tesci

An interactive toolkit for merging data from multiple citation databases

Overview

TeslaSCIToolkit (abbrev. tesci) is a scientific mapping tool that comes with the following features:

1. Merging data from multiple citation databases
2. Restricting access to sensitive columns in data sources with aggregations
3. Exporting transformed data into other repositories
4. CI/CD integration, currently GitHub Actions

For examples and use-cases, see examples directory.

Quickstart

Aggregating data from a single database source

To create an aggregation of simple.csv based on average salary and age.

1. Interactive approach

tesci start -d simple.csv -o exported.csv
tesci aggregate avg -c salary -a avg_salary
tesci aggregate avg -c age -a avg_age
tesci apply

2. Configuration approach

aggregate:
  - alias: avg_salary
      column: salary
    function: avg
  - alias: avg_age
    column: age
    function: avg
data:
  dest: exported.csv
  src: simple.csv

The result is a transformation from simple.csv to exported.csv:

id name email phone-number age salary 1 John Doe john@mail.com 1234567890 33 100000 2 Jane Doe jane@mail.com 0987654321 44 200000 3 John Smith smith@mail.com 1234509876 55 300000 4 Jane Williams jwilliams@mail.com 1234509876 31 98000 5 Jack Miller 1234509876 33 79000	→	avg_salary avg_age 155400.0 39.2

Merging data from multiple citation databases

After retrieving data sources from citation databases of your choice, place the databases in a directory of your choice. Then, specify the configuration used for merging. An example of a configuration is here.

After specifying your configuration choices, merge can then by run with:

tesci similarity merge --src PATH --src PATH --dest DIR

where PATH and DIR refer to relative or absolute filesystem paths and directories.

Citing tesci

If you find tesci useful in your research, please support our work by citing our paper.

Nikolić, D., Ivanović, D., & Ivanović, L. (2024). An open-source tool for merging data from multiple citation databases.
Scientometrics, 1-23. https://doi.org/10.1007/s11192-024-05076-2

License

Licensed under either of Apache License, Version 2.0 or MIT license.