MaLDReTH Research Data Lifecycle

Official visualization based on MaLDReTH deliverables showing the 12-stage research data lifecycle with tool mapping

Based on MaLDReTH Deliverable D2.1 and D3.1 specifications - Circular lifecycle model with interconnected stages

Official MaLDReTH Flow

Based on deliverable diagram

The MaLDReTH Research Data Lifecycle

MaLDReTH Research Data Lifecycle

Interactive nested visualization - click stages to expand categories and tools

Return
1
Conceptualise
To formulate the initial resea...
9 3
2
Plan
To establish a structured stra...
9 3
3
Fund
To identify and acquire financ...
0 0
4
Collect
To use predefined procedures, ...
9 3
5
Process
To make new and existing data ...
8 3
6
Analyse
To derive insights, knowledge,...
5 3
7
Store
To record data using technolog...
6 3
8
Publish
To release research data in pu...
4 3
9
Preserve
To ensure the safety, integrit...
5 3
10
Share
To make data available and acc...
3 3
11
Access
To control and manage data acc...
7 3
12
Transform
To create new data from the or...
7 3

Research Data Lifecycle Stages

Stage Name Description Tools Categories
1 CONCEPTUALISE To formulate the initial research idea or hypothesis, and define the scope of the research project a... 9 3
2 PLAN To establish a structured strategic framework for management of the research project, outlining aims... 9 3
3 FUND To identify and acquire financial resources to support the research project, including data collecti... 0 0
4 COLLECT To use predefined procedures, methodologies and instruments to acquire and store data that is reliab... 9 3
5 PROCESS To make new and existing data analysis-ready. This may involve standardised pre-processing, cleaning... 8 3
6 ANALYSE To derive insights, knowledge, and understanding from processed data.... 5 3
7 STORE To record data using technological media appropriate for processing and analysis whilst maintaining ... 6 3
8 PUBLISH To release research data in published form for use by others with appropriate metadata for citation ... 4 3
9 PRESERVE To ensure the safety, integrity, and accessibility of data for as long as necessary so that data is ... 5 3
10 SHARE To make data available and accessible to humans and/or machines.... 3 3
11 ACCESS To control and manage data access by designated users and reusers.... 7 3
12 TRANSFORM To create new data from the original, for example by migration into a different format or by creatin... 7 3

Tool Categories by Lifecycle Stage

1. CONCEPTUALISE
Mind mapping, concept mapping and knowledge modelling
3 tools
Diagramming and flowchart
3 tools
Wireframing and prototyping
3 tools
2. PLAN
Data management planning (DMP)
3 tools
Project planning
3 tools
Combined DMP/project
3 tools
3. FUND
4. COLLECT
Quantitative data collection tool
3 tools
Qualitative data collection (e.g. Survey tool)
3 tools
Harvesting tool (e.g. WebScrapers)
3 tools
5. PROCESS
Electronic laboratory notebooks (ELNs)
4 tools
Scientific computing across all programming languages
3 tools
Metadata Tool
1 tools
6. ANALYSE
Remediation (e.g. motion capture for gait analysis)
1 tools
Computational methods (e.g. Statistical software)
2 tools
Computational tools
2 tools
7. STORE
Data Repository
3 tools
Archive
1 tools
Management tool
2 tools
8. PUBLISH
Discipline-specific data repository
1 tools
Generalist data repository
1 tools
Metadata repository
2 tools
9. PRESERVE
Data repository
1 tools
Archive
1 tools
Containers
3 tools
10. SHARE
Data repository
0 tools
Electronic laboratory notebooks (ELNs)
2 tools
Scientific computing across all programming languages
1 tools
11. ACCESS
Data repository
1 tools
Database
3 tools
Authorisation/Authentication Infrastructure
3 tools
12. TRANSFORM
Electronic laboratory notebooks (ELNs)
1 tools
Programming languages
3 tools
Extract, Transform, Load (ETL) tools
3 tools
Build: 2024.003
Date:
Time: