Difference between revisions of "Deliverable 1.2"

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= Deliverable D1.1 - Guidelines for data collection methods, data names and types, and granularity =
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= Deliverable D1.2 - Data Management Plan =
  
 
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The various work packages in PrimeFish cover several different aspects of the economic sustainability and competitiveness of the European seafood sector. This entails a substantial amount of diverse data including, but not limited to, data on price development, socio-economic factors, supply chain relations, consumer behaviour etc. The project will use both already existing data extracted from various databases or other sources, as well as data generated in connection to PrimeFish. Having a uniform approach to not only the data collection, but also the standardisation and analysis methods is needed for several reasons. Firstly, to ensure that sufficient data is produced and gathered for each case. Secondly, to have a uniform approach to naming and interpreting the data. Thirdly, that there is a comparable level of detail and granularity in each case, and lastly, to make the data available in a uniform way to all relevant parties. The information provided for all submitted data sets are included in the appendix of this document. The forms are grouped according to the corresponding work package (WP). Forms where the work package-number was not listed have been included under "non-specific WP". The forms are further subdivided by task-number where possible. If no task-number has been indicated, they are placed in no particular order. The header for each data set is the same as the header for each corresponding data set in D1.2, and can thus be used as a reference for further information regarding the different data sets. The order of the data sets is the same in both deliverables.
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As part of the Pilot Action on Open Access to Research Data in Horizon 2020, participants in PrimeFish will have to create a Data Management Plan (DMP). The Data Management Plans included in this document outlines the general information regarding each data set, covering several subjects all relevant to data management and the possible reuse of data sets. Each data management plan (DMP) gives an overview on what sort of data the data set contains, and what (if any) standards are being used. Information about the content of the data set includes both an overview of the different variables included as well as metadata. This goes for both data extracted from existing sources as well as data developed over the course of the PrimeFish-project.  
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A major focal point of the Pilot Action on Open Access to Research Data is the possibility of sharing and reusing data sets. Each DMP outlines whether or not access to the data is (semi-)restricted to certain institutions or if it is available without restrictions. In any case, the DMP describes who has the right to use to it, and how it might be accessed. This includes access procedures, which repository the data is stored in, etc. It also details possible barriers to dissemination such as the need for certain software, language barriers, etc.
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As the possibilities of reusing and sharing data depends on, among other things, the methods used for preserving and archiving the data sets, procedures for long-term storage of data are also outlined. This section details for how long the data set will be preserved (for a given time period or indefinite), methods of backup, the possibility of future incongruence between the extracted data and the original sources due to periodical updates of the latter one, etc.  
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All submitted data management plans are included in the appendix of this document. They are grouped according to the corresponding work package (WP). The data management plans within are listed first according to sub-task where this has been provided. If no task-number has been listed, they have been placed in no particular order. Where possible, the corresponding WP- and task-number is listed for each DMP along with the institution. In cases where two or more identical data management plans were submitted for different tasks, these have been included as only one form.  
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== Methods ==
 
== Methods ==
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This deliverable, D1.1, is closely tied to D1.2 - "Data Management Plan". As part of D1.2, participants in PrimeFish were asked to create a Data Management Plan (DMP). A DMP-template was distributed among the project participants, along with instructions on how to fill out the form. The form contained questions regarding details on the data elements, metadata, data sharing procedures, archiving/preservation procedures and the overall structure of the data set. The majority of the information provided made up the data management plan in D1.2, but it also formed the basis for D1.1. The data set names have been edited to better reflect the content of the data set. These follow a standardised form (Sector – Nation/Region – Data description – Time period).
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A DMP-template was distributed among all project participants, along with instructions on how to fill out the form. Instructions were given both by e-mail and through a separate, and more detailed, "explanation-file" (both the template and explanation are included in the appendix). The information requested in the DMP-template was meant to form the basis for deliverables 1.1 and 1.2 ("Guidelines on data collection methods", and the "Data Management Plan", respectively). A draft of the deliverable containing all submitted forms was sent out to the project participants in order to be reviewed. The deliverable was later edited based on the feedback provided by the participants.  
  
 
== Conclusion ==
 
== Conclusion ==
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Deliverable 1.1 "Guidelines for data collection methods, data names and types, and granularity" focuses on namely what the title suggests, and provides a report with information on the different methods used in each data set. This includes methods on data collection for both extracted and generated data, as well as the use of names, standards and types.
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The Data Managements Plans provided in this document give a detailed overview on the essential elements in the corresponding data sets. They have been reworked based on feedback provided by the project participants. However, the process has highlighted some slight difficulties concerning both the level of detail provided and the potential for harmonization between DMPs. Different data sets corresponds to different WPs, all of whom have different schedules. As a result, the amount of information regarding the data sets might vary greatly depending on how far along in the process each participant is at any given time. It also appears that the project participants have interpreted the DMP requirements differently, leading to different ways of filling out the form. This is turn has made harmonizing between DMPs difficult.
 
 
The amount of information for each data set varies depending on the level of detail provided by each participant. The reason for this might be partly due to the project participants being responsible for different tasks - all of whom are on different time schedules. The amount of information provided thus largely depends on how far along the process each participant is. The different types of data used also dictates what kind of information is relevant in each case. Qualitative and quantitative data sets different limits on the extent to which one can identify standards.
 
  
 
== Acknowledgements ==
 
== Acknowledgements ==
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We wish to thank all the project participants who have contributed to the completion of this deliverable.
 
We wish to thank all the project participants who have contributed to the completion of this deliverable.
  
== Appendix 1 - Forms ==
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== References ==
  
 
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== Appendix 2 - Templates ==
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*''Guidelines on Data Management in Horizon 2020''. Version 1, Dec. 11. 2013.
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*''Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020''. Version 2.0, Oct. 30th. 2015.
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== Appendix 1 ==
  
 
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Revision as of 18:59, 9 February 2018

Deliverable D1.2 - Data Management Plan



Introduction


As part of the Pilot Action on Open Access to Research Data in Horizon 2020, participants in PrimeFish will have to create a Data Management Plan (DMP). The Data Management Plans included in this document outlines the general information regarding each data set, covering several subjects all relevant to data management and the possible reuse of data sets. Each data management plan (DMP) gives an overview on what sort of data the data set contains, and what (if any) standards are being used. Information about the content of the data set includes both an overview of the different variables included as well as metadata. This goes for both data extracted from existing sources as well as data developed over the course of the PrimeFish-project.

A major focal point of the Pilot Action on Open Access to Research Data is the possibility of sharing and reusing data sets. Each DMP outlines whether or not access to the data is (semi-)restricted to certain institutions or if it is available without restrictions. In any case, the DMP describes who has the right to use to it, and how it might be accessed. This includes access procedures, which repository the data is stored in, etc. It also details possible barriers to dissemination such as the need for certain software, language barriers, etc.

As the possibilities of reusing and sharing data depends on, among other things, the methods used for preserving and archiving the data sets, procedures for long-term storage of data are also outlined. This section details for how long the data set will be preserved (for a given time period or indefinite), methods of backup, the possibility of future incongruence between the extracted data and the original sources due to periodical updates of the latter one, etc.

All submitted data management plans are included in the appendix of this document. They are grouped according to the corresponding work package (WP). The data management plans within are listed first according to sub-task where this has been provided. If no task-number has been listed, they have been placed in no particular order. Where possible, the corresponding WP- and task-number is listed for each DMP along with the institution. In cases where two or more identical data management plans were submitted for different tasks, these have been included as only one form.


Methods


A DMP-template was distributed among all project participants, along with instructions on how to fill out the form. Instructions were given both by e-mail and through a separate, and more detailed, "explanation-file" (both the template and explanation are included in the appendix). The information requested in the DMP-template was meant to form the basis for deliverables 1.1 and 1.2 ("Guidelines on data collection methods", and the "Data Management Plan", respectively). A draft of the deliverable containing all submitted forms was sent out to the project participants in order to be reviewed. The deliverable was later edited based on the feedback provided by the participants.

Conclusion


The Data Managements Plans provided in this document give a detailed overview on the essential elements in the corresponding data sets. They have been reworked based on feedback provided by the project participants. However, the process has highlighted some slight difficulties concerning both the level of detail provided and the potential for harmonization between DMPs. Different data sets corresponds to different WPs, all of whom have different schedules. As a result, the amount of information regarding the data sets might vary greatly depending on how far along in the process each participant is at any given time. It also appears that the project participants have interpreted the DMP requirements differently, leading to different ways of filling out the form. This is turn has made harmonizing between DMPs difficult.

Acknowledgements


We wish to thank all the project participants who have contributed to the completion of this deliverable.

References


  • Guidelines on Data Management in Horizon 2020. Version 1, Dec. 11. 2013.
  • Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020. Version 2.0, Oct. 30th. 2015.


Appendix 1