# Providing Data in a User-Friendly Manner at the Center for Socio-Political Data Paris

Alina Danciu, Alexandre Mairot

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Alina Danciu, Alexandre Mairot. Providing Data in a User-Friendly Manner at the Center for Socio-Political Data Paris. 10th Annual European DDI User Conference (EDDI18), Dec 2018, Berlin, Germany. hal-02874091

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Submitted on 3 Jan 2023

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Distributed under a Creative Commons Attribution 4.0 International License
# Providing Data in a User-Friendly Manner
at the Center for Socio-Political Data Paris

EDDI18 – 10th Annual European DDI User Conference,
December, 4 2018, Berlin

Alina Danciu, Alexandre Mairot
“Documents are malleable, mutable,
and mobile”*

“Data are even more malleable, mutable,
and mobile than documents.”**

* LATOUR Bruno, *Sciences in Action: How to Follow Scientists and Engineers through Society*, Cambridge, Harvard University Press

** WALLIS Jillian, ROLANDO Elizabeth and BORGMAN Christine (2013), “If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology”, PLoS One, vol. 8, n° 7 (DOI:10.1371/journal.pone.0067332)
# Making data discoverable and reusable*

* Data tend to exist in **small units**, are **linked** to many other related units,

* They are **context-dependent**: difficult to interpret without considerable documentation and context,

* **“Big science”** (large teams, long-term projects, extensive instrumentation): great in volume and consistent in structure,

* **“Small science”** (individual or small teams, data collected for specific projects): small in volume, local in character, intended for use only by these teams, and are less likely to be structured in ways that allow data to be transferred easily between teams or individuals,

* **Making data from the long tail discoverable and reusable is emerging as a major challenge.**

* WALLIS Jillian, ROLANDO Elizabeth and BORGMAN Christine (2013), “If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology”, PLoS One, vol. 8, n° 7 (DOI:10.1371/journal.pone.0067332)
Data archives: putting the pieces together

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# Meaningful metadata

* Defining rules and procedures internally

* DDI Controlled Vocabularies Group (DDI-CVG)

* CESSDA recommendations (ex: testing CESSDA Metadata Portfolio)
# One variable, One documentation, Multiple datasets

Dataset: Enquête annuelle - vague 5 (2017)

EA, ELIPSS Mars 2017

Dataset: Dynamiques de mobilisation - vague 18 (2017)

DYNAMOB - vague 18, ELIPSS Décembre 2017

## Variable ea17_E1A: Personnes dans le ménage percevant : salaires, traitements et primes

## Variable ea17_E1A: Personnes dans le ménage percevant : salaires, traitements et primes

### PREQUESTION TEXT

Les questions qui suivent portent sur vos revenus et les prestations sociales que vous touchez éventuellement. Elles sont détaillées afin d'établir une estimation de votre niveau de vie et celui de votre ménage.

### PREQUESTION TEXT

Les questions qui suivent portent sur vos revenus et les prestations sociales que vous touchez éventuellement. Elles sont détaillées afin d'établir une estimation de votre niveau de vie et celui de votre ménage.

### LITERAL QUESTION

Y a-t-il actuellement dans votre ménage (y compris vous-même), une ou plusieurs personnes qui perçoit(ven)t les ressources suivantes: - salaires, traitements et primes

### LITERAL QUESTION

Y a-t-il actuellement dans votre ménage (y compris vous-même), une ou plusieurs personnes qui perçoit(ven)t les ressources suivantes: - salaires, traitements et primes

<table><thead><tr><th>Values</th><th>Categories</th><th>N</th></tr></thead><tbody><tr><td>1</td><td>Oui</td><td>1760</td></tr><tr><td>2</td><td>Non</td><td>891</td></tr><tr><td>3</td><td>Je ne sais pas</td><td>74</td></tr></tbody></table>

<table><thead><tr><th>Values</th><th>Categories</th><th>N</th></tr></thead><tbody><tr><td>1</td><td>Oui</td><td>1447</td></tr><tr><td>2</td><td>Non</td><td>755</td></tr><tr><td>3</td><td>Je ne sais pas</td><td>57</td></tr><tr><td>96</td><td>Non enquêté</td><td>67</td></tr></tbody></table>

### SUMMARY STATISTICS

Valid cases 2725
Missing cases 0
This variable is numeric

### SUMMARY STATISTICS

Valid cases 2259
Missing cases 67
This variable is numeric

### NOTES

Batterie de questions dans le questionnaire E1 (Y-a-t-il actuellement dans votre ménage (y compris vous), une ou plusieurs personnes qui perçoit(ven)t les ressources suivantes ?), comprenant plusieurs sous-questions divisées dans la base en différentes variables (E1A à E1J)

### NOTES

Batterie de questions dans le questionnaire E1 (Y-a-t-il actuellement dans votre ménage (y compris vous), une ou plusieurs personnes qui perçoit(ven)t les ressources suivantes ?), comprenant plusieurs sous-questions divisées dans la base en différentes variables (E1A à E1J)
# Metadata variables standardisation

## UNIVERSE:

*Model*: "If interviewer" + [LITTERAL CONDITION] + "(meaning (" + [ALGORITHMIC CONDITION] + ") )"

Si l'intervieweur est inscrit sur les listes électorales (c'est-à-dire (INSCRIPTION in 1:2))

Si l'intervieweur apporte une aide à domicile à un tiers (c'est-à-dire (Q1A==1))

## NOTES:

*Model*: "Grid question in the questionnaire" + [GRID QUESTION NAME] + ", meaning several sub-questions divided in the base in different variables (" + [VARIABLE1] + "to" + [VARIABLE2] + ")."

Batterie de questions dans le questionnaire RAD_STAT, comprenant plusieurs sous-question divisées dans la base en différentes variables (RAD_STAT1 à RAD_STAT23).

Batterie de questions dans le questionnaire MUS_GENR, comprenant plusieurs sous-questions divisées dans la base en différentes variables (MUS_GENR1 à MUS_GENR13).
dataKind: Kind of Data

<table><thead><tr><th>DDI Alliance example*</th><th>fr.cdsp.ddi.AGORA1978</th><th>fr.cdsp.ddi.elipss.2013.04.ea</th><th>fr.cdsp.ddi.PostElect1997</th></tr></thead><tbody><tr><td>survey data</td><td>Individual survey data</td><td>Data from individual surveys and geographical data taken from the census.</td><td>survey data</td></tr></tbody></table>

<footnote>* http://www.ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/field_level_documentation.html</footnote>
collSitu: Characteristics of Data Collection Situation

<table><thead><tr><td>DDI Alliance example*</td><td>fr.cdsp.ddi.elipss.2012.12.pn</td><td>fr.cdsp.ddi.FES2007</td><td>fr.cdsp.ddi.LMSEP1986</td></tr></thead><tbody><tr><td>There were 1,194 respondents who answered questions in face-to-face interviews lasting approximately 75 minutes each.</td><td>Estimated time to complete questionnaire: 15 minutes. Panellists who had begun the questionnaire before the end of the main fieldwork were able to access and complete it up to 31 May 2014.</td><td>The total number of households in the sample is 10,469, with 5849 valid households, making a total of 2000 interviews.</td><td>Since the questionnaires were self-administered and in paper format, it is difficult to assess how fully they were completed. It is therefore not possible to distinguish between real non-responses, individuals for whom a question was “not applicable” (i.e. filtered by a previous question) or anomalous values. In this survey, all these situations are treated as non-responses (coded 0).</td></tr></tbody></table>

<footnote>* http://www.ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/field_level_documentation.html</footnote>
## resInstru: Type of Research Instrument

<table><thead><tr><td>DDI Alliance example*</td><td>fr.cdsp.ddi.AGORA1981</td><td>fr.cdsp.ddi.elipss.2014.02.soligene</td><td>fr.cdsp.ddi.elipss.2014.12.ess</td></tr></thead><tbody><tr><td>structured</td><td>A large part of the questionnaire consists of closed questions.</td><td>Questionnaire consisting of closed questions.<br/>Methodological and technical specificities:<br/>Presentation of some questions in the form of scenarios.<br/>Random rotation of items in certain batteries of questions.<br/>Randomisation in the order of two blocks in the questionnaire (family mutual aid and role-playing).</td><td>The questionnaire consists of closed questions and a few open questions.</td></tr></tbody></table>

<footnote>* http://www.ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/field_level_documentation.html</footnote>
timeMeth: Time Method

<table><thead><tr><th>DDI Alliance example*</th><th>fr.cdsp.ddi.AGORA1986</th><th>fr.cdsp.ddi.BPF2007-R4</th><th>fr.cdsp.ddi.elipss.2013.07.fecond</th></tr></thead><tbody><tr><td>panel survey<br/>cross-section<br/>trend study<br/>time-series</td><td>The Agoramétrie surveys were<br/>conducted annually from 1977 to<br/>2005.</td><td>4 survey waves<br/>4th wave: February 5-19, 2007</td><td>The questionnaire consists of closed<br/>questions and a few open questions.</td></tr></tbody></table>

<footnote>* http://www.ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/field_level_documentation.html</footnote>
weight: Weighting

<table><thead><tr><th>DDI Alliance example*</th><th>fr.cdsp.ddi.AGORA1982</th><th>fr.cdsp.ddi.elipss.2014.05.dynamob</th><th>fr.cdsp.ddi.PostElec2012</th></tr></thead><tbody><tr><td>The 1996 NES dataset includes two final person-level analysis weights which incorporate sampling, nonresponse, and post-stratification factors. One weight (variable #4) is for longitudinal micro-level analysis using the 1996 NES Panel. The other weight (variable #3) is for analysis of the 1996 NES combined sample (Panel component cases plus Cross-section supplement cases). In addition, a Time Series Weight (variable #5) which corrects for Panel attrition was constructed. This weight should be used in analyses which compare the 1996 NES to earlier unweighted National Election Study data collections</td><td>The data from surveys conducted by Agoramétrie are not weighted.</td><td>The sampling procedure for the pilot survey had underestimated the impact that the small sample size and the process for selecting the primary units could have on the weight spread. To limit this spread, it was proposed that a uniform sampling weight should be set for the whole sample. The individual weightings were adjusted for nonresponse by the homogeneous response groups method, then by an adjustment on five criteria in the 2014 Annual Census Survey (sex, age, nationality, qualification and ZEAT (study and development zone)).<br>The weightings of the survey respondents alone are adjusted once again on the same criteria to correct for nonresponse in the survey wave. Together, they add up to the size of the respondent sample.<br>The weighting documentation gives more details on the adjustment procedure and the use of weightings.</td><td>The weighting was calculated on the criteria of sex, age, socio-professional category of the reference person, region, conurbation size, official results of the 1st and 2nd rounds of the 2012 presidential election, and educational qualifications.<br>Four weighting variables are available:<br>Weight0: Adjustment for sociodemographic criteria: Sex, age, occupation of household head, Region, category of municipality.<br>Weight1: Weight0 adjustment + vote in 1st round of 2012 presidential election.<br>Weight2: Weight1 adjustment + vote in 2nd round of the 2012 presidential election.<br>Weight3: Weight2 adjustment + educational qualification.<br>They are described in the following document:</td></tr></tbody></table>

<footnote>* http://www.ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/field_level_documentation.html</footnote>
# DDI3 principles in a DDI2 environment*

<table><thead><tr><td>DDI3 Principles</td><td>How we manage in DDI2</td></tr></thead><tbody><tr><td>All Identifiable Objects have an object source attribute that can contain a DDI URN.</td><td>Link between documentation source and documentation target</td></tr><tr><td>Description of the source of the data.</td><td>Documentation all the sources of data beyond the using for the documentation with the DDI2 structure.</td></tr><tr><td>Identification of the versions</td><td>Versionning documentation file and data file</td></tr><tr><td>Lifecycle pulls out the various bits so that you can manage and control them better</td><td>Standardisation universe, notes across the dataset (next step at the level collection)</td></tr></tbody></table>

<footnote>* JOHNSON Jon, SMITH Dan, THOMAS Wendy, WACKEROW Joachim (2018), Workshop: “Data Documentation Initiative (DDI) – Train the Trainers”, Dagstuhl, 23rd-28th September (https://www.dagstuhl.de/18393)</footnote>
## DDI3 principles in a DDI2 environment*

<table><thead><tr><td>DDI3 Principles</td><td>How we manage in DDI2</td></tr></thead><tbody><tr><td>Allows reuse of question</td><td>Standardisation variable labels across the collection of dataset</td></tr><tr><td>Reuse and metadata</td><td>Routine to reuse documentation for producing XML Files</td></tr><tr><td>Separates question content from the use of the question</td><td>Quetelet Questions bank</td></tr><tr><td>Captures assembly into a questionnaire (question flow, instructions, informational text)</td><td>Documentation of the “Interviews instructions”, universe, prequestion and describe in the notes tags all the context of the question</td></tr><tr><td>Tracks the flow of data and deposits it into a variable</td><td>Documentation of the formula in separated field</td></tr></tbody></table>

<footnote>* JOHNSON Jon, SMITH Dan, THOMAS Wendy, WACKEROW Joachim (2018), Workshop: “Data Documentation Initiative (DDI) – Train the Trainers”, Dagstuhl, 23rd-28th September (https://www.dagstuhl.de/18393)</footnote>
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# Translating metadata to improve discoverability

* ⅓ of our data users prefer English as a working language

* Bilingual study metadata-level (work in progress)

* Users can identify easier relevant surveys for their research

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How about accessibility?

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alina.danciu@sciencespo.fr

alexandre.mairot@sciencespo.fr

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