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Unfolding frictions in database projects

Processus frictionnels de mises en bases de données
Procesos friccionales de puesta en bases de datos
Florian Jaton et Dominique Vinck
Cet article est une traduction de :
Processus frictionnels de mises en bases de données [fr]
Autre(s) traduction(s) de cet article :
Procesos friccionales de puesta en bases de datos [es]


L’article rend compte des études sociales sur les bases de données en sciences humaines et sociales qui rejoignent les études sur les infrastructures de la recherche. Malgré des différences théoriques notoires entre ces études, quatre grandes directions d’analyse sont mises en évidence. Il se penche ensuite sur trois problématiques que posent le cas des bases de données pour la recherche et celui des collections de données numériques en SHS avant d’attirer l’attention sur les frictions qui surgissent lors de processus de mise en base de données.

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The Dead Sea Scrolls on the doorstep of a new database

The Dead Sea Scrolls were discovered throughout the 1950s in caves of the area of Qumran, West Bank. Today they constitute a corpus of about 950 manuscripts, probably written between the end of the third century BCE and the middle of the first century CE. Their study gives us precious elements about the spiritual shifts of this period of Judaic transformations and early Christianity. The quality of the manuscripts varies considerably, going from well-preserved scrolls to tiny fragments consumed by fire and fungi. The collective, laborious and controversial decipherment of the manuscripts has driven digitization projects from as early as the 1960s. Today, the many digital systems available to explore and study the corpus include infrared luminescence technologies that reveal characters invisible to the naked eye, tools for textual segmentation and vocalization, integrated dictionaries that can access the “original” scanned texts in high-definition, and reconstitution tools for lost passages based on formal handwritten characteristics (outlines of characters, spacing deviation between words and characters, etc.). Google has also recently launched a re-digitization project of the corpus in ultra-high-definition in collaboration with the Israeli government. Many tools and systems for the analysis of this corpus –made famous through the popular novel The Da Vinci Code– coexist then in a quite competitive environment.
The project of David Hamidovic –a historian of antiquity– is in line with recent attempts to exploit the pixel properties of the scanned manuscripts. Yet, contrary to what has been already proposed, his ambition is to learn more about the important yet mysterious people who wrote these manuscripts: their scribes. His question is the following: what are the editorial projects inscribed within the manuscripts? The question is a legitimate one since at that time, scribes did not copy (monasteries are later historical formations): they tell, add, rearrange and modify according to different sensibilities and affects. If they did not radically transform the final messages of canonical texts, scribes often added or changed some elements of the stories. And since they had diverse sensibilities, backgrounds, and references, these scribes can be considered as expressers –and, to a certain extent, actors– of the spiritual shifts of this historical period. By collecting and comparing semantic and formal traces left behind by scribes (words, turns of phrase, curves of the characters, spacing between words), it surely is possible to build profiles of scribes with diverse interests and editorial projects. And today, this could be done with statistical rigor via the creation of a database with structuration and content that could support the definition and training of more or less supervised machine-learning algorithms.
Yet, from this point, the questions that arise immediately concern the protocol required in order to shape this database. Since the manuscripts are quite renowned, it is not difficult to raise the interest of computer science laboratories specialized in the automated processing of hand-written characters. But the development of machine-learning models necessitates heavy preparatory work: how could a historian of antiquity foresee the irreversible consequences of the computational propositions he is being proposed? How can he even understand these propositions? And similarly, how could computer scientists foresee the potential dangers of their database model for the practice of history? How do they start the construction of the preparatory database of digital characters without making important mistakes that are too expansive to correct for both parties? In sum, how do they start such an interdisciplinary project in the best possible way for both the history of antiquity and two-dimensional digital signal processing?

  • 1 Cf. the review of Understanding Research Infrastructures in the Social Sciences (Kleiner et al., 20 (...)

1Many database projects are under way in the human and social sciences (HSS). From small PhD projects to big national infrastructures, an increasing amount of researchers in HSS endeavor to collect, select, and organize digital data, with the help of computer scientists, in order to make them queryable, shareable, and eventually augmentable (Magnien & Vinck, to be published). Moreover, after a two-year research seminar where colleagues were invited to discuss problems related to their database projects, it appeared to us that most of these projects were sources of controversies and disputes. Science and human frictions (Edwards et al., 2011) seem to emanate from these projects, notably questions about the status of HSS in the academic landscape, the adequacy of digital tools for research, and the credibility and utility of HSS for the collective world. Often involuntarily, humanists and social scientists engaged in such projects also carry visions for their disciplines and become controversial prescribers of good practices and technical solutions.1 During these work situations, real trials (Boltanski and Thévenot, 2001) take place with results that tend to set up irreversibility consequences.

  • 2 Lemieux (2007) distinguishes between two ways to consider controversies: a “classical way” that con (...)
  • 3 See for example Currie (2012), Heftberger (2012) and Kirschenbaum (2007).

2Yet, even though trials and controversies are now common sociological starting points (Akrich et al., 2006; Boltanski & Thévenot, 1991),2 very few studies have inquired into these hectic projects. Despite their noisy aspects and relatively easy access –often the department next door, or even one’s own lab!– that make them ideal environments for sociological explorations, very few serious attempts have been made to account for these projects. Some researchers have published their reflections but they mainly constitute prescriptive positions about scientific uses of digital technologies.3 The recent popularity of social studies of digital databases (cf. below) makes the story even more surprising: even though heuristic controversial processes engaging digital technologies and the production of knowledge in HSS are happening next door, most inquiries seem to focus on other disciplines.

3By diving into the shaping of digital databases in HSS, this special issue tries to better understand what is going on in and through these conflicting situations. By focusing on frictional moments (Edwards et al., 2011), each contribution participates in documenting the mode of the existence (Latour, 2012) of digital databases as well as the dynamics of knowledge infrastructures (Karasti et al., 2016a, 2016b) for HSS. As we shall see, these contributions reveal new injunctions, competences and articulations that surely deserve greater attention.

Social studies of databases

4Social studies of databases are not in their infancy, even though they do not constitute a unified sociological tradition. According to us, four major research directions can be listed.

5The first research direction is sociohistorical and is the result of recent efforts made by the Annals of the History of Computing (Grad & Bergin, 2009; Grad, 2012, 2013). Quite ignored in the French-speaking academic landscape, these works have brought into light the sociogenesis of the term “database” (Haigh, 2009) as well as its attachments to administrative, military and managerial communities (Bergin & Haigh, 2009; Haigh, 2011; Grier, 2012; Wade & Chamberlin, 2012; Haderle & Saracco, 2013). If digital databases often appear as confident extensions of digital data collections, these sociohistorical inquiries have documented their fragile beginnings and their progressive associations with technologies that today appear ubiquitous (relational models, SQL language, theoretical distinction between “data” and “views,” etc.).

6The second research direction analyzes the effects digital databases have on society. Drawing upon surveillance studies, they tend to denounce the subjection power of databases (Lyon, 2003) and their ability to produce restrictive categories (Porter, 1995; Atten, 2013). If this reading of databases tends to decry the asymmetry between those who design databases (private companies, administrations) and those who endure them, actors are not always considered as passive agents and do sometimes manage to reconfigure them through unexpected interactions and uses (Flichy, 2013). This emphasis on the effects of databases also encapsulates symbolic and cultural interpretations (Manovich, 1999, 2012) where digital databases are considered as new media reflecting today’s society. This interpretation in terms of mediology puts the emphasis on the new potentials for action inscribe within digital databases.

7A third research direction –mainly initiated by science and technology studies (STS)– puts the emphasis on the shaping processes of digital databases. Yates (2005), Segresting (2004), Gardey (2008) and Vinck & Penz (2008) have shown that the initial desires that trigger database projects are radically transformed once confronted with construction issues, hence creating new arrangements. Similarly, other studies have explored the shifts between initial goals and effective uses. Ugettho (2013) shows for example that intertwined co-construction mechanisms easily widen the gap between imagined and effective uses of digital databases. Discussions, disagreements and many unexpected events transform the architectures and functionalities of databases that sometimes end up expressing something very different from their designers’ initial plans. Moreover, Dagiral and Peerbaye (2013) show how a digital database initially designed to share information is confronted with equivocal interpretations of this information. This leads to struggles among users and designers to establish a “standardized” interpretation of the shared information. According to this research direction, it is then difficult to infer anything from the effects of databases; one should rather document the performativity of their collective construction processes.

8A fourth direction of analysis –close to the third one– considers databases as part of broader categorization and classification processes. Porter (1995) for example inquires into the social, political and economic dynamics that shaped the categories of an American administrative database. He shows how private companies, competing administrations, federal agencies, social scientists, programmers and computer scientists more or less successfully influenced the definition of the categories to their advantages. In the same vein, the work of Susan Leigh Star and Goeffrey C. Bowker (2000) shows that classification practices required by databases go along with invisibilization processes; the collection and structuration of data also implies more or less harmful exclusions and muting (Star, 1989; Bowker, 2000). Using the example of a digital repository for cycle lanes, Denis and Pontille (2013) further show how collection practices imply binding choices as well as specific competences. In their work on research infrastructures for biodiversity, Granjou et al. (2014) describe how the structuration of contents requires new collaborations and management systems that tend to transform taxonomists into “data providers.” In the same vein, Dagiral and Peerbay (2016) show how the feeding, maintenance and use of a research database on rare diseases include a surprising duality: for the actors involved, this knowledge infrastructure (Karasti et al., 2016a, 2016b) is stable and representative of rare diseases but also and at the same time problematic and potentially useful for further (re)negotiations. The invisibilization practices that go along with digital databases seem then to be coupled with systematic infrastructural inversion practices (Bowker, 1994) that are potential resources for the actors in situation, and not only researchers in social sciences.

9As different and interesting as they are, these studies have in common that they largely ignore the relationships between digital databases and HSS and the mutations they may provoke. Indeed, notably through the rise of digital humanities (Magnien & Vinck, to be published), more and more funding for innovative projects that gather practitioners of HSS –historians, philosophers, psychologists, sociologists– and of computer science and technologies (CST) –data scientists, GUI designers, programmers, system architects– are allocated; what happens when these actors work together in order to design a database? How do (dis)agreements and compromises arise? What paths do collective practices of data structuration take? As we shall see in this special issue, compromises are instituted, attempts are made to put arrangements in place and new entities appear. Through the constitution of digital databases in HSS, a specific research environment is expressed possessing an ecology that may deserve greater consideration.

Databases in the sciences and humanities

10For sure, databases are important entities for scientists: it is difficult indeed to imagine the practice of science without any analogical or digital device for data storage and retrieval (Bowker, 2008). According to Latour (1989), scientific activity necessitates the stabilization of resources and constants in order to produce traces and inscriptions; it is only through laborious compilations of documents that more or less controversial chains of reference (Latour, 2012) can be put in place. But traces, alignments, synthetizations and compilations also imply storage, exchanges and standards: the extension of a knowledge network requires equipment (Vinck, 1999, 2011) in order to make traces of events commensurable. Even before the rise of digital technologies, the constitution of data collections that could support specific requests and comparisons seems then coextensive to the scientific activity (Desrosières, 2008).

11The dynamics related to the constitution of databases in the “hard” sciences are pretty well documented (Hilgarter, 1995, 2012; MacKenzie, 2003; Beaulieu, 2004; Bowker, 2000, 2005; Hine, 2006; Heaton & Proulx, 2012; Edwards, 2013; Meyer & Schroeder, 2015). Bruno Strasser (2011) shows, for example, that the rise of digital storage and compilation has partially transformed the field of genomics. Indeed, because of the growing emphasis on the collection, storage and sharing of data, this science that used to be presented as mainly experimental looks more and more like “natural sciences,” older and often less valorized. Notably because of the rise of digital technologies and the setting up of enormous databases (big data), practitioners of genomics collect, sort, standardize and share data more than they organize “classical” analogical laboratory experiments. A different way to conceive and present genomics is shaped through the potentialities of digital databases and this, of course, causes resistances and transformations. But what about HSS? How do digital databases transform their practices? Despite the importance of the topic, very few studies have been conducted (Vinck, 2016).

Digital data collection in the human and social sciences

  • 4 Some European examples among many, the “Consortiums Eurpéens d’Infrastructures de Recherche” (ERIC) (...)

12Databases are also important in HSS. From small individual projects to big institutional strategies requiring costly technological infrastructures,4 databases in HSS have histories that would be, according to us, important to unfold. We think, for example, about the constitution of private archives during the 1940s in the United States for the study of public opinion, the development of quantification in HSS (notably in linguistics, history and sociology), the constitution of national statistic resources and thesauri, and the recent development of digital humanities and their relationships with the notion of big data; all these topics are ultimately linked with the design of databases. The structuration and sharing of data are also related to methodological issues about protocols, comparability, interoperability and quality control. Performative definitions of equivalence between objects, people, relationships, and events (Desrosières, 2008) required by quantitative analysis are also an issue: choices related to data structure within databases can produce very tangible effects, for example when HSS propositions are included in the design of policies. More inquiries into digital databases in HSS could help better understand these socio-technical processes that take part in the shaping of the collective world.

13The constitution of databases in HSS also implies best practices and international norms –such as the Data Documentation Initiative (DDI) and the International Standard Archival Description (ISAD)– for the collection, preparation, harmonization and cleaning of data as well as the documentation of their conditions of production and indexation (Beltrame & Jungen, 2013).

  • 5 See the special issue on this topic in the Revue d’anthropologie des connaissances – Denis and Pont (...)

14Yet, even though these practices are highly problematic, the success of databases in HSS seems also to rely upon their invisibilization5 since the users-researchers do not necessarily want to bother with conception, maintenance, or security issues. To a certain extent, the utility of databases in HSS seems to be also a function of their ability to be put into black boxes.

15This tension between obvious issues and necessary blinders works to produce misunderstanding with CST specialists concerning both the conception and the utilization of databases in HSS. Whatever one might say, in-depth collective discussions upstream of the construction of databases remain badly equipped. The contracted computer scientist is often tasked with choosing the database management system, even though it may quickly create irreversible consequences or may not guarantee any sustainability.

Some issues related to digital data collections in HSS

16Pressures for results certainly contribute to the under-exploration of issues and tensions that arise during the conception and management of databases in HSS; for obvious reasons, researchers tend to privilege demos and publications in ranked journals over in-depth reflections about their own practices. Yet we do think that these projects are perfect situations for learning more about our disciplines: by documenting what is going on during these eventful work situations, one may produce refreshing knowledge about research practices in HSS when dealing with digital data collections. An unpublished preliminary inquiry conducted by Pierre-Nicolas Oberhauser has stressed some of these issues that will be further explored by the contributions of this special issue.

Issues related to the duplication and sharing of digital data

17When data were confined in binders and cardboard files, researchers in HSS had to produce very tangible efforts in order to share them with their colleagues. Once digitally translated, data seem more easily duplicable and the efforts required to share them seem to diminish: other entities –operating systems, data transmission protocols, systems architects– are in fact taking over, hence diminishing the costs of circulation, at least from the point of view of the researchers. Data then seem more sharable and better suited for distributed projects.

18These seemingly intrinsic sharing capabilities of digital data do not only intervene downstream of their production: they also intervene upstream, when they are shaped with the help of digital tools. Hence the apparition of other issues notably related to their property: who owns digital data? Those who own the servers that store them? The managers of the research projects? Those who equipped them in order to make them able to circulate within communication networks? This further indicates issues related to the equipment of data –data are never sharable by themselves but always by others: who are those who work in order to make them suitable for digital networks? Are they not often subordinated employees doing repetitive tasks that may deserve greater consideration?

Issues related to the collectivization of scientific work

19The collectivization of scientific work suggested by the sharing capabilities of digital data further creates organizational issues. The first one is related to a bootstrapping problem (Bowker et al., 2010). Indeed, in order to be considered as trustworthy, one set of data on a specific topic often needs to be crosschecked with another set of data produced by other researchers on the same topic. From this point, the collectivization of scientific work induced by digitization further induces the definition of valuable topics capable of bridging diverse preoccupations. These “boundary-objects” are of course problematic precisely because of their power of attraction: how are they constituted and how can we eventually make them shift (Star & Griesemer, 1989; Star, 2010)?

20A second issue related to the collectivization of scientific work is related to the standardization of data and the definition of formatting rules: how are they produced? And how do researchers in HSS enact them?

Quality issues

21Once produced –that is shaped, organized and equipped so that they can be shared and queried– data are often submitted to epistemological proofs that test their robustness (what was the data collection protocol? what references were used for the conceptualization of the research? etc.). But equally important are the technical proofs that test the ability of data to suit the practical and changing needs of researchers (are the data in a standardized format? could they be merged with another dataset without compatibility problems? etc.). Robustness of the data and flexibility of the collection: a subtle articulation between these two attributes seems to define a good digital data collection for HSS. Yet are these criteria always considered evenly?

Frictions that “make do”

22More than analyzing the effects digital databases have on HSS, this special issue tries to document the transformative relationships that pop up during the construction of digital databases: what do these processes make us do? Over the active voice of control and the passive voice of domination, this special issue privileges the middle voice of the making do (Latour, 2000). What do the sparks of trials (Akrich, Callon, & Latour, 2006 ; Boltanski & Thévenot, 1991) and frictions (Edwards et al., 2011) draw when digital databases are being designed for HSS?

23Each of the contributions answers this question in its own way. For Gilles Bastin and Jean-Marc Francony, who try to transform inscriptions stored in the Web servers of LinkedIn into data capable of being sociologically queried, the unfolding of frictions reveal a need of visibilization: the transformation process that makes Web inscriptions become sociological data “wakes up” unexpected actors whose views need to be taken into account. The design of their database is then coupled with inquiries into these contradictory views in order to become capable of composing with them. In short, rather than muting discordant views and interests, the construction of their database requires their expressions and considerations.

24Sophie Duchesne and Mathieu Brugidou analyze the constitution of a database for French-speaking qualitative inquiries. By exploring the numerous frictions of this project, they make appear a continuous need of simulation: throughout its progress, the project never stops asking its participants to foresee—and eventually confront –what it could later enable, the difficulty being precisely the variability of these projections through time. The more entities are included into the project –funding, people, institutions– the more difficult it becomes for those involved to confront their visions and even more to conciliate them.

25Finally, by finely exploring the interactions between actors conducting a database project in psychology, Pierre-Nicolas Oberhauser documents the competences that need to be constructed –almost on the fly!– in order to provoke relationships between domains of expertise. The frictions of a database project are therefore not given: the actors need to develop situational competences in order to eventually make them appear.

26These three contributions unfold the frictions of database projects in HSS in quite different ways: are they commensurable enough to support a broader proposition that would merge them? It is, of course, up to the readers to decide. Yet, at least according to us, these contributions do not only explore situations that were previously poorly documented; they also help digital databases to become more familiar by attributing to them composition, simulation and competences desires. These conceptual supports may engage new inquiries but they may also help the pursuit of new interdisciplinary database projects.

The publication of this special report was supported by the Fonds des publications of the University of Lausanne (Unil).
We would like to thank the participants of the LaDHUL (Laboratory of Digital Humanities of the University of Lausanne) workshop on databases held in October 2015 as well as the institutions that supported it, in particular the Institute of Social Sciences of the University of Lausanne. We are also very grateful to Marc Barbier who followed up this special issue with great care on behalf of the
RAC Editorial Board.

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1 Cf. the review of Understanding Research Infrastructures in the Social Sciences (Kleiner et al., 2013) by Vinck (2013). The studies on Big Science and its particle accelerators (Simoulin, 2007; Boisot et al., 2011), radio telescopes, nanotechnology platforms (Merz & Biniok, 2010; Hubert, 2013) and on genomics (Peerbaye, 2004), scientific cooperation networks (Vinck, 1999, 2012) and natural histories (Bowker & Star, 1999; Bowker, 2005) have not inspired similar studies on HSS.

2 Lemieux (2007) distinguishes between two ways to consider controversies: a “classical way” that considers them as revealers of previous sociological positions and a “science studies way” that consider them as performative processes that establish new entities.

3 See for example Currie (2012), Heftberger (2012) and Kirschenbaum (2007).

4 Some European examples among many, the “Consortiums Eurpéens d’Infrastructures de Recherche” (ERIC), the “Conseil Européen pour l’Archivage des Données en Sciences Sociales,” the International Federation of Data Organisations (IFDO) and, in France, the infrastructure “Huma-Num” to support research in the humanities and social sciences.

5 See the special issue on this topic in the Revue d’anthropologie des connaissances – Denis and Pontille (2012), especially the paper of Millerand (2012).

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Florian Jaton et Dominique Vinck, « Unfolding frictions in database projects »Revue d’anthropologie des connaissances [En ligne], 10-4 | 2016, mis en ligne le 01 décembre 2016, consulté le 08 juin 2023. URL : ; DOI :

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Florian Jaton

PhD student in social study of science and technology at the University of Lausanne, he is part of the Institute of Social Sciences, the STS Lab and the Laboratory of Digital Humanities of the University of Lausanne (LaDHUL). He is currently doing a research stay at the University of California at Irvine, in the EVOKE laboratory. His thesis is an ethnographic account of a computer science laboratory specialized in digital signal processing. This laboratory study deals more specifically with referential repositories for algorithmic procedures, programming practices and the shaping of mathematical models.

Address: Université de Lausanne (UNIL), Institut des Sciences Sociales, Quartier Mouline– Géopolis, CH-1015 Lausanne (Suisse).
E-mail: florian.jaton[at], fjaton[at]

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Dominique Vinck

Full Professor at the University of Lausanne (UNIL) and teaches at the College of Humanities at the Swiss Federal Institute of Technology in Lausanne (EPFL), he is member of the Social Sciences Institute and STS Lab of the UNIL and director of the Laboratory of Digital Humanities of the University of Lausanne (LaDHUL). His research interests are in the sociology of science and innovation and the engineering of digital humanities and cultures. His publications include Pratiques de l’interdisciplinarité (PUG, 2000), Everyday Engineering. An Ethnography of Design and Innovation (MIT Press, 2003), The Sociology of Scientific Work (Edward Elgar, 2010), L’équipement de l’organisation industrielle. Les ERP à l’usage (Hermes, 2008), Les nanotechnologies (Le Cavalier Bleu, 2009), Comment les acteurs s’arrangent avec l’incertitude (EAC, 2009), Les Masques de la convergence (EAC, 2012), Ingénieur aujourd’hui (PPUR, 2015), Sciences et technologies émergentes : pourquoi tant de promesses ? (Hermann, 2015), Humanités numériques : la culture face aux nouvelles technologies (Le Cavalier Bleu, 2016).

Address: Université de Lausanne (UNIL), Institut des Sciences Sociales, Quartier Mouline– Géopolis, CH-1015 Lausanne (Suisse).
E-mail: dominique.vinck[at]

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