaging and easy to access.

  21. Engineering Research Data Management Plan Requirement Specification INFRASTRUCTURE AND IMPLEMENTATION ISSUES Relating the DMP to other documentation Relating other documentation to the DMP Understanding the DMP Rôles and responsibilities Review of the DMP Revision of the DMP Budget Storage, back-up and security Receiving repository DMP CONTENTS Data re-use Relating new data to existing data Future use of the data Project record manifest Data generation and manipulation Data organization Data structures and formats Data semantics Data quality

  22. Activities Data Management Activities: • Data Purposing: Making research data available and fit for the current research activity. • Data Re-purposing:Making existing research data available and fit for a future knownresearch activity • Supporting Data Re-use: Managing existing research data such that it will be available for a future unknown research activity Data Use Activities • Data Use:Using research data for the current research purpose/activity to infer new knowledge about the research subject. • Data Re-use:Using research data for a research purpose other than that for which it was intended.

  23. Engineering Research Data Record Types

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