Deep Impact: A Study on the Impact of Data Papers and Datasets in the Humanities and Social Sciences

Authors : Barbara McGillivray, Paola Marongiu, Nilo Pedrazzini, Marton Ribary, Mandy Wigdorowitz, Eleonora Zordan

The humanities and social sciences (HSS) have recently witnessed an exponential growth in data-driven research. In response, attention has been afforded to datasets and accompanying data papers as outputs of the research and dissemination ecosystem.

In 2015, two data journals dedicated to HSS disciplines appeared in this landscape: Journal of Open Humanities Data (JOHD) and Research Data Journal for the Humanities and Social Sciences (RDJ).

In this paper, we analyse the state of the art in the landscape of data journals in HSS using JOHD and RDJ as exemplars by measuring performance and the deep impact of data-driven projects, including metrics (citation count; Altmetrics, views, downloads, tweets) of data papers in relation to associated research papers and the reuse of associated datasets.

Our findings indicate: that data papers are published following the deposit of datasets in a repository and usually following research articles; that data papers have a positive impact on both the metrics of research papers associated with them and on data reuse; and that Twitter hashtags targeted at specific research campaigns can lead to increases in data papers’ views and downloads.

HSS data papers improve the visibility of datasets they describe, support accompanying research articles, and add to transparency and the open research agenda.

URL : Deep Impact: A Study on the Impact of Data Papers and Datasets in the Humanities and Social Sciences


Data papers as a new form of knowledge organization in the field of research data

Authors : Joachim Schöpfel, Dominic Farace, Hélène Prost, Antonella Zane

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e. disciplines, publishers and business models, and about their structure, length, formats, metadata and licensing.

Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable.

Data papers are essentially information, i.e. description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing.


Data objects and documenting scientific processes: An analysis of data events in biodiversity data papers

Authors : Kai Li, Jane Greenberg, Jillian Dunic

The data paper, an emerging scholarly genre, describes research datasets and is intended to bridge the gap between the publication of research data and scientific articles. Research examining how data papers report data events, such as data transactions and manipulations, is limited.

The research reported on in this paper addresses this limitation and investigated how data events are inscribed in data papers. A content analysis was conducted examining the full texts of 82 data papers, drawn from the curated list of data papers connected to the Global Biodiversity Information Facility (GBIF).

Data events recorded for each paper were organized into a set of 17 categories. Many of these categories are described together in the same sentence, which indicates the messiness of data events in the laboratory space.

The findings challenge the degrees to which data papers are a distinct genre compared to research papers and they describe data-centric research processes in a through way.

This paper also discusses how our results could inform a better data publication ecosystem in the future.

URL : Data objects and documenting scientific processes: An analysis of data events in biodiversity data papers

Alternative location :

Publishing science without results and recycling research

Author : Eric Lichtfouse

Most scientists focus too much on publishing original articles. In doing so, scientists are restricting their writing skills to this form of highly specialised publication, which is poorly readable by scientists from other disciplines.

In the context of rising interdisciplinary research and data abundance, there is a need for more publications that recycle existing research and communicate to a wider audience. Therefore, I present here five types of publications that do not require additional experiments , namely reviews, methods, data papers, meta-analyses and videos.

Benefits include more citations, larger visibility, wider dissemination, easier job finding, grant success and better recycling of research.


Améliorer l’exposition des données de la recherche : la publication de data papers

Auteur/Author : Nathalie Reymonet

Les données de la recherche sont l’objet de l’intérêt des financeurs de la recherche publique, qui incitent les chercheurs à partager ces données, afin de répondre à des enjeux financiers comme de circulation des savoirs.

Parmi les différentes modalités de la communication scientifique, la publication d’un « data paper » est une démarche relativement nouvelle. Le « data paper », ou article sur des données, décrit des données scientifiques et propose un lien vers un entrepôt de données qui les stocke.

La description est en particulier très précise sur les points techniques et la méthodologie de production des données. Cette démarche va dans le sens de l’exposition des données, de leur accessibilité, leur interopérabilité et leur réutilisabilité, répondant ainsi aux recommandations des communautés d’intérêt de la recherche académique.

Ce texte présente la structure et le contenu d’un « data paper » ainsi que des exemples de revues qui publient de tels articles.

URL : Améliorer l’exposition des données de la recherche : la publication de data papers

Alternative location :