# Paradata, from by-product to standard documentation

Ingo Barkow, Geneviève Michaud, Anja Perry, David Schiller, Wendy Thomas

## ► To cite this version:

Ingo Barkow, Geneviève Michaud, Anja Perry, David Schiller, Wendy Thomas. Paradata, from by-product to standard documentation. 12th Annual European DDI User Conference (EDDI 2020). 2020. [https://doi.org/10.5407/eddi.2020.03906466](https://doi.org/10.5407/eddi.2020.03906466)

HAL Id: hal-03906466

https://sciencespo.hal.science/hal-03906466

Submitted on 19 Dec 2022

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_1.png" /></figure>
<figure><img src="image_2.png" /></figure>

# Paradata - from by-product to standard documentation

<figure><img src="image_3.png" /></figure>

12th Annual European DDI User Conference - 01-12-2020

Ingo Barkow (FHGR), Geneviève Michaud (Sciences Po), Anja Perry (GESIS), David Schiller (FHGR), Wendy Thomas (IPUMS)

DOI: 10.5281/zenodo.4299076

Creative Commons Attribution 4.0 International (CC BY 4.0)
Paradata - from
by-product to standard
documentation

• first definition

· modes of collection

· what paradata are or are not

· examples

· potential usage

· barriers to publication

· use cases

· primary use

· potential of reuse

· the call for a model

· from by-product to standard
documentation

· DDI framework

· next steps for this group
first definition

There is no clear definition of paradata,
but it is mainly viewed as auxiliary data collected in a survey as a
by-product that describe the collection process. Although such a
concept is not limited to a specific discipline, it is often discussed
linked to survey research.
## how paradata are collected

Depending on the mode of data collection:

* automatically, manually

* at different levels:

* interviewer or survey agency

* respondent level (self-administered surveys)

* item level (passive data collection)
what paradata are or are not

* paradata are not auxiliary data

* stratum identifiers, demographic features of Census tracts, data from commercial sources

* data from different sources

* some metadata are in fact paradata

* response rates for example
paradata examples

* call records, contact history and disposition codes

* successful interview, hard refusal, non-contact

* audio-recordings, verbal paradata

* pauses, voice pitch

* response behavior in online survey

* keystrokes, navigation within the survey, correction of answers

* sensor data

* such as GPS data
potential paradata usage

* improve survey quality

* field monitoring, and costs control

* included in total survey error measures

* post-survey assessment or corrections of errors

* paradata-driven basis to improve survey quality in a longitudinal study
barriers to paradata publication

* post-processing is resource-consuming,

* no standard format,

* ethics and legal concerns:

* in European studies, GDPR requires respondent's "specific and informed" consent prior to data collection,

* dramatic increase in **re-identification risk.**
# paradata stories and use cases

* Multiple modes of paradata generation

* PIAAC

* Log files from wearables

* SensoMot

* Survey methodology

* CRONOS

* ELIPSS
paradata stories and use cases

* Paradata on clinical trials

* Capture protocols

* clinical trials template

* Integration/Harmonization

* IPUMS experience

* Privacy Preservation Environment - Statistics Canada
paradata primary use

* verification,

* quality control content management,

* data processing,

* international normalization,

* data analysis,

Overall, paradata support the evaluation of the primary data collection and the processes used to capture it.
potential of reuse

What our uses cases show is a huge potential for reuse and analysis.

In fact, paradata is often not released.

To fully realize this potential, we need a model framework, i.e basic
requirements.

This model would be used as a guideline for researchers during the
first steps of study design.
the call for a model

This would help to move paradata from a totally internal
information resource to a research object that can be published and
reused.
from by-product to standard documentation

This would help to move paradata from a totally internal
information resource, an under-(re)used, internal by-product, to a
research object that can be published and reused.
# DDI framework

Given the role of DDI as a common form for the "primary" data, a **DDI expression of a paradata model** is both appropriate and very desirable for structuring, accessing and using paradata.
## next steps for this group

We are currently considering three papers to start the discussion
(all working titles):

- Leveraging paradata from capture to analysis (in preparation)

- Formalizing paradata as a standard (only title, no content)

- Paradata, the DDI view (only title, no content)
## next steps for this group

Furthermore, we are waiting for the new scientific board to start operating. We are considering to apply to become a new official working group about paradata.

If you are interested in joining, please contact David Schiller

[david.schiller@fhgr.ch](mailto:david.schiller@fhgr.ch)
Thank you!