TDCC SSH Bottleneck Projects

These projects are intended to respond to one or more of our key bottleneck areas:

  • Increasing the amount of findable, accessible, interoperable and reusable (FAIR) research data and software 
  • Raising awareness amongst researchers about FAIR data and software practices
  • Enhancing the awareness of available digital data and SSH-oriented tools
  • Addressing pressing issues related to the collection and usage of data, like privacy and copyright legislation and the high costs of collecting and producing digital data 
  • Building an open, inclusive and equitable network

They are small scale, last up to 12 months and with a budget of maximum €150,000. There is a one-off sum of €950,000 per TDCC available to distribute through this funding strand.

Bottleneck Projects Process

The collaborative process to develop these projects began in mid 2023 with a publicly shared 'request for community input', as well as a series of stakeholder conversations and community consultations.

After a public consultation period and review by the TDCC-SSH Executive Board, the six project ideas below are now in development into full project proposals. We established a Bottleneck Project Board with three members who will provide the project teams with feedback by one member ('mentoring role') and a review of the proposal by two members ('reviewers').

Note: This Project Board is only focusing on the 'Bottleneck' projects. For more information on the process for the 'Challenge' projects (NWO TDCC call), please refer to the information on our corresponding web pages.

If you have questions about the projects, please reach out to the primary contact person listed and include in CC.

Project Idea 1: Combating Bias: Guidelines for Creating Equitable Data in the Humanities

Consultation period ended.

In the humanities, colonial archives stand as potent remnants of histories told through the lens of colonizers. Their inherent biases not only skew historical narratives but perpetuate inequalities if left unchecked. Such historically rooted biases echo a broader challenge faced by the contemporary world: the danger of constructing knowledge from unexamined sources, be it conventional studies or machine learning.

While strides have been made in computer science in tackling bias with dataset documentation standards, historical data presents unique challenges. Given the nature of historical data, especially from colonial sources, the goal cannot be to seek out 'less biased' datasets, but rather to ethically and transparently represent existing biases, particularly when these concern marginalized communities. There are now growing calls in the cultural heritage sector for standards to help guide this process, but resources for humanities researchers remain limited. At the same time, the humanities disciplines, equipped with the necessary critical methodological frameworks, also hold the potential to define and create these standards.

The Combatting Bias initiative unites four projects focusing on colonial archives and themes of slavery. Anchored in data ethics and governance, we will scrutinize issues of data provenance, terminology, categorization, and dataset interoperability at each partner project. Our mission is to craft evidence-based guidelines promoting ethical and transparent data practices. Originating from methodological approaches employed in the humanities to address colonial imbalances, these guidelines aspire to be of broad import, benefiting both the wider humanities and cultural heritage landscape and machine learning fields that utilize socially and historically informed data.

Involved parties so far:
International Institute for Social History - Merve Tosun and Filipa Ribeiro da Silva, Exploring Slave Trade in Asia Project 
Radboud University - Coen van Galen, Slave Registers Project
Huygens Institute - Mrinalini Luthra and Matthias van Rossum, GLOBALISE Project
The Slave Voyages Project - Daniel Domingues da Silva, sponsored by numerous universities in the United States 

Primary contact info:
Manjusha Kuruppath
GLOBALISE Project, Huygens Institute

Project Idea 2: Towards a FAIR-Enabling Approach to Research Integrity in Research Data Management: A national consultation with Faculties of Social & Behavioural Sciences

Consultation period ended.

The DSW Committee on Research Integrity in Research Data Management (hereafter,  the Committee)[1] maintains a Guideline for Faculties of Social & Behavioural Sciences (FSBSs) in the Netherlands (20182022) outlining best practices and requirements for ensuring the transparency of empirical research to enable verification by academic peers. In light of the Committee’s wishes to extend the Guideline’s scope to cover the entire research lifecycle – and seizing an opportunity presented by a mandate to reevaluate the Guideline every two years – this Bottleneck Project proposes a national consultation on the current state of Research Data Management (RDM) in FSBSs.

The consultation will (1) survey the policies, practices, and infrastructure that are currently in place to support RDM, including research integrity, Open Science, and FAIR data; (2) probe the attitudinal, epistemological, and sociotechnical factors that support/inhibit their uptake; and (3) solicit respondents’ perspectives on how existing bottlenecks can be addressed/overcome. Methodologically, we will deploy both a (quantitative) survey instrument as well as (qualitative) focus groups and semi-structured interviews with stakeholders in each FSBS throughout the country. Our target population includes researchers, institute leadership, research data and software managementpersonnel, data privacy officers, research ethics committees, policy officers, as well as research data infrastructure/IT personnel..

Project findings will inform a report to the Committee with recommendations for addressing the observed bottlenecks in the next version of the Guideline – including developing more FAIR-enabling approaches to Research Integrity in RDM – while also highlighting key areas of digital competency that future TDCC-SSH projects can target for improvement.
[1] Formerly the committee on Scientific Integrity, Data Storage and Reproducibility, which operates under the auspices of the Deans of Faculties of Social and Behavioural Sciences in the Netherlands (DSW)

Involved parties so far:
Leiden University – Andrew S. Hoffman (Service Scientist - RDM), Kathleen Gregory (Researcher), Katie Hudson (Data Steward), Céline Richard (Data Manager)
DSW Committee on Research Integrity in Research Data Management – Cristina Grasseni (Leiden University), Frans Oort (University of Amsterdam), Marion Palstring (Maastricht University), Jelte Wicherts (Tilburg University)
University of Amsterdam – Marilena Poulopoulo (Data Steward), Emma Schreurs (Data Steward)
• DANS – Ricarda Braukmann (Data Station Manager Social Sciences), Jetze Touber (Data Station Manager Humanities)

Primary contact person:
Andrew S. Hoffman, Faculty of Social Sciences, Leiden University

Project Idea 3: StoRe – Storing oral histories for future reuse across communities

Consultation period ended.

Oral history has been growing in popularity in the Netherlands, both within and outside established research institutes. However, oral history collections are rarely preserved for re-use for several reasons: researchers struggle with privacy and ethical issues, community archives aren't well versed in the concept of FAIR data, museums lack infrastructural knowledge, to name a few. [1] Moreover, practitioners in general often underestimate the added value of preserving oral history and other qualitative interview data for reuse, as datasets that could add to multivocality, and counter or nuance dominant scholarly narratives.
A coordinated effort of the SSH community in the Netherlands is needed to unlock large amounts of oral history data for and by SSH scholars, community archivists and museum professionals. In this project, we develop much needed guidelines to increase the preservation and reusability of oral histories and other qualitative interviews as research and heritage data. Our aim is to stimulate preservation for reuse by removing technical obstacles and develop tools to address legal and ethical bottlenecks. 
What is required is assistance for oral history practitioners to find their way to the expertise and technical infrastructure that is already available. We coordinate the effort of producing guidelines, differentiating among various target audiences: (1) academic researchers, (2) community archives and (3) museums. We disseminate guidelines through workshops and open access tutorials. We do so within an action-based framework: with each target audience, we co-develop a set of use cases to identify bottlenecks and co-create guidelines.
[1] See for instance: this article from Netwerk Digitaal Erfgoed (consulted 24 October 2023) and this article on the Sprekende Geschiedenis website (consulted 24 October 2023).

Involved parties so far:
Vrije Universiteit Amsterdam – Dr. Norah Karrouche (Huizinga Institute Oral History Research Network, CLARIAH)
Stichting Bevordering Maatschappelijke Participatie – Saskia Moerbeek (Sprekende Geschiedenis)
Nederlands Instituut voor Beeld en Geluid – Dr Roeland Ordelman (CLARIAH)
CLARIAH – Dr Jetze Touber (DANS)

Primary contact person:
Dr. Norah Karrouche, Huizinga Institute Oral History Research Network/CLARIAH, Vrije Universiteit Amsterdam

Project Idea 4: Untangling FAIR Implementation in the SSH

Consultation period ended.

Research Data Management (RDM) experts in the Dutch SSH Research and Infrastructure milieu aim to provide FAIR data in accordance with a rapidly-evolving ecosystem. In doing so, they are required to balance the need for community-specific standards due to the heterogeneous types of data, while also fostering interoperability at the level of the SSH domain to facilitate ground-breaking interdisciplinary research. 
We have identified two primary stakeholder groups. The first includes infrastructure, archival entities and heritage institutions (e.g., CLARIAH, ODISSEI, DANS, UKB, NDE), mainly responsible for developing and maintaining domain-wide FAIR technical, curatorial, and archival standards. The second group includes Research Performing Organizations (universities, research institutes) and pursues the implementation of FAIR community-/discipline-specific standards in their policies, services, and workflows when providing data.
Currently, alignment is hindered by structural divergence along two dimensions: first, the diverse and often implicit technical standards for FAIR data management adopted by different entities; second, the organisational structures which place the responsibility of FAIR policies at different levels in each organisation, hindering dialogue. 
In the project, we aim at untangling these technical and organisational complexities to facilitate a coordinated approach to FAIR Implementation.  The project is divided into two main components. First, we will conduct a preliminary reconnaissance of the organisation-specific FAIR technologies, practices  and decisional structures.  Second, we will organise a 2-day workshop to discuss the results of the technological inventory and the organisational mapping and decide how to move forward. The workshop will inform the creation of a Roadmap towards FAIR implementation in the SSH.

Involved parties so far:
ODISSEI – Angelica Maineri (EUR-ESSB, FAIR Expertise Hub for the Social Sciences)
Erasmus University Rotterdam – Bora Lushaj (ISS/ESL)
CLARIAH – Jetze Touber (DANS)
Netwerk Digitaal Erfgoed (NDE), Royal Library (KB) – Enno Meijers

Primary contact person:
Angelica Maineri, ODISSEI

Project Idea 5: Beyond personal data: RDNL training on hard-to-share data for SSH early-career researchers

Consultation period ended.

In SSH, attention is mostly focused on challenges in sharing personal data, and while this is a key issue, there are many other reasons why data can be hard to share that are not currently addressed. Examples are non-personal sensitive data like location data of archaeological sites, field notes in sociology or anthropology, commercial or security constraints in economics or criminology, ethical considerations on data sovereignty for researchers working abroad and/or with local communities, and practical questions where to safely store, share and find data. Therefore, we propose to develop training and guidelines on hard-to-share data examples.
We bring together Research Data Management experts with domain experts to train early-career researchers in two half-day workshops on:

1. Field notes: these form ‘raw data’ in several disciplines. They are often handwritten, but even when born-digital they tend to be subjective and not shared. 

2. The ethical side of data sovereignty: legally this may be clear, but who should decide on data sharing, for example when working with commercial partners or local communities?
Trainees will discuss and learn how to share this type of data in a FAIR way. Research Data Netherlands (RDNL) will make the materials available both for reuse directly on these topics within and outside SSH, to inspire more training on other hard-to-share examples.

Involved parties so far:
• Research Data Netherlands (RDNL) - Maithili Kalamkar-Stam (SURF), Marjan Grootveld and Pascal Flohr (DANS-KNAW)
Promovendi Netwerk Nederland (PNN) – Anna Roodhof (WUR)
• Erasmus Research Institute of Management/Erasmus Data Service Center

Primary contact person:
Maithili Kalamkar-Stam (SURF, RDNL partner)

Project Idea 6: Daidalos - A Digital Social Sciences and Humanities Summer/Winter School on Research Software

Consultation period ended.

We propose to develop a Digital Social Sciences and Humanities (Summer/Winter) School (Daidalos). The consortium partners will work together to create a format for a 2-3 week “crash course” in good practices for social scientists and humanities researchers. A group of ~30 researchers will be selected to be part of the first edition of this course with a specific research project. During the course, they will learn about good practices in software development, as well as an introduction to programming, parallel programming, machine learning and/or Natural Language Processing. After the formal training part of the course, one week of on-site consultancy will be available by experienced methodology and software engineering consultants while the researchers work on their projects. 
Consortium partners will be providing either consultancy, teaching time, course material or ways to access research tools and data to Daidalos. Software and data used in the course will be taken from / uploaded to the RSD, Ineo or the DANS data station. A dedicated website with all course materials will be set up, as well as a playbook on how to run the programme to ensure the programme’s sustainability.  

Daidalos addresses specific challenges in specified in the TDCC-SSH roadmap, such as (a) lack of awareness, experience and knowledge of good coding and software engineering practices (challenge 1, 3, 4, 6 in the roadmap); (b) a lack of recognition for good practices in research software (challenge 2, 6); (c) scattered and broad domain (challenge 5, 8, 9); (d) strong impact of recent technological developments (challenge 7, 10).

Involved parties so far:
• Netherlands eScience Center – Lieke de Boer, Valentina Azzara
Utrecht University, CDH Research Software Lab – Jill Briggeman, Hugo Quene, Andre van Kooij
• KNAW Digital Humanities Cluster

Primary contact person:
Lieke de Boer (eScience Center)