ASReview-datatools is an extension to ASReview LAB that can be used for describing basic properties of a dataset (e.g., number of papers, number of inclusions, the amount of missing data and duplicates), converting file formats via the command line, and cleaning your (input) data by removing duplicate records.

❣️ ASReview-datatools is the successor to ASReview-statistics. ASReview datatools is available for version 1 or later. Use ASReview statistics for versions 0.x.

The ASReview-datatools extensions requires Python 3.7+ and ASReview LAB version 1 or later.

The easiest way to install the datatools extension is to install from PyPI:

pip install asreview-datatools

After installation of the datatools extension, asreview should automatically detect it. Test this with the following command:

asreview --help

The extension is successfully installed if it lists asreview data.

ASReview-datatools is a command line tool that extends ASReview LAB. Each subsection below describes one of the tools. The structure is

asreview data NAME_OF_TOOL

where NAME_OF_TOOL is the name of one of the tools below (i.e., describe) followed by positional arguments and optional arguments.

Each tool has its own help description which is available with

asreview data NAME_OF_TOOL -h

Describe the content of a dataset

asreview data describe MY_DATASET.csv

Export the results to a file (output.json)

asreview data describe MY_DATASET.csv -o output.json

Describe the van_de_schoot_2017 dataset from the benchmark platform.

asreview data describe benchmark:van_de_schoot_2017 -o output.json

{
  "asreviewVersion": "1.0",
  "apiVersion": "1.0",
  "data": {
    "items": [
      {
        "id": "n_records",
        "title": "Number of records",
        "description": "The number of records in the dataset.",
        "value": 6189
      },
      {
        "id": "n_relevant",
        "title": "Number of relevant records",
        "description": "The number of relevant records in the dataset.",
        "value": 43
      },
      {
        "id": "n_irrelevant",
        "title": "Number of irrelevant records",
        "description": "The number of irrelevant records in the dataset.",
        "value": 6146
      },
      {
        "id": "n_unlabeled",
        "title": "Number of unlabeled records",
        "description": "The number of unlabeled records in the dataset.",
        "value": 0
      },
      {
        "id": "n_missing_title",
        "title": "Number of records with missing title",
        "description": "The number of records in the dataset with missing title.",
        "value": 5
      },
      {
        "id": "n_missing_abstract",
        "title": "Number of records with missing abstract",
        "description": "The number of records in the dataset with missing abstract.",
        "value": 764
      },
      {
        "id": "n_duplicates",
        "title": "Number of duplicate records (basic algorithm)",
        "description": "The number of duplicate records in the dataset based on similar text.",
        "value": 104
      }
    ]
  }
}

Convert the format of a dataset. For example, convert a RIS dataset into a CSV, Excel, or TAB dataset.

asreview data convert MY_DATASET.ris MY_OUTPUT.csv

Remove duplicate records with a simple and straightforward deduplication algorithm (see source code). The algorithm concatenates the title and abstract, whereafter it removes all non-alphanumeric tokens. Then the duplicates are removed.

asreview data dedup MY_DATASET.ris

Export the deduplicated dataset to a file (output.csv)

asreview data dedup MY_DATASET.ris -o output.csv

Using the van_de_schoot_2017 dataset from the benchmark platform.

asreview data dedup benchmark:van_de_schoot_2017 -o van_de_schoot_2017_dedup.csv

This extension is published under the MIT license.

This extension is part of the ASReview project (asreview.ai). It is maintained by the maintainers of ASReview LAB. See ASReview LAB for contact information and more resources.