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Moving Data Into and Out of an Institutional Repository: Off the Map and Into the Territory

The objective of this paper is to attempt to move beyond the impasse of ethical objections to reusing qualitative data. In doing so, there is no intention of dismissing the importance of ethical debates, in fact, quite the opposite. The debate about ethical reuse needs to be deepened and broadened. First, the current terrain of research ethics will be summarised and situated in the context of broader philosophical ethical frameworks. In contrast, the debates around ethics of archiving have often been narrowly focused on participants' rights. The framework of debate should be broadened first by recognising other entities traditionally deemed within the scope of research ethics, namely the scholarly community and the public. The second useful broadening of the framework is provided by a deontological ethical stance with its focus on duties. In the final section, this expanded framework will be used to rebut several common ethical arguments against archiving qualitative data: archiving violates confidentiality; informed consent for reusing data is impossible; reusing data violates trust between researcher and participant; and, archiving creates an unacceptably high risk of data misrepresentation. If a more general philosophical debate on ethics has something to contribute, the central message must be that no single ethical claim is incontestable. The conclusion will position these debates in a wider context by asking what is at stake when the boundaries of ethical discourse about sharing data are drawn too narrowly.

Though secondary analysis of qualitative data is becoming more prevalent, relatively few methodological studies exist that provide reflection on the actual, not idealised, process. This paper offers a reflexive account of secondary analysis focused on the topic of convenience food and choice. Several phases of the research process are examined: understanding context, defining a subject area, finding data and sampling, later sampling and topic refinement, and relating to transcripts. For each phase, I explore if reusing data is different from using it in the first instance, and if so, how those differences manifest themselves. The paper closes with reflections on the differences, similarities, and relationships between primary and secondary analysis of qualitative data. Although differences exist regarding the researcher-respondent relationship, primary and secondary analyses are more alike than not. The suitability of each approach can only be assessed in light of a particular research question.

ESRC funding for the Timescapes initiative included provision for the creation of a specialist resource of Qualitative Longitudinal (QL) data for sharing and re-use. In this article we document the development of this resource, focusing on the strategic and practical dimensions of its growth. In the process we explore the importance of effective communication and negotiation in the development of stakeholder collaborations between researchers and archivists. We reveal the potential of the archive to operate at the intersection of primary and secondary research, acting as a useful repository for the data of primary researchers to aid temporal QL analysis, and bringing related datasets together for enhanced analysis by both primary and secondary users.

Qualitative and Qualitative Longitudinal Resources in Europe

Sharing Qualitative and Qualitative Longitudinal Data in the UK

Anders als im Falle quantitativer Verfahren gibt es fast keine Literatur zur Sekundäranalyse qualitativer Daten. In der qualitativen Sozialforschung existiert weder eine etablierte Kultur, die die Durchführung von Sekundäranalysen ermutigt, noch findet sich ein ausreichender Korpus an Literatur, der interessierten Forschenden helfen könnte, die Vorteile und Probleme, die mir der Sekundäranalyse von Daten verbunden sind, hinreichend zu verstehen. Wohin sollen sich also Studierende und junge Forscherinnen und Forscher mit ihrem Wunsch nach Unterstützung und Training wenden? In diesem Beitrag zeigen wir, wie ESDS Qualidata versucht, sowohl die Nutzung von archivierten Daten als auch methodologische Debatten einer breiteren Fachöffentlichkeit nahezubringen. Wir präsentieren dafür einen Überblick über die vorhandene Literatur und über existierende Schulungsmaßnahmen zur Sekundäranalyse qualitativer Daten und beschreiben verschiedene Ansätze, die bei uns für den Support und für Schulungen zum Einsatz kommen. Abschließend befassen wir uns mit dem Erstellen von Lehrmaterial (Datensätze, Nutzungsanleitungen, Kommentare und Übungen), das Lehrenden und Lernenden helfen soll, sekundäranalytische Verfahren in ihre tägliche Forschungspraxis und -kultur einzubeziehen.

Archivierte qualitative Daten beinhalten einen reichen und einzigartigen, aber oft ungenutzten Fundus an Forschungsmaterial, das reanalysiert, neu bearbeitet und mit aktuellen Daten verglichen werden kann. Diese FQS-Schwerpunktausgabe möchte einen Beitrag zur Diskussion methodologischer, ethischer und theoretischer Aspekte der Sekundärnutzung qualitativer Daten liefern und einige Anwendungen der Methode vorführen. Viele Arbeiten präsentieren Fallstudien, die sich auf die Wiederverwendung qualitativer Daten stützen, während andere sich mit den Stärken und Schwächen von einzelnen Ansätzen der Sekundäranalyse qualitativer Daten befassen. Im ersten Abschnitt beziehen sich die Beiträge auf die Bedeutung des Kontextes: wie am Besten der Kontext der Ersterhebung erhalten bleibt und wie mit den Herausforderungen durch dekontextualisierte Archivdaten umgegangen werden kann. Im zweiten Teil der Schwerpunktausgabe berichten die Autoren und Autorinnen über ihre Erfahrungen mit der Sekundärnutzung von Daten in den Themenbereichen Klasse, Medizin, Geschichte und Beruf. Dabei diskutieren sie die Re-Interpretation von Befunden und analytischen Strategien der Primärstudien und Ansätze, die Methode der Sekundäranalyse zu lehren. Im letzten Abschnitt zielen die Beiträge eher auf forschungspraktische Probleme wie Anonymisierungsstrategien und Hilfsmittel, die einige der technischen Defizite beim Umgang mit qualitativen Daten beseitigen sollen. Obwohl sich neue Möglichkeiten der Unterstützung und Förderung von Sekundäranalysen abzeichnen, besteht weiterhin insbesondere Bedarf an wissenschaftlich anspruchsvollen und Skeptiker überzeugenden Beispielen für die Wiederverwendung qualitativer Daten. Wir hoffen, dass die vorliegende FQS-Schwerpunktausgabe zum Ausfüllen dieser Lücke beiträgt.

The ubiquity of digital devices and the increasing intensity of users' interactions with them create vast amounts of digital trace data. Companies use these data to optimize their services or products, but these data are also of interest to researchers studying human behavior. As most of these data are owned by private companies and their collection requires adherence to their terms of service, research with digital trace data often entails some form of public-private partnership. Private companies and academic researchers each have their own interests, some of which are shared, while others may conflict. In this article, we explore different types of private-public partnerships for research with digital trace data. Based on general considerations and particular experiences from a research project with linked digital trace data, we propose strategies for identifying and productively negotiating both shared and conflicting interests in these relationships.

Linking social media data with survey data is a way to combine the unique strengths and address some of the respective limitations of these two data types. As such linked data can be quite disclosive and potentially sensitive, it is important that researchers obtain informed consent from the individuals whose data are being linked. When formulating appropriate informed consent, there are several things that researchers need to take into account. Besides legal and ethical questions, key aspects to consider are the differences between platforms and data types. Depending on what type of social media data is collected, how the data are collected, and from which platform(s), different points need to be addressed in the informed consent. In this paper, we present three case studies in which survey data were linked with data from 1) Twitter, 2) Facebook, and 3) LinkedIn and discuss how the specific features of the platforms and data collection methods were covered in the informed consent. We compare the key attributes of these platforms that are relevant for the formulation of informed consent and also discuss scenarios of social media data collection and linking in which obtaining informed consent is not necessary. By presenting the specific case studies as well as general considerations, this paper is meant to provide guidance on informed consent for linked survey and social media data for both researchers and archivists working with this type of data.

Balancing speed and quality during crises pose challenges for ensuring the value and utility of data in social science research. The COVID-19 pandemic in particular underscores the need for high-quality data and rapid dissemination. Given the importance of behavioral measures and compliance with measures to contain the pandemic, social science research has played a key role for policymaking during this global crisis.

This study addresses two key research questions: How FAIR (findable, accessible, interoperable, and reusable) are social science data on the COVID-19 pandemic? Which study features are related to the level of FAIRness scores of datasets? We assess the FAIRness of n=1,131 articles, retrieved through a keyword search in the Web of Science database, employing both automated and manual coding methods. Our study inclusion criteria encompass empirical studies on the COVID-19 pandemic published between 2019-2023 with a social science focus and explicit reference to the underlying dataset(s). Our analysis of n=45 datasets reveals substantial differences in FAIRness for different types of research on the COVID-19 pandemic. The overall FAIRness of data is acceptable, although particularly Reusability scores fall short, in both the manual and the automatic assessment. Further, articles explicitly linked to the Social Science concept in the OpenAlex database exhibit a higher mean overall FAIRness value. Based on these results, we derive recommendations for balancing ethical obligations and the potential tradeoff between speed and data (sharing) quality in social-scientific crisis research.

The replication data contains the manual and automatic coded values for FAIR criteria and the complete code to re-produce the results for the article.