Notes on Population Data


IJPDS is delighted to present this new call for manuscripts for our new special collection of Notes on Population Data.

This collection will consist of articles allowing researchers and practitioners to report on unexpected or underestimated data issues encountered during their population data science projects. These can be any aspect of the data pipeline: how data was collected, recorded, sampled, captured, processed, standardised, cleaned, transformed, linked, integrated, and merged/fused. Often, either nothing or only very limited details of these processes and tasks are described in journal publications. As a result, lessons learnt in data aspects are not shared with the community.

Please note that we are not considering manuscripts that report on data science projects that did not result in any useful end product or analysis, especially due to statistical design issues, or legal or organisational constraints. Rather, we are interested in manuscripts that describe the problems encountered in the data pipeline and where the reader can learn something for their own projects, not the specific one described in a manuscript.

The emphasis of a Data Note should not be on the description of a data set but rather on the process of what has been done with this data in the data pipeline from its source until it was research-ready. The reader should learn what kind of unexpected technical or organisational problems were encountered and if or how these problems could be solved. For a list of issues that potentially can affect population data and a description of the data pipeline, we encourage all authors of Data Note manuscripts to read the IJPDS article "Thirty-three myths and misconceptions about population data: from data capture and processing to linkage".

Submissions to this collection should typically include the following:

  • An abstract including:
    • A brief description of the data set(s) used,
    • the data challenges encountered in this project,
    • and lessons learned that should be of general use for other projects.
  • An introduction, including a description of the purpose and aims of the project where these data issues occurred.
  • A description of the data sources (data collections, databases, or data sets), such as where the data comes from, how the data have been captured (collected, recorded, or sampled from), and their content, structure, size, etc. This section should include a basic data description and summary of data quality aspects relevant to the Data Note.
  • A description of the methods used in the data pipeline of this project, such as what data cleaning, data processing, and / or data linking methods have been used.
  • A discussion of the data issues, problems, and challenges that have been encountered in this project, and how they have been overcome. Neither problems due to legal or organisational restrictions nor statistical design issues are of core interest in Data Notes.
  • A section on recommendations and lessons learnt should contain take-home messages for the reader that will help them limit or even prevent similar issues or mistakes from occurring in their projects. These recommendations and lessons should be of general interest and not specific to the project described in the manuscript. They can include approaches taken by the authors of a Data Note to turn their data into a form suitable for their project by making them more reliable or useful for inferences about a population.
  • A section of Conclusions, which summarises the findings and recommendations.

Word Limit: 2000 - 5000

Please refer to the Author Guidelines/How to Format Notes on Population Data for specifics on how to format your manuscript before completing your submission.

This call will remain always open so that we can compile Notes on Population Data on a continuous basis and share this valuable corpus with the global Population Data Science community into the future.

All manuscripts must be centred on Population Data Science, as per the scope of IJPDS.

To submit a manuscript: either login to your existing account or register if you are submitting for the first time.