Python script to facilitate matching reviewers with entrants (i.e., reviewees), using CSV-formatted input files. Both the entrants.csv and reviewers.csv are 4-column files that contain a) the name (first and last), b) their email, c) the methods that they are experts in, and d) their research topics. The reviewers.csv can also have additional columns at the end containing their history of review participation, whose column headers must include the word "Round" for filtering purposes and values as 'yes' or 'no'.
A 2 column, semicolon-separated taxonomy.csv file is included for suggestions on values for topics and methods.
The entrants.csv and reviewers.csv can be generated using a spreadsheet program.
Running the notebook will result in the creation of matching_results.csv.
Figure 1. An illustration of resulting matching for 10 entrants, each requiring
3 reviews and each reviewer being responsible for performing 3.
Depending on the numbers (e.g., reviewer_responsibility = 5 and entrant_needed_reviews = 3 for 10 entrants), the script can result in a reviewer obtaining the same entrant twice. To check this sort the results dataframe by both the reviewers and the entrants and do a visual inspection. Until this is solved, please check the results and hand edit where needed.
- reviewers CSV file (; separated)
- entrants CSV file (; separated)
- use_history - 'True' or 'False'
- reviewer_responsibility - number of reviews to be done by each reviewer
- entrant_needed_reviews - number of reviews need for each entrant
- CSV formatted file of matchings (; separated), including itemized and total matching scores.
- prints to screen the suggested best matchings
- Pandas
The structure and examples of the entrants.csv and reviewers.csv input files can be found below. The "Methods" and "Topics" can be several entries that are separated by a comma. For the reviewers.csv, it is assumed that the last columns are the histories of their participation (i.e., 'yes' or 'no'). These are provided in a column whose header name includes the word 'Round' (see example).
Karl N. Kirschner
Department of Computer Science
University of Applied Sciences Bonn-Rhein-Sieg
Grantham-Allee 20
53757 Sankt Augustin - Germany
Email: k.n.kirschner at gmail.com
Concept: Kirschner
Coding and structure: Jiang, Daniel and Bitterling, Robert (prototype); Kirschner
Name;Email;Methods;Topics
Zoowee Blubberworth;[email protected];Mathematics, md;viruses, Security
Flufffy Gloomkins;[email protected];md, Statistics;Virtual Reality, proteins
etc.
Name;Email;Methods;Topics;Round 2016;Round 2017;Round 2018;Round 2019
Peafy Doodoofish;[email protected];Numerical Algorithms, Statistical Mechanics, Infrared, Python;Security, Viruses, Virtual Reality, Carbohydrates;No; No; Yes; No
Peawee Pimplehair;[email protected];Numerical Algorithms, Bioinformatics, NMR, Raman;Methods Development, Virtual Reality, DNA, Viruses;Yes; Yes; No; No
Chewlu Boogerbrain;[email protected];Basis Sets, Statistical Mechanics, Molecular Dynamics, Bioinformatics;Security, Virtual Reality, Methods Development, Protein;No; No; No; No
Eggster HoboSmittens;[email protected];Infrared, Machine Learning, NMR, Raman;Security, Carbohydrates, Viruses, DNA;Yes; Yes; Yes; Yes
etc.
Reviewer Name;Entrant Name;Itemized Score [topics, methods, reviewer's history];Total Score
Fartmoo PimpleFadden;Flapberry Fudgewhistle;['1.000', '1.000', 0];2.0
Fartmoo PimpleFadden;Buritt Noseface;['0.500', '0.500', 0];1.0
Fartmoo PimpleFadden;Peaberry Wigglewhistle;['1.000', '0.000', 0];1.0
Ratspitz Noodlehill;Buritt Noseface;['0.500', '0.500', 0];1.0
Ratspitz Noodlehill;Peaberry Wigglewhistle;['0.500', '0.500', 0];1.0
Ratspitz Noodlehill;Trashwee Sockborn;['0.500', '0.500', 0];1.0
etc.
Topics;Methods
admet;cg
aerosols;bioinformatics
agriculture and food;cheminformatics
analytical;dft
atmospheric;docking
...
viruses;
waste and recycling;
water;
zwitterions;
- Fake names obtained from: https://www.imagineforest.com/blog/funny-name-generator/
- The Sankey illustration was made using https://github.com/riley-x/SankeyFlow.git