Engineering Research Information Management The ERIM Project

Alex Ball, Steve Culley, Mansur Darlington, Michael Day, Tom Howard, Liz Lyon & Chris McMahon

Managing Datain the

Innovative Design & Manufacturing Research Centreat the University of Bath

JISC MRD Workshop 29th March 20112

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.

JISC MRD Workshop 29th March 20113

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

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CHALLENGES for Engineering Research Information

Management

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IdMRC Research Themes

research programme divided into four complementary themes:

IdMRCTHEME Constraint-Based Design & OptimisationIdMRCTHEME Constraint-Based Design & Optimisation

IdMRCTHEME Advanced Machining Processes & SystemsIdMRCTHEME Advanced Machining Processes & Systems

IdMRCTHEME Metrology & Assembly Systems & Technologies IdMRCTHEME Metrology & Assembly Systems & Technologies

IdMRCTHEME Design Information & KnowledgeIdMRCTHEME Design Information & Knowledge

10 year research lifespan

16 Academics

65 Researchers

60 Research Students

700 Journal & Conference Papers

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Engineering Research Project Diversity

Aerospace CostForecasting

Large-Scale Metrology Shared

Resources

Form-fill-feedPackagingModelling

CNC Machine Measurement

Snow MobileDesign

Observation

CryogenicMachining

Information Management Tool

Knowledge-Enhanced Notes

ServiceDesign Research

Design Activity& Knowledge

Capture

Understandingthe LearningOrganization

Airframe StressData Reuse

ERIM

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Advanced Machining

Processes & Systems

CRYogenic MAchiNing (CRYMAN)

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

CAD/CAM for a Customised

Sole

FreezeBillet

Material

CryogenicCooled Fixture

PersonalisedSoles

MachineSoles

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Advanced Machining

Processes & Systems

CRYogenic MAchiNing (CRYMAN)

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

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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.

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Solutions for Engineering Research Information

Management

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Key Research Findings

1. Poor framework for: – data management during the research.– during-project data management for post-project re-use.

2. 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.

3. Knowing the context is vital for understanding data.

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Multi-level ERDMP Best-Practice Guidance

Principles for Engineering Research Data Management.

(erim6rep101028mjd)

Engineering Research Data Management Plan Requirement Specification

(erim6rep100901ab)

The Draft IdMRC Projects Data Management Plan

(erim6rep101015mjd)

RAID Associative Tool Requirements Specification

(erim6rep101111mjd11)

1

2

Being a specification for 2

Being an implementation of 1

1. Improving the DMP

Framework

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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.

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Multi-level ERDMP Best-Practice Guidance

Principles for Engineering Research Data Management.

(erim6rep101028mjd)

Engineering Research Data Management Plan Requirement Specification

(erim6rep100901ab)

The Draft IdMRC Projects Data Management Plan

(erim6rep101015mjd)

RAID Associative Tool Requirements Specification

(erim6rep101111mjd11)

1

2

Being a specification for 2

Being an implementation of 1

2. & 3.Recording

the Context

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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.

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Capturing the Context (RAID)

CRYMAN PROJECT

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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

The CRYMAN Project

Data Management for the IdMRC

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The 12 Principles of ERDM

1. ERDM should be informed by the more general Principles of Engineering Information Management.

2. ERDM should be consistent with the approach outlined in the DCC Charter and Statement of Principles.

3. RDM should reflect the need for and provide guidance to support research data reproducibility.

4. The notions of re-usability and re-purposing should be supported by the use of generic or standard data generation and manipulation tools.

5. All DMPs should contains aspects which explicitly set out to help 'supporting data re-use' and re-purposing.

6. The data objects associated with a research activity should be considered to be and managed as a mutually explanatory set.

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The Twelve Principles of ERDM

7. The data objects associated with a research activity should be associated explicitly by the use of contextual information.

8. The specification of the contextualizing methods should be made available, to aid their interpretation.

9. Any agreement on the confidentiality or otherwise of research data should be as permissive as can be negotiated.

10. Due consideration should be given in research project planning to the role of data management and its cost.

11. Requirements specified in data management plans for the activities of 'supporting re-use' and 're-purposing' should hinder use activities as little as possible.

12. Data management tools should be simple, engaging and easy to access.

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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

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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 known research 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.

Activities

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Engineering Research Data Record Types

ASSOCIATIVE DATA RECORD

EXPERIMENTAL APPARATUS

DATA RECORD

RESEARCH OBJECT DATA RECORD

Data Asset

Digital Object(aka digital data

asset)

Physical Object(aka physical data

asset)

Research Object

Description of Object

Pre-existingResearch Generated

First Generation Nth Generation

Pre-existingResearch Generated Pre-existing

Research Generated

Contextualizing Object

Intentional Contextualizing

Data

RESEARCH DATA RECORD

CONTEXT DATA RECORD

Unintentional Contextualizing

Data

Experimental Apparatus Data

Intentional Contextualizing

Data

2.

5.

1.

4. 3.

6.