Data management and data sharing: An ecologists perspective

Erlend B. Nilsen (Senior Researcher, NINA)

Anders G. Finstad (Associate Professor, NTNU)

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Aiming for the impossible?

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Ecological data

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Well deveolped infrastructure for georeferenced occurence data

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But; usually ecological data sets are often more complex…

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Finstad,  Nilsen  &  Hendrichsen,  unpublished  

In fact: Ecological data sets are often far more complex

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Data life cycle

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Data  life  cycle  

Planning  projects  and  data  capture      

Planning  

Planning  of  data  capture;  but  also  long  term  storage  and  documenta>o  

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Data  life  cycle  

Data  capture      

Data  capture  

Planning  

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Data  life  cycle  

Quality  controll      

Outliers,  missing  data,  etc.  

Data  capture  

Quality  controll  

Planning  

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Data  life  cycle  

Documenta>on      

•  Make  data  recongizable  (also  for  yourself!)  through  metadata  

•  Metadata  standards  (what  is  stored,  and  where)  

Planning  

Data  capture  

Quality  controll  

Documenta>on  

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Planning  

Data  capture  

Quality  controll  

Documenta>on  

Store,  secure,  share  

Data  life  cycle  

•  From  internal  data  bases  to  external  «data  hubs»  

 

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Planlegge  

Samle  

Quality  controll  

Documenta>on  

Store,  secure,  share   Rediscover  

Integrate  

Analyze  

Data  life  cycle  

Old  data  get  a  new  life      

Metaanalysis,  before  /  aRer  studies,  new  analys>cal  tools,  integra>on  with  climate  and  environmental  data.  

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Planning  

Data  capture  

Quality  controll  

Documenta>on  

Store,  secure,  share  

Rediscover  

Integrate  

Analyze  

Data  life  cycle  

   

Hierarchical  dependence:    Fysical  storage  makes  no  sense  without  solid  documenta8on  

What  should  be  preserved,  and  how  

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Securing and sharing research data – why should scientists care? - Data synthesis and «big data»

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The world needs science that is open, reproducible and transparent

Securing  and  sharing  research  data  –  why  should  scien>sts  care?    -­‐  Reproducibility  and  fraud    

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Securing and sharing research data – why should scientists care? - Demand from funders

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Securing and sharing research data – why should scientists care? - Demand from journals

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Data sharing and authorship

”Authorship  credit  should  be  based  on  1)  substan5al  contribu5ons  to  concep5on  and  design,  acquisi5on  of  data,  or  analysis  and  interpreta5on  of  data;  2)  dra=ing  the  ar5cle  or  revising  it  cri5cally  for  important  intellectual  content;  and  3)  final  approval  of  the  version  to  be  published.  Authors  should  meet  condi5ons  1,  2,  and  3.”  (ICMJE  2010,  kapi\el  om  Authorship)    ”Acquisi5on  of  funding,  collec5on  of  data,  or  general  supervision  of  the  research  group  alone  does  not  cons5tute  authorship.”  

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But – unique access to data is an advantage when applying for research funding

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Positive incitaments to make data sharing valuable to the independent researchers and their institutions

•  Sharing data just becasuse the funders demand it is likely to result in suboptimal documentation and data quality controll

}  «It just add another burden to an allready stressed workingday»

•  The current basic funding system is structured around # journal papers, grants, students etc.

•  Adjusting the current funding system so that data sharing becomes valuable to the independent scientist and their institutions

}  Making sure that when data is re-used in another project, the data owner/author gets credit!

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Offentlig finansierte miljødata må ivaretas og tilgjengeliggjøres Det samles inn betydelige mengder data av ulik slag i forbindelse med forskningsprosjekter og overvåking. Disse data er organisert, finansiert og ivaretatt på ulike måter. Selv om de er offentlig finansiert, er de ikke alltid tilgjengelige for andre. Dette er ikke tilfredsstillende. Det foreslås at det opprettes et prosjekt for å utarbeide retningslinjer og virkemidler for hvordan data bør sikres stabil finansiering og gjøres tilgjengelig for alle, samt for spørsmål knyttet til rettigheter og publisering.

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Summary •  There is an interesting movement towards better data documentation, standardization and sharing within ecological science

}  This will facilitate novel research that is needed to provide guidance for ongoing environmental changes

•  There is a urgent need for better infrastructure and routines for data documentation, standardization and sharing

•  Incitaments to promote data sharing in addition to demands from funders is likely to speed up the process

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Foto på side 1: P. Jordhøy, J. Thomassen, E. B. Thorstad, A. Staverløkk, T. Aarvak, B. Løken/Samfoto

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