ERIM, REDm-MED and Orbital (II)

1 Orbital DMP Meeting 20.01.12

Managing Engineering Research Data

at the University of Lincoln

Part 2 of 2

Mansur Darlington20 January 2012


THE NATURE OF ENGINEERING RESEARCH DATA


ERIM

Engineering Research Information Management

JISC MRD Programme Phase 1http://www.ukoln.ac.uk/projects/erim/


ERIM Project Overview

• Primarily associated with the engineering

research domain.

• 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

or re-used.

• To increase their value to the community.


The Aims

• Achieving an understanding of the diversity

and character of research data.

• Devising a means by which research data

can be classified in respect of research data

management.

• Developing models of the research data life-

cycle which characterize the information flow

in the research process and identify critical

points in the management process.

• Providing exemplars of best-practice

research data management strategies.


The Objectives

• Identify opportunities for and the benefits of

research data re-use and re-purposing.

• Identify the contextual, technical, legal and

social barriers to the re-use and repurposing

of research data.

• Establish whether and what data might be

used in a raw form, what data would require

reprocessing and how this might be achieved.

• Understand what contextual information is

required for research data to be understood

for the purpose of re-use.


Theoretical Elements to the Research

1. Understanding & Defining the ‘Space’

2. Terminology https://wiki.bath.ac.uk/display/ERIMterminology/ERIM+Terminology+V4

3. Identifying the Objects in the space

4. Understanding the Relationships between

Objects

5. Modelling the Relationships

6. Understanding the Outcomes


CURRENT-ACTIVITY MANAGEMENT SPACE

FUTURE-ACTIVITY MANAGEMENT SPACE

for Current Research

for

Future

ResearchMaking data available and

fit for a future known purpose

RE-PURPOSING:

Managing data such that it will be available

for a future unknown purpose

supporting data RE-USE:

Making data available and fit for the current known

purpose

PU

RP

OS

ING

:

Raw

Research

Data

Management for A by A

Management for X by Y,

where Y can be X Management for X by Y

Understanding & Defining the ‘Space’


ERIM Project Terminology for

Research Data Mangement

https://wiki.bath.ac.uk/display/ERIMterminology/ERIM+Terminology+V4

(source definitions for terms found in slides 10-14)


Preparation 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

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.

2. The Terminology I


2. The Terminology II

What do we Mean by DATA?

• Data. Reinterpretable representations of information in a formalized manner suitable for communication, interpretation or processing.

• Information. Any type of knowledge that can be exchanged. In an exchange, it is represented by data.

***********************

• Data Object. Either a physical object or a digital object containing data.

• Data Record. A data object created, received and maintained as evidence of an activity.

• Data Case. The set of data records associated with some discrete research activity (project, task, experiment, etc.).


3. Identifying the Objects


4. Understanding the Relationships

��Migration

��Refinement

��Derivation

��Generation

��Collation

��Collection

��Augmentation

��Annotation

��Aggregation

��Association

Re-

purposing

Supporting Re-usePurposingData Development

Data Preparation in


6. Understanding the Outcomes

Management and Development Side-effects

• Information Loss

• Information Gain

• Function Loss

• State Loss


5. Modelling the Objects’ Relationships

RDR1 Refine RDR1' Refine RDR1''

Derive RDR4

RDR2 Derive RDR3

CDR1 Aggregate RDR6

RDR5

RESEARCH TIME LINE

Gather

Gather

Data level

As

so

cia

te


Capturing the Context through RAID-modelling


Research Data Scoping Survey

• 12 Research Cases

• 46 Data Assets

• 12 questions for each

• Researchers from:

Bath, Lancaster, Leeds,

Salford, Strathclyde,

Heriot-Watt


Scoping Survey Targets

1. Airframe Stress Data Reuse

2. Snow Mobile Design Activity Observation

3. Aerospace Cost Forecasting

4. Large-Scale Metrology Shared Resources

5. Form-fill-feed Packaging Modelling

6. CNC Machine Measurement

7. Cryogenic Machining

8. Information Management Tool

9. Knowledge Enhanced Notes

10. Service Design Research

11. Design Activity & Knowledge Capture Research

12. Understanding the Learning Organization


Selecting 5 Case Studies using Binary Classification

Research Generated Data vs Pre-existing Data

Homogeneous Media vs Heterogeneous Media

Descriptive vs Prescriptive

Real vs Simulated

4. Interview analysis 5. Metrology

3. Programming

2. Company

case studies

1. Costing


ERIM Research Summary

• Designed and carried out scoping survey.

• Theory development and revision

• Designed and carried out audit on 5 cases

• RAID Modelled the case research activities.

• Complete analysis and characterization of audit cases

• Identified barriers to data re-use and strategies to mitigate.

• Established critical points in Information Flow.

• Developed research data management plan process ‘cascade’.


Key ERIM Research Findings I

• Great diversity of data type and quality.

• Complex and chaotic nature of data

development.

• Outputs not linked to data.

• Supporting documents not situated with the data

files.

• Little use of metadata to support future use.

• Immature understanding of benefits of sharing

and thus need for management.

• Limited understanding of the barriers to or

opportunities for information sharing and re-use.


Key ERIM Research Findings II

Poor framework for:

• pre-project considerations of data management.

• 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.


What Needs Managing?

• Research Data:– Data � Data Objects � Information.

• Their life cycle processes:– Collection

– Generation

– Development

– Organization

– Disposal, etc.

• The process of data management itself.


ERDM PLANNING & EXECUTION


What is the Purpose of RDM Planning?

• Reduction in duplicated work.

• Inspiration for new/continuation research &

funding.

• Greater transparency of research.

• Improved basis for validation.

• Obviating the need for re-collection and

generation.

• Providing basis for reliable data citation.

• Increasing scholarly output.

Relies upon RE-USING DATA


Amenability Criteria & ‘Re-usefulness’

‘To manage research data such that they are

highly amenable to re-use.’

‘What is the nature of these data that makes them more or less amenable to re-use?’

• Findability

• Readability

• Comprehensibility

• Interpretability

• Admissibility

• Desirability

Data ‘RE-USEFULNESS’

(some data will remain forever re-useless)


DATA MANAGEMENT PLANNING TASKS


DMP Task Dimensions and Topics

• Access, Data Sharing and Re-use.

• Data Types, Format, Standards and Capture Methods.

• Ethical and Privacy Concerns.

• Resourcing.

• Short-term Storage and Data Management.

• Deposit and Long-term preservation.

• DMP Adherence and Review.DCC DMP Checklist


Data Management is not just about

STORAGE!


Guidance Required to Support Tasks

• Data management planning.

• Data management execution.

• Bid submission.

• Project planning.

• During-project management whilst doing the research.

• Collaboration with colleagues, industry and others.

• Supporting data use, re-use, re-purposing.

• Preparation for long-term preservation.

• End-of-life concerns.


The Two Stages of RDM

‘Managing research data such that they are

highly amenable to re-use.’

• Good DM planning provides the

potential to increase data re-usefulness.

• The execution of good DMPs promotes

data re-usefulness.


Key Building Blocks for Practical Data Management

1. DMP Guidance, Documentation &

Procedures.

2. Storage and security

3. Data Organization

4. Data Documentation


1. DMP Guidance, Documentation & Procedures

Principles for Engineering Research

Data Management.

(erim6rep101028mjd)

Engineering Research Data Management

Plan Requirement Specification

(erim6rep100901ab)

Thematic Analysis of Data Management

Plan Tools and Exemplars.

(erim6rep100701ab)

The Draft IdMRC Projects Data

Management Plan

(erim6rep101015mjd)

1

2

Being a specification for 2

Being an implementation of 1

RAID Associative Tool Specification

(erim6rep101109mjd)RAIDmap Use Cases

(erim6rep101125mjd)

REDm-MED

Prototype

RAIDmap Tool

Model DMP for

Mech. Eng. Depts.


Security: Document/Data Access Levels

Level 1 – In the public domain with an unrestricted

readership and can distributed at will.

Level 2 – Viewable by any individual who has

password access to the main project web site.

Level 3 – Viewable by any individual who has

password access to the main project file store and is

a project-affiliated member of a university research

team.

Level 4 – For sensitive documents. Must carry a

distribution list identifying for whom it is intended and

be disseminated through a nominated secure

passwork-protected portal. Distribution controlled by

PI and Collaborator liaison officer.


3. Data organization


kim12rep05pjw01.doc

Project

name

Document

type

Task

numberAuthor initials

File type

Revision

number

Document

rank number

Work package

number


1. Fill in the document properties (use

metadata!).

2. Make them visible by browsing or by search

– in particular rehabitate the record TITLE.

3. Use a file NAME coding convention that

captures human-readable context

information.

3 Data Organization: 3 steps to document happiness


4. Data Documentation

• RAID-mapping: provision of context.

• Project Document Records:

– Existence Location of key Project Documents

• Project Plan

• Project data management plan

• Project document manifest

– Location of Data Records

– Some description of relations between data

records

ERIM, REDm-MED and Orbital (II)

Education

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