Data Journals: A Survey

Data Science and Informetrics, 2024

The contribution of the data paper publishing paradigm to the knowledge generation and validation processes is becoming substantial and pivotal. In this paper, through the information-processing perspective of Mindsponge Theory, we discuss how the data article publishing system serves as a filtering mechanism for quality control of the increasingly chaotic datasphere. The overemphasis on machine-actionality and technical standards presents some shortcomings and limitations of the data article publishing system, such as the lack of consideration of humanistic values, radical race for big data, and inadequate use of expertise in data evaluation. Without addressing the shortcomings and limitations, the reusability of data will be hindered, and scientific investment to facilitate data sharing will be wasted. Thus, we suggest that the current data paper publishing paradigm needs to be updated with a new philosophy of data.

Journal of Scholarly Publishing, 2017

The last decade has seen a dramatic increase in attention from the scholarly communications and research community to open access (OA) and open data practices. These are potentially related because journal publication policies and practices both signal disciplinary norms and provide direct incentives for data sharing and citation. However, there is little research evaluating the data policies of OA journals. In this study we analyse the state of data policies for OA journals by employing random sampling of the Directory of Open Access Journals and Open Journal Systems journal directories and applying a coding framework that integrates both previous studies and emerging taxonomies of data sharing and citation. This study, for the first time, reveals both the low prevalence of data-sharing policies and practices in OA journals, which differs from the previous studies of commercial journals in specific disciplines.

KNOWLEDGE ORGANIZATION

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 ...

2008

Abstract This paper presents a discussion of the issues associated with formally publishing data in academia. We begin by presenting the reasons why formal publication of data is necessary, which range from simple fact that it is possible, to the changing disciplinary requirements. We then discuss the meaning of publication and peer review in the context of data, provide a detailed description of the activities one expects to see in the peer review of data, and present a simple taxonomy of data publication methodologies.

2016

Journal data policies are a potentially strong incentive for researchers to make research data available. Therefore, information about these policies is desirable. This article presents an analysis of 346 journal data policies based on a 534 cross-disciplinary journal sample with a focus on how journal publishers expect authors to make research data available. Furthermore, it includes an analysis of features such as thematic scope, user costs and hosting organisations of 171 repositories with an entry in the Thomson Reuters Data Citation Index.

With the growing importance of data to the scholarly record and the critical role journals play in facilitating data sharing, the complex landscape of scholarly journal data publication policies has become an obstacle for research. This paper outlines Data-PE, a framework for evaluating these policies. It takes the form of a conceptual foundation, comprising twelve criteria for evaluation, operationalized through an evaluation tool. Its objective is to function as a flexible means for a variety of stakeholders to appraise individual policies. Examples of the use of the framework are provided and means for the validation of the tool are discussed.

PLOS One, 2011

Background: There is increasing interest to make primary data from published research publicly available. We aimed to assess the current status of making research data available in highly-cited journals across the scientific literature.

Scientific journals have long acted as a stabilizing force in academia, by defining scientific communities, demarcating subfields and showcasing their key insights. Stability derives not least from the structure of a scientific paper, which imposes order on the ever-shifting processes of data collection and analysis by fitting results into a systematic and cohesive narrative, aimed at persuading readers of the validity of a given knowledge claim. This is what philosophers of science have dubbed 'reconstruction' or 'justification' of scientific insights: papers provide an account that excludes research aspects and outputs that are not directly relevant to the arguments at hand – such as experiments or models that failed, data that proved irrelevant or neutral with regards to the hypotheses at stake, and procedural details that do not fit existing formats.1 Journal publications thus provide science with a quantifiable, fixed and spatio-temporally located output, which helps to adjudicate the success, and disseminate the achievements of, a given research effort.

Revista Hipertext.net, 2023

This article aims to suggest actions for the opening of scientific data, deposit, use and dissemination, so that scientific journals, linked to Higher Education Institutions, create open data collections. It is an applied social research, with a qualitative, exploratory, documentary approach and with action-research dimensions. A survey of the scientific data openness policies of the journals that use the Dataverse repository of Harvard University was carried out, based on the requirements of the quality seal of reliable digital repositories Core Trust Seal and the Transparency and Openness Promotion Guidelines. The information obtained in this survey supported the implementation of action-research steps, through which guidelines were formulated to meet the proposed objective. With such results, other journals will be able to join the movement of open data adjacent to the articles they publish, expanding the scientific practices related to the movement for open science and the democratization of scientific knowledge.

Data Science Journal, 2006