[4.1] Data Citation and DOI's - Research Data Management - part of PhD course - [3TU.Datacenter]
[1.1] Workshop Introduction - Research Data Management - part of PhD course - [3TU.Datacenter]
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Transcript of [1.1] Workshop Introduction - Research Data Management - part of PhD course - [3TU.Datacenter]
Research Data Management Workshop101 for PhD students, starting their academic career
[2014] CC-BY: 3TU.Datacentre
more info @ www.datacentrum.3tu.nl/en/
What will you learn today
• History about 3TU Datacentre
• Incorporate data management planning in your research workflow
• The key importance of persistent identifiers and data citation in the global scholarly information infrastructure.
• The importance of proper data archiving.
Data Wave
Source: http://www.odgersberndtson.com/en/observe/article/riding-the-data-tidal-wave-7659/
HISTORY
Sources:http://research.microsoft.com/en-us/collaboration/fourthparadigm/http://cordis.europa.eu/fp7/ict/e-infrastructure/docs/hlg-sdi-report.pdf http://www.knowledge-exchange.info/Default.aspx?ID=469
Introduction 3TU.Datacenter• Federation of 3 Technical Universities
– (Delft, Twente, Eindhoven)– Mandate for Research Data Management
• 3TU.Datacenter: start 2008– 12 employees– Archive: 90 TB storage (incl. mirror+backup),
6500 Datasets, ~350 up- & downloads /year,
– Labs: Open Earth, Dataverse, Share
– Services: Datamanagement planning Advise,
DOImining/DataCite, Training, etc.
€
Data archiving: After Research project
Data capture: During Research project
Data Archive
Data planning: Before Research project DMP
Data Lab
Services overview
Research Data
Create
Describe &
Store
Identify &
Register
Discover &
Access
Exploit
Data captureEarly meta data
Data model design
Complete meta dataData repositoryCreate ‘resource maps’/ ‘scientific publication packages’
Assign DOIs‘Publish’ meta dataLinked data
BrowseSearch
Query onlineGoogle maps/earth
Support data-labsData mining support
[ANDS Verbs]
Archives, Labs & Services
Goal: long-term access to research data
• Data archive– Main goal: ‘freeze’ a dataset (version) for future use.
‘Published’ data, simple or complex, varying meta-data, …• Data lab
– Main goal: exchange of data and other research material.Collaboration platforms, specific to discipline/content. Differing in access policies, functionality, size, …
• Data services– Main goal: stimulate improvements in data management.
Advice on standards, licensing & training, support in data documentation, tool development, search and retrieval, …
PREVIEW OF TODAY
Data Management Planning
Persistent Identifiers: Data Claiming and Citation
Data Archiving:Trust and Quality Assurance
Data Archive
INTRODUCTION ROUNDEnjoy today!