#data citation

[superlinguo]

New Research Article: Data transparency and citation in the journal Gesture

This new paper extends the data transparency survey method that I’ve been using with the Linguistic Data Interest Group to the journal Gesture. It not only brings together two research areas I care deeply about: gesture and data management, but also two groups of collaborators I love working with: Andrea Berez-Kroeker and Helene Andreassen in lingdata and Chelsea Krajcik and Barb Kelly in gesture.

This is the first time we have published a paper on this methodology focusing on a specific journal, and I’m grateful to Sotaro Kita and the Gesture editorial board for being open to this reflexive experience. Some key observations:

Gesture research encompasses a wide range of methodologies

There are a small number of strongly represented languages (hello English), but a lot of linguistic diversity too

Researchers mostly work with their own data, but don’t always give a lot of detail on where that data is located

There is scope to improve the way data is cited back to the original source - something that makes it easier for the reader to engage with the paper but is also helpful for the author!

Gesture is a feature of language that is highly context depended, and is hard to replicate for a new author. Allowing for more transparent access to underlying examples for the reader allows for the possibility of reproducing the analysis (or not!) based on the original data. This approach means the foundation of the field can be built stronger.

Why am I blogging about this in 2020 when it was published in 2019?

The official publication date for this paper is 2019, but Gesture is running a bit behind on its publication schedule. You can see on the Gesture website page for this article that it was first published in 2020. I’m just glad to be able to finally share it with you!

Abstract

Data is central to scholarly research, but the nature and location of data used is often under-reported in research publications. Greater transparency and citation of data have positive effects for the culture of research. This article presents the results of a survey of data citation in six years of articles published in the journal Gesture (12.1–17.2). Gesture researchers draw on a broad range of data types, but the source and location of data are often not disclosed in publications. There is also still a strong research focus on only a small range of the world’s languages and their linguistic diversity. Published papers rarely cite back to the primary data, unless it is already published. We discuss both the implications of these findings and the ways that scholars in the field of gesture studies can build a positive culture around open data.

Keywords:

data citation, open data, data management, gesture studies

Reference

Gawne, Lauren, Chelsea Krajcik, Helene N. Andreassen, Andrea L. Berez-Kroeker & Barbara F. Kelly. (2019). Data Transparency and Citation in the Journal Gesture. Gesture 18(1):  83–109. doi: https://doi.org/10.1075/gest.00034.gaw

Green Open Access version available on Figshare: https://doi.org/10.26181/5f57fddc85ebb

Related research publications on data citation:

Reproducible research in linguistics: A position statement on data citation and attribution in our field

Putting practice into words: New paper out about methods and data in descriptive grammar writing

Survey of Current Reproducibility Practices in Linguistics Journals, 2003-2012

General resources on data citation in linguistics

The Austin principles of data citation in linguistics

The Tromsø recommendations for citation of research data in linguistics

Linguistics Data Interest Group of the Research Data Alliance (interested in this topic? Join us!)

[superlinguo]

New Paper: Reproducible research in linguistics: A position statement on data citation and attribution in our field

I’m so excited to share this paper on data citation in linguistics, published in Linguistics. Not just because it was co-authored with 13 other linguists, including some of my linguistics heroes, but because it articulates so much of what we need to do to improve the way linguists think about data. (it’s Open Access, so you can read/download and share as you wish!)

I’m often reminded of something Nicholas Evans likes to say:

“Linguistics has a unique but unfulfilled destiny, as the most scientific of the humanities and the most humanistic of the sciences.”

It captures what I love about linguistics, but I think it also explains why we have a complicated relationship with the idea of data, and its management. This position paper outlines why it is important that linguists think about the data on which linguistic claims are made.

My Favourite line

Linguistic data are the very building blocks of our field. Given that linguistic theories need to be borne out through data, we believe that linguistic data are important resources in their own right and represent valuable assets for the field. Therefore, our field needs to accept responsibility for the proper documentation, preservation, attribution, and citation of these assets. The responsibility to do so is an integral part of linguistic research, and it should be collectively shared by individual scientists and researchers, data stewards, research institutions, and funding organizations.

Article writing Trivia

I’ve been working on some parts of this paper with Andrea Berez-Kroeker since 2013. Andrea has been working on some of the central ideas in this paper for even longer. Academia is a slow game sometimes, but this paper says a lot of things that a lot of the authors have been thinking about for a long time.

A lot of ideas in this paper formed the initial motivation for the Austin Principles of Data Citation in Linguistics

There is a reference to work on bacteria in human navels as an example of replicable research because I had read about Carl Zimmer’s participation in this research on his blog a couple of years early and it amused me greatly.

Abstract

This paper is a position statement on reproducible research in linguistics, including data citation and attribution, that represents the collective views of some 41 colleagues. Reproducibility can play a key role in increasing verification and accountability in linguistic research, and is a hallmark of social science research that is currently under-represented in our field. We believe that we need to take time as a discipline to clearly articulate our expectations for how linguistic data are managed, cited, and maintained for long-term access.

See also

Putting practice into words: New paper out about methods and data in descriptive grammar writing

Linguistics Data Interest Group - New RDA group to improve data citation and transparency

The Austin Principles of Data Citation in Linguistics

Reference

Berez-Kroeker, A.L., L. Gawne, S. Kung, B.F. Kelly, T. Heston, G. Holton, P. Pulsifer, D. Beaver, S. Chelliah, S. Dubinsky, R. Meier, N. Thieberger, K. Rice & A. Woodbury. 2018. Reproducible Research in linguistics: A position statement on data citation and attribution in our field. Linguistics. 56(1): 1-17. 10.1515/ling-2017-0032

[superlinguo]

Linguistic data form not only a record of scholarship, but also of cultural heritage, societal evolution, and human potential. Because of this, the data on which linguistic analyses are based are of fundamental importance to the field and should be treated as such. Linguistic data should be citable and cited, and these citations should be accorded the same importance as citations of other, more recognizable products of linguistic research like publications.

The Austin Principles of Data Citation in Linguistics (Berez-Kroeker et al. 2017)

The Austin Principles of Data Citation in Linguistics

The Linguistics Data Interest Group in the Research Data Alliance have spent the last year working on a document that explains why it’s so important for linguists to make their data ‘citable’. Linguistics builds itself as a discipline that uses empirical evidence to make claims, but so often the reader doesn’t have access to this underlying data to verify the claims (or test their own ideas!). The Austin Principles of Data Citation in Linguistics provide the reasons that citation should be central to all linguistic work. Even if you work with introspection, you may not have data to cite, but making clear that the data come from in introspection is still an important, and often omitted, piece of information.  

If you’re a linguist, you can endorse the principles

Even if you’re only just starting your linguistic research career, you can add your name to the list of linguists who endorse the principles. You can also use the principles to start conversations about data citation and management in your lab, class, department, linguistics society, or journal.

If you would like to help shape the future of linguistic data, you can also join us in the RDA Linguistics Data Interest Group (LDIG). This post from April explains what the LDIG is, and why it’s important.

From the Preamble of the Austin Principles:

Data is central to empirical linguistic research. Linguistic data comes in many different forms, and is collected and processed with a wide range of methods. Data citation recognizes the centrality of data to research. Furthermore, it facilitates verification of claims and repurposing of data for other studies.

The FORCE11 Joint Declaration of Data Citation Principles* state that “[s]ound, reproducible scholarship rests upon a foundation of robust, accessible data. For this to be so in practice as well as theory, data must be accorded due importance in the practice of scholarship and in the enduring scholarly record. In other words, data should be considered legitimate, citable products of research. Data citation, like the citation of other evidence and sources, is good research practice and is part of the scholarly ecosystem supporting data reuse.”

The FORCE11 Joint Declaration of Data Citation Principles is intentionally broad so to be as inclusive of data from as many scientific disciplines as possible. This document, the Austin Principles of Data Citation in Linguistics, interprets the FORCE11 document to address linguistic data specifically. These guiding principles have been created to enable linguists to make decisions about their data that ensure it is as accessible and transparent as possible. Some subfields of linguistics may already have specific guidelines for data citation; in these cases the Austin Principles can supplement extant guidelines to ensure that data citation conforms with current best practices.

What’s next for the Linguistics Data Interest Group

The Austin Principles of Data Citation are the first major output for the LDIG, it focuses on the why of data citation. We’re now focusing on the how of data citation. This includes sharing the Austin Principles, developing more training on research data management, and also working with researchers, archives and publishers to develop data citation standards.

Reference

Berez-Kroeker, A. L., Andreassen, H. N., Gawne, L., Holton, G., Kung, S. S., Pulsifer, P., Collister, L. B., The Data Citation and Attribution in Linguistics Group, & the Linguistics Data Interest Group. 2017. Draft: The Austin Principles of Data Citation in Linguistics (Version 0.1). http://site.uit.no/linguisticsdatacitation/austinprinciples/ Accessed 13/12/2017.

[openingscience-blog]

The motivation to cite datasets comes from a recognition that data generated in the course of research are just as valuable to the ongoing academic discourse as papers, and should therefore be treated in the same manner.

Blog entry by Scott Edmunds, including a brief history of data citation.