In pbs-assess/gfsynopsis: Data Synopsis Reports for PBS Groundfish
Start broader, discuss challenges of and value of data visualization in general.
Narrow in our motivation and what we did, flow from databases to R packages to the paper. Show two figures - one for each species page from the synopsis report.
Journal ideas:
- Canadian Journal of Fisheries and Aquatic Science - rapid communication
- 2 figure limit
-
2500 words
-
Fisheries Research - short communication (not technical communication)
- no figure limit
- ~6 page limit (doesn't appear to be strictly enforced; eg. some with 8 pages)
...
- PLoS One
- few, if any, restrictions
Thoughts on how to frame the paper:
-
Put in framework of complexity of systems (particularly marine). Discuss
ability to detect environmental or stock changes (eg. climate change, stock
status) quickly and respond quickly. Focus more broadly, not only narrowly as
in a few intense stock assessments, but more broadly monitor many species in
many ways. (see Hilborn reference 1970's)
-
Frame in context of high volumes of data, with increasing sensor technology,
drone surveys, collecting vast quantities of data. Problematic to look at all of
these data. Tie into movement towards open data/open science/transparency.
Openness is about more than just data availablity, but is also about
summarizing the data in a digestable way.
suggested beginning paragraph to get readers in
Perhaps frame in context of vast amounts of data, then discuss our specific
issues relating to tons of data
with discussion on
applicability to the issue of visualizing data quickly to be able to detect
and quickly respond to any changes.
In addition, communicate what we've learned along the way.
Uses (perhaps end of intro - what our goals were):
- new staff coming up to speed with summaries of what the data are and what the
data mean
- at meetings about individual species - good overview of stocks and data
availability
- facilitate discussions between managers and scientists about priorities
(visual tool to show stock and biological trends relevant to discussion)
- rapid detection of data issues (that may go unseen and into assessments/research)
- engaging data gathering partners, stakeholders, funding sources - showcase
the data to participants, strengthen relationships with industry (show them
where their money is going, that the data are being used and not sitting away
in a database)
- useful tools for stock assessment and other research
- good first glance when deciding approaches, what data are available for modelling, analysis, etc.
- standardize process of data extraction and summarizing
- identify data gaps for directing research efforts/funding
Insights:
- this was only possible because of well-structured databases
- modular code has made the tools usable for other contexts
- there were major benefits to limiting ourselves to 2 pages per species so all the data can be taken and once
- showing blank plots indicating missing data was critical: (1) it ensures the same layout for all species so the user knows where to look quickly (2) it emphasizes what we just don't know (known unknowns)
- a fully reproducible pipeline from databases to final report is critical. For one, the process is inevitably iterated on many times as changes are suggested and problems with the data and modelling are fixed. Secondly, the real benefit is that this can be updated regularly and rapidly.
What we did:
- briefly describe the elements of our plots
- explain the design decisions we made (some things could go here or in the insights section):
- colour (consistent colours for surveys, colourblind proof, prints and greyscale)
- layout (put like things together, keep all individual fish sample data on one page)
- species to focus on (relevant to commercial or recreational fisheries, relevant to conservation, relevant to First Nations, or caught regularly in our surveys)
- surveys to focus on (the ones applicable to the most species)
- show uncertainty wherever possible
- focus on both spatial and temporal
- combine relevant metadata in one place and link to relevant resources
- mention the opportunities for feedback and meetings that we had
- mention the R packages and what they do
- mention our intended annual or biennual schedule
Discussion points:
pbs-assess/gfsynopsis documentation built on March 26, 2024, 7:30 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Start broader, discuss challenges of and value of data visualization in general. Narrow in our motivation and what we did, flow from databases to R packages to the paper. Show two figures - one for each species page from the synopsis report.
Journal ideas:
- Canadian Journal of Fisheries and Aquatic Science - rapid communication
- 2 figure limit
-
2500 words
-
Fisheries Research - short communication (not technical communication)
- no figure limit
- ~6 page limit (doesn't appear to be strictly enforced; eg. some with 8 pages)
...
- PLoS One
- few, if any, restrictions
Thoughts on how to frame the paper:
-
Put in framework of complexity of systems (particularly marine). Discuss ability to detect environmental or stock changes (eg. climate change, stock status) quickly and respond quickly. Focus more broadly, not only narrowly as in a few intense stock assessments, but more broadly monitor many species in many ways. (see Hilborn reference 1970's)
-
Frame in context of high volumes of data, with increasing sensor technology, drone surveys, collecting vast quantities of data. Problematic to look at all of these data. Tie into movement towards open data/open science/transparency. Openness is about more than just data availablity, but is also about summarizing the data in a digestable way.
suggested beginning paragraph to get readers in
Perhaps frame in context of vast amounts of data, then discuss our specific issues relating to tons of data with discussion on applicability to the issue of visualizing data quickly to be able to detect and quickly respond to any changes.
In addition, communicate what we've learned along the way.
Uses (perhaps end of intro - what our goals were):
- new staff coming up to speed with summaries of what the data are and what the data mean
- at meetings about individual species - good overview of stocks and data availability
- facilitate discussions between managers and scientists about priorities (visual tool to show stock and biological trends relevant to discussion)
- rapid detection of data issues (that may go unseen and into assessments/research)
- engaging data gathering partners, stakeholders, funding sources - showcase the data to participants, strengthen relationships with industry (show them where their money is going, that the data are being used and not sitting away in a database)
- useful tools for stock assessment and other research
- good first glance when deciding approaches, what data are available for modelling, analysis, etc.
- standardize process of data extraction and summarizing
- identify data gaps for directing research efforts/funding
Insights:
- this was only possible because of well-structured databases
- modular code has made the tools usable for other contexts
- there were major benefits to limiting ourselves to 2 pages per species so all the data can be taken and once
- showing blank plots indicating missing data was critical: (1) it ensures the same layout for all species so the user knows where to look quickly (2) it emphasizes what we just don't know (known unknowns)
- a fully reproducible pipeline from databases to final report is critical. For one, the process is inevitably iterated on many times as changes are suggested and problems with the data and modelling are fixed. Secondly, the real benefit is that this can be updated regularly and rapidly.
What we did:
- briefly describe the elements of our plots
- explain the design decisions we made (some things could go here or in the insights section):
- colour (consistent colours for surveys, colourblind proof, prints and greyscale)
- layout (put like things together, keep all individual fish sample data on one page)
- species to focus on (relevant to commercial or recreational fisheries, relevant to conservation, relevant to First Nations, or caught regularly in our surveys)
- surveys to focus on (the ones applicable to the most species)
- show uncertainty wherever possible
- focus on both spatial and temporal
- combine relevant metadata in one place and link to relevant resources
- mention the opportunities for feedback and meetings that we had
- mention the R packages and what they do
- mention our intended annual or biennual schedule
Discussion points:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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