Deliverable 1.3 - Revision history

Andrew at 17:30, 5 November 2018

2018-11-05T17:30:59Z

Jacandrade at 18:26, 19 February 2018

2018-02-19T18:26:22Z

Jacandrade at 18:24, 19 February 2018

2018-02-19T18:24:23Z

Jacandrade at 18:01, 9 February 2018

2018-02-09T18:01:51Z

Jacandrade: Created page with " = Deliverable D1.1 - Guidelines for data collection methods, data names and types, and granularity = ---- ---- == Introduction == ---- The various work packages in Prime..."

2018-02-09T17:55:13Z

Created page with " = Deliverable D1.1 - Guidelines for data collection methods, data names and types, and granularity = ---- ---- == Introduction == ---- The various work packages in Prime..."

New page

= Deliverable D1.1 - Guidelines for data collection methods, data names and types, and granularity =

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== Introduction ==

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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.

== 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).

== 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.

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 ==

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

== Appendix 1 - Forms ==

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== Appendix 2 - Templates ==

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@@ Line 1: / Line 1: @@
-= Deliverable D1.3 - Guidelines for data analysis methods, with links to collected data types =
+= Guidelines for data analysis methods, with links to collected data types =
 ----
@@ Line 50: / Line 50: @@
 ----
-===WP2===
+=== WP2 ===
-[[File:D1p3_apx_wp2_1.JPG | center | Annex 1 ]]
+[[File:D1p3 apx wp2 1.JPG|center|Annex 1]] [[File:D1p3 apx wp2 2.JPG|center|Annex 1]] [[File:D1p3 apx wp2 3.JPG|center|Annex 1]] [[File:D1p3 apx wp2 4.JPG|center|Annex 1]] [[File:D1p3 apx wp2 5.JPG|center|Annex 1]] [[File:D1p3 apx wp2 6.JPG|center|Annex 1]] [[File:D1p3 apx wp2 7.JPG|center|Annex 1]] [[File:D1p3 apx wp2 8.JPG|center|Annex 1]] [[File:D1p3 apx wp2 9.JPG|center|Annex 1]] [[File:D1p3 apx wp2 10.JPG|center|Annex 1]] [[File:D1p3 apx wp2 11.JPG|center|Annex 1]] [[File:D1p3 apx wp2 12.JPG|center|Annex 1]] [[File:D1p3 apx wp2 13.JPG|center|Annex 1]] [[File:D1p3 apx wp2 14.JPG|center|Annex 1]] [[File:D1p3 apx wp2 15.JPG|center|Annex 1]] [[File:D1p3 apx wp2 16.JPG|center|Annex 1]] [[File:D1p3 apx wp2 17.JPG|center|Annex 1]] [[File:D1p3 apx wp2 18.JPG|center|Annex 1]] [[File:D1p3 apx wp2 19.JPG|center|Annex 1]] [[File:D1p3 apx wp2 20.JPG|center|Annex 1]] [[File:D1p3 apx wp2 21.JPG|center|Annex 1]] [[File:D1p3 apx wp2 22.JPG|center|Annex 1]] [[File:D1p3 apx wp2 23.JPG|center|Annex 1]] [[File:D1p3 apx wp2 24.JPG|center|Annex 1]]
-===WP3===
+=== WP3 ===
-[[File:D1p3_apx_wp3_1.JPG | center | Annex 1 ]]
+[[File:D1p3 apx wp3 1.JPG|center|Annex 1]] [[File:D1p3 apx wp3 2.JPG|center|Annex 1]] [[File:D1p3 apx wp3 3.JPG|center|Annex 1]] [[File:D1p3 apx wp3 4.JPG|center|Annex 1]] [[File:D1p3 apx wp3 5.JPG|center|Annex 1]] [[File:D1p3 apx wp3 6.JPG|center|Annex 1]] [[File:D1p3 apx wp3 7.JPG|center|Annex 1]] [[File:D1p3 apx wp3 8.JPG|center|Annex 1]] [[File:D1p3 apx wp3 9.JPG|center|Annex 1]] [[File:D1p3 apx wp3 10.JPG|center|Annex 1]]
-===WP4===
+=== WP4 ===
-[[File:D1p3_apx_wp4_1p1.JPG | center | Annex 1 ]]
+[[File:D1p3 apx wp4 1p1.JPG|center|Annex 1]] [[File:D1p3 apx wp4 1p2.JPG|center|Annex 1]] [[File:D1p3 apx wp4 2.JPG|center|Annex 1]] [[File:D1p3 apx wp4 3.JPG|center|Annex 1]] [[File:D1p3 apx wp4 4.JPG|center|Annex 1]]
-===WP5===
+=== WP5 ===
-[[File:D1p3_apx_wp5_1.JPG | center | Annex 1 ]]
+[[File:D1p3 apx wp5 1.JPG|center|Annex 1]] [[File:D1p3 apx wp5 2p1.JPG|center|Annex 1]] [[File:D1p3 apx wp5 2p2.JPG|center|Annex 1]]
-===Non specific work package===
+=== Non specific work package ===
-[[File:D1p3_apx_ns_1p1.JPG | center | Annex 1 ]]
+[[File:D1p3 apx ns 1p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 1p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 2p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 2p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 3p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 3p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 4p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 4p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 5p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 5p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 6p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 6p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 7p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 7p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 8p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 8p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 9p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 9p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 10p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 10p2.JPG|center|Annex 1]] [[File:D1p3 apx ns 11p1.JPG|center|Annex 1]] [[File:D1p3 apx ns 11p2.JPG|center|Annex 1]]
-===Data Analysis Form – Template===
+=== Data Analysis Form – Template ===
-[[File:D1p3_apx_template.JPG | center | Annex 1 ]]
+[[File:D1p3 apx template.JPG|center|Annex 1]]

@@ Line 36: / Line 36: @@
 Whilst each form contains the required information, e.i. which methods are used, the amount of supplementary information varies. This can mainly be attributed to the types of methods used. Certain analysis methods might provide little room for alternative approaches, and thus require little or no additional explanation on the way in which the work has been-, or will be carried out. Other analysis methods, on the other hand might allow for a much more open-ended approach.
+&nbsp;
 == Acknowledgements ==
@@ Line 44: / Line 44: @@
 We wish to thank all the project participants who have contributed to the completion of this deliverable.
+&nbsp;
 == Appendix ==
@@ Line 131: / Line 131: @@
 ===Data Analysis Form – Template===
-[[File:D1p3_apx_ns_template.JPG | center | Annex 1 ]]
+[[File:D1p3_apx_template.JPG | center | Annex 1 ]]

@@ Line 1: / Line 1: @@
-= Deliverable D1.3 -  Guidelines for data analysis methods, with links to collected data types =
+= Deliverable D1.3 - Guidelines for data analysis methods, with links to collected data types =
 ----
@@ Line 10: / Line 10: @@
 ----
 PrimeFish has a wide scope, namely to "improve the economic sustainability of European fisheries and aquaculture sectors". This will be done by gathering data from "individual production companies, industry and sales organisations, consumers and public sources". Such a wide range of sources produces large amounts of diverse data.
 Previous deliverables (D1.1/D1.2) have focused on describing the content of different data sets with regards to data management, -archiving and -sharing, data collection and the use of standards in order to enable harmonisation. This deliverable continues this work and provides a comprehensive overview of the data analysis methods used by the different research groups.
 The forms that were provided by the project participants have been included in the appendix of this document. They are grouped according to work package (WP) number. Where possible, the forms are grouped in the same order that is found in deliverables 1.1 and 1.2. However, in the two mentioned deliverables, one form was used for each data set. In this deliverable, several data sets can be grouped in the same form provided they use the same analysis methods. Certain data sets might also be used either in different work packages or by different organizations, meaning they are mentioned more than once. For these reasons, the number of forms in this deliverable will not be identical to the number in the previous deliverables; neither will the order in which they appear.
 == Methods ==
@@ Line 21: / Line 22: @@
 ----
 In order to obtain the information needed, a form detailing the required information was created and distributed among the project participants. Detailed instructions on how to fill out the form was included in the accompanying e-mail. The form contained a predefined list of different methods categorized under the main headings "Regression; Multivariate; Forecasting; Qualitative; Supply/Value chain analysis". Each header contained between three to five different methods, and participants were asked to tick the box next to each applicable method. The list of possible methods was compiled through a literature review of similar studies as well as method guidelines. The list was not exhaustive, meaning participants also had the option to choose "Other" should none of the options be applicable, and to specify further in a text field.
 The form contained optional fields were participants were invited to provide comments on the application of their method of choice, or to provide links and/or other references to contemporary guidelines for the use of the method(s) in question, such as seminal works or similar. In order to provide a link to the type of data used, the forms use the same data set name/reference as was used in deliverables 1.1 and 1.2 ("Guidelines on data collection methods", and the "Data Management Plan", respectively).
 The form issued is included in the appendix.
 == Conclusion ==
@@ Line 31: / Line 32: @@
 ----
 Deliverable 1.3 "Guidelines on data analysis methods" provides a thorough overview of the different analysis methods that the project participants will make use of over the course of the project. This comprehensive summary will act as a tool enabling participants to gain an insight into the strategies applied by others, and can help researchers working with similar data types to coordinate their efforts in order to ensure a more harmonious final product. This harmonisation of strategies and effort is enabled further through the use of a standardised form containing predefined lists of choices.
@@ Line 44: / Line 46: @@
-== Appendix==
+== Appendix ==
 ----

@@ Line 1: / Line 1: @@
-= Deliverable D1.1 - Guidelines for data collection methods, data names and types, and granularity =
+= Deliverable D1.3 -  Guidelines for data analysis methods, with links to collected data types =
 ----
@@ Line 10: / Line 10: @@
 ----
-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.
+PrimeFish has a wide scope, namely to "improve the economic sustainability of European fisheries and aquaculture sectors". This will be done by gathering data from "individual production companies, industry and sales organisations, consumers and public sources". Such a wide range of sources produces large amounts of diverse data.
 == Methods ==
@@ Line 16: / Line 21: @@
 ----
-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).
+In order to obtain the information needed, a form detailing the required information was created and distributed among the project participants. Detailed instructions on how to fill out the form was included in the accompanying e-mail. The form contained a predefined list of different methods categorized under the main headings "Regression; Multivariate; Forecasting; Qualitative; Supply/Value chain analysis". Each header contained between three to five different methods, and participants were asked to tick the box next to each applicable method. The list of possible methods was compiled through a literature review of similar studies as well as method guidelines. The list was not exhaustive, meaning participants also had the option to choose "Other" should none of the options be applicable, and to specify further in a text field.
 == Conclusion ==
@@ Line 22: / Line 31: @@
 ----
-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.
+Deliverable 1.3 "Guidelines on data analysis methods" provides a thorough overview of the different analysis methods that the project participants will make use of over the course of the project. This comprehensive summary will act as a tool enabling participants to gain an insight into the strategies applied by others, and can help researchers working with similar data types to coordinate their efforts in order to ensure a more harmonious final product. This harmonisation of strategies and effort is enabled further through the use of a standardised form containing predefined lists of choices.
 == Acknowledgements ==
@@ Line 32: / Line 42: @@
 We wish to thank all the project participants who have contributed to the completion of this deliverable.
-== Appendix 2 - Templates ==
+== Appendix==
 ----