Corpus and mapping – Work Package 1

WP1 creates a corpus of sources mapping nanobiology and its community and is presented in this post.

The project is organised in five closely connected work packages, each involving all the PIs to guarantee maximum synergy. WP2 traces error and controversial claims in nanobiology over time and is described here. WP3 analyses attempts at correction and includes actual attempts at correction and improved communication to discourage error propagation and encourage correction in the future, see here. WP4 analyses processes that impede or facilitate correction and investigates how scientists trust research results, as well as how this trust can be enhanced; it is presented here. A fifth work package is devoted to project organisation and integration.

Shared IT platform

We will establish a shared IT platform providing support for data use and analysis, including for non-specialist project members. To empower synergies among the teams, the platform will:

• Assure the usability by non-IT specialists of advanced software developed by computer scientists,
• Foster harmonization, common usage and practices regarding concepts, datasets and procedures,
• Develop and curate the data management plan.

The platform team will be composed of two engineers with complementary skills (software development and digital humanities) under the supervision of Cyril Labbé and team member Frédérique Bordignon. The platform will provide access to a range of tools, from digital procedures that are relatively standard (for instance parsing or scraping tools, geolocalization or spatial activities, customized needs, etc.) to frontier research in computing sciences.

The platform will define an explicit common vocabulary, particularly for nanobiosciences and technologies concepts. The team will coordinate the building of an ontology, co-elaborated with all PIs and their teams, to provide a hierarchy of concepts and define their semantic relations. This will facilitate many aspects of the project, particularly retrieval of articles and constitution of corpuses for scientometric studies, and for textual material analyses (evolution of concepts with natural language processing tools, discourse analysis and argumentative patterns recognition, tagging of interviews).

A data management plan will be written as soon as the project starts and will be regularly updated. It will include information about what kinds of data are collected, processed and generated, what standards should be applied -if they exist-, and how and when they will be made available for reuse. The data management plan will be guided by the kinds of data generated in all the work packages; some of these, such as field observations (including visuals) and interviews, are not easily documented within widely-used protocols developed for quantitative data and will therefore require particular attention.

Shared data set

We will establish a shared data set that brings together texts, arguments, events, and the nanobio community relevant for the analyses in WP2. This will be both a foundation for the project and an evolving resource that will be progressively enriched throughout the project, creating synergy around data in NanoBubbles. This reference library will allow more detailed studies, in close collaboration between digital methods (scientometrics, textual analysis) and qualitative research (case studies, interviews, historical work, ethnography of conferences and scientific communication), in collaboration with critical nanobiologists.

The shared data sets include:

• A corpus of texts, ranging from research journals, to repositories, conference papers, social media communications and media publications (newspapers, magazines).
• An identification of key communication channels, including an overview of conferences, journals, social media, funding agencies.
• A set of key scientists and researchers in crucial positions, such as editors.
• An inventory of key terms, concepts, preparing further lexicographic work.
• Preparatory work for the annotation and replication projects.

Main outcomes and synergies

WP1 is highly collaborative. It draws on the expertise of all teams to build a shared vocabulary, tools, data sets and a data management plan that ensure synergy throughout the project.

Risk assessment

Given the PIs’ different backgrounds, building a corpus and common language may be difficult and converge too slowly. This risk is handled by allocating particularly skilled human resources to this task (two engineers and a philosopher of language, Yasemin J Erden). Previous collaboration between team members will also help. Adopting an incremental and highly adaptive approach will allow a quick start and assure reactivity.

Cyril Labbé is the lead PI of this WP.