Search results

As intelligent technology advances, practical applications often involve data with multiple labels. Therefore, multi-label feature selection methods have attracted much attention to extract valuable information. However, current methods tend to lack interpretability when evaluating the relationship between different types of variables without considering the potential causal relationship.

To address the above problems, we propose an ensemble causal feature selection method based on mutual information and group fusion strategy (CMIFS) for multi-label data. First, the causal relationship between labels and features is analyzed by local causal structure learning, respectively, to obtain a causal feature set. Second, we eliminate false positive features from the obtained feature set using mutual information to improve the feature subset reliability. Eventually, we employ a group fusion strategy to fuse the obtained feature subsets from multiple data sub-space to enhance the stability of the results.

Experimental comparisons are performed on six datasets to validate that our proposal can enhance the interpretation and robustness of the model compared with other methods in different metrics. Furthermore, the statistical analyses further validate the effectiveness of our approach.

The present study makes a noteworthy contribution to proposing a causal feature selection approach based on mutual information to obtain an approximate optimal feature subset for multi-label data. Additionally, our proposal adopts the group fusion strategy to guarantee the robustness of the obtained feature subset.

This study aims to identify the readiness of institutional repositories in Indonesia to implement digital humanities (DH) data curation. Data curation is a method of managing research data that maintains the data’s accuracy and makes it available for reuse. It requires controlled data management.

The study uses a qualitative approach. Data collection was carried out through a focus group discussion in September–October 2022, interviews and document analysis. The informants came from four institutions in Indonesia.

The findings reveal that the national research repository has implemented data curation, albeit not optimally. Within the case study, one of the university repositories diligently curates its humanities data and has established networks extending to various ASEAN countries. Both the national archive repository and the other university repository have implemented rudimentary data curation practices but have not prioritized them. In conclusion, the readiness of the national research repository and the university repository stand at the high-capacity stage, while the national archive repository and the other university repository are at the established and early stages of data curation, respectively.

This study examined only four repositories due to time constraints. Nonetheless, the four institutions were able to provide a comprehensive picture of their readiness for DH data curation management.

This study provides insight into strategies for developing DH data curation activities in institutional repositories. It also highlights the need for professional development for curators so they can devise and implement stronger ownership policies and data privacy to support a data-driven research agenda.

This study describes the preparations that must be considered by institutional repositories in the development of DH data curation activities.

This paper aims to delve into the critical examination of retractions in virology to identify the underlying factor that led to the retraction of scientific publications in this specialised domain. Further, this study offers insights into the impact of the retracted publications in the scholarly world vis-à-vis citation and Altmetric indicators.

The top 100 highly cited retracted articles from virology category were taken from the Web of Science (WoS) database. The Retraction Watch database was used for knowing the reasons for retraction for each retracted publication. The citation and Altmetric score of retracted publications were noted down from WoS and Altmetric.com databases, respectively. Journal Citation Report was used to note down the impact factor of the journals that have published these articles.

“Misconduct” (57.73%) is the most prevalent reason for the retraction of publications followed by plagiarism (18.55%) and journal issues (14.43%). The retracted papers are cited even after their retraction. Around 70.52% citations were received before and 29.47% after retraction. The highest number of retracted papers was published in the Journal of Virology (14) and Journal of Chemistry (10). High-impact factor journals such as Lancet, Cell and Nature each own one retracted paper. The study found dissemination of these publications through social media platforms with highest social media mentions (394) followed by policy and patents mentions (373) and news and blog mentions (300).

The research delves into understanding the reasons behind the retraction of virology papers and the impact of these publications through citation and Altmetric analyses. Its impactions include bolstering quality control in virology research, maintaining trust in scientific literature. Citation and Altmetric analyses offer deep insights into the broader impact of retracted papers, informing policy and publishing practices to uphold scientific integrity in virology.

This study addresses a specific and crucial aspect of scientific research retractions within the field of virology. While retractions have been studied in broader terms in scientific research, to the best of the authors’ knowledge, no such study has been conducted in the scientific field of virology.

A major obstacle regarding the measurement of an organization's sustainability and accountability in the space economy is defining the context and boundaries of commercial activity in outer space. Here, we introduce an ecosystem framework to address this obstacle. We utilize this framework to analyze the space mining sector. Our ecosystem framework sets the space mining sector's boundaries and helps a firm identify key stakeholders, activities, policies, norms and common pool resources in that sector and the interactions between them; a significant step in structuring how to measure space sustainability and accountability.

Borrowing theories and perspectives from a wide range of academic fields, this paper conducts a comprehensive context analysis of the space mining ecosystem.

Using our ecosystem framework to define the context and set boundaries for the space mining sector allowed us to identify sustainability-related issues in the sector and offer roadmaps to develop sustainability measures and standards.

To the best of the authors’ knowledge, this is one of the first papers to introduce a framework to define boundaries in the global space economy and provides a tool to understand, measure and evaluate the space mining sector's environmental, social and economic issues.

This paper aims to analyze the relationships between discourse leading indicators and citations from perspectives of integrating altmetrics indicators and tries to provide references for comprehending the quantitative indicators of scientific communication in the era of open science, constructing the evaluation indicator system of the discourse leading for academic journals and then improving the discourse leading of academic journals.

Based on the theory of communication and the new pattern of scientific communication, this paper explores the formation process of academic journals' discourse leading. This paper obtains 874,119 citations and 6,378,843 altmetrics indicators data from 65 international multidisciplinary academic journals. The relationships between indicators of discourse leading (altmetrics) and citations are studied by using descriptive statistical analysis, correlation analysis, principal component analysis, negative binomial regression analysis and marginal effects analysis. Meanwhile, the connotation and essential characteristics of the indicators, the strength and influence of the relationships are further analyzed and explored. It is proposed that academic journals' discourse leading is composed of news discourse leading, social media discourse leading, peer review discourse leading, encyclopedic discourse leading, video discourse leading and policy discourse leading.

It is discovered that the 15 altmetrics indicators data have a low degree of centralization to the center and a high degree of polarization dispersion overall; their distribution patterns do not follow the normal distributions, and their distributions have the characteristics of long-tailed right-peaked curves. Overall, 15 indicators show positive correlations and wide gaps exist in the number of mentions and coverage. The academic journals' discourse leading significantly affects total cites. When altmetrics indicators of international mainstream academic and social media platforms are used to explore the connotation and characteristics of academic journals' discourse leading, the influence or contribution of social media discourse, news discourse, video discourse, policy discourse, peer review discourse and encyclopedia discourse on the citations decreases in turn.

This study is innovative from the academic journal level to analyze the deep relationships between altmetrics indicators and citations from the perspective of correlation. First, this paper explores the formation process of academic journals' discourse leading. Second, this paper integrates altmetrics indicators to study the correlation between discourse leading indicators and citations. This study will help to enrich and improve basic theoretical issues and indicators’ composition, provide theoretical support for the construction of the discourse leading evaluation system for academic journals and provide ideas for the evaluation practice activities.

This study investigates differences and commonalities in data production, sharing and reuse across the widest range of disciplines yet and identifies types of improvements needed to promote data sharing and reuse.

The first authors of randomly selected publications from 2018 to 2019 in 20 Scopus disciplines were surveyed for their beliefs and experiences about data sharing and reuse.

From the 3,257 survey responses, data sharing and reuse are still increasing but not ubiquitous in any subject area and are more common among experienced researchers. Researchers with previous data reuse experience were more likely to share data than others. Types of data produced and systematic online data sharing varied substantially between subject areas. Although the use of institutional and journal-supported repositories for sharing data is increasing, personal websites are still frequently used. Combining multiple existing datasets to answer new research questions was the most common use. Proper documentation, openness and information on the usability of data continue to be important when searching for existing datasets. However, researchers in most disciplines struggled to find datasets to reuse. Researchers' feedback suggested 23 recommendations to promote data sharing and reuse, including improved data access and usability, formal data citations, new search features and cultural and policy-related disciplinary changes to increase awareness and acceptance.

This study is the first to explore data sharing and reuse practices across the full range of academic discipline types. It expands and updates previous data sharing surveys and suggests new areas of improvement in terms of policy, guidance and training programs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2021-0423.