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This study aims to examine the current status and different characteristic features of research data repositories established by BRICS nations in order to understand the research data infrastructure within BRICS countries.

The data were collected from the re3data repository (http://www.re3data.org/), focusing specifically on BRICS nations. The data were analyzed to grasp the current status of research data repositories in BRICS countries. The dataset was retrieved on March 2, 2024. A total of 195 Research Data Repositories (RDRs) originating from BRICS countries were identified and selected for comprehensive analysis.

As of March 2, 2024, re3data.org indexes a total of 3,192 Research Data Repositories (RDRs) worldwide, with BRICS nations contributing 195. China leads among BRICS nations, followed by India, Russia, and Brazil. Scientific and Statistical Formats are the most shared content categories, followed closely by Standard Office Documents. There is notable diversity in the subjects covered by RDRs across BRICS nations. English is the primary interface language, followed by Chinese and Portuguese. “House, tailor-made” software is widely used for creating RDRs, followed by Dataverse and DSpace. Fourteen metadata standards are found, with Dublin Core metadata being the most prevalent, followed by the DataCite Metadata Scheme. Most repositories are disciplinary, followed by institutional ones. Most repositories specify data upload types, with “restricted” being the most common, followed by closed types. Open access is predominant in data access, followed by restricted access and embargo periods, while a small number restrict access entirely.

The present study will help gauge the strengths and weaknesses of the RDRs of BRICS nations and also learn how open these RDRs are for data access and upload provisions. The study contributes to a broader comprehension of the accessibility and usability of research data within the BRICS community, ultimately fostering greater transparency, collaboration, and knowledge dissemination within the scientific community, thus fostering greater innovation and advancement in research endeavors. The study provides a nuanced understanding of the research data infrastructure within BRICS nations, highlighting key trends, strengths, and areas for potential improvement.

This paper aims to assess the relationship between energy poverty and the well-being of people using Amartya Sen’s capability approach to development as theoretical underpinning.

The study uses household-level energy access data collected by the Harvard Dataverse in 2015 and 2018. The authors use multidimensional indices to measure energy poverty and well-being. Further, the authors apply quantile regression approach to measure the relationship between energy poverty and well-being.

The study’s findings reveal that energy poverty and well-being are negatively related. India has made progress in reducing energy poverty and improving well-being during the study period. However, progress in reducing energy poverty is largely due to improved access to electricity and improvement in well-being due to income and financial inclusion. Using modern cooking fuel has a greater negative impact on well-being compared to lighting using electricity. Further, households spending a greater proportion of their income on modern energy fuels leads to a lower quality of life as it precludes them from using it for other purposes. The study records wide variations in the observed relationship between energy poverty and well-being across various socioeconomic groups.

This calls for improvement in the production and distribution of modern energy resources, which have substantial welfare implications.

This is the first study to measure the relationship between energy poverty and quality of life using multidimensional indices. The findings of this paper have policy implications for the pricing of energy resources and energy access measures.

Data sharing is increasingly being recognized as an essential component of scholarly research and publishing. Sharing data improves results and propels research and discovery forward. Given the importance of data sharing, the purpose of the study is to unveil the present scenario of research data repositories (RDR) and sheds light on strategies and tactics followed by different countries for efficient organization and optimal use of scientific literature.

The data for the study is collected from registry of RDR (re3data registry) (re3data.org), which covers RDR from different academic disciplines and provides filtration options “Search” and “Browse” to access the repositories. Using these filtration options, the researchers collected metadata of repositories i.e. country wise contribution, content-type data, repository language interface, software usage, metadata standards and data access type. Furthermore, the data was exported to Google Sheets for analysis and visualization.

The re3data registry holds a rich and diverse collection of data repositories from the majority of countries all over the world. It is revealed that English is the dominant language, and the most widely used software for the creation of data repositories are “DataVerse”, followed by “Dspace” and “MySQL”. The most frequently used metadata standards are “Dublin Core” and “Datacite metadata schema”. The majority of repositories are open, with more than half of the repositories being “disciplinary” in nature, and the most significant data sources include “scientific and statistical data” followed by “standard office documents”.

The main limitation of the study is that the findings are based on the data collected through a single registry of repositories, and only a few characteristic features were investigated.

The study will benefit all countries with a small number of data repositories or no repositories at all, with tools and techniques used by the top repositories to ensure long-term storage and accessibility to research data. In addition to this, the study provides a global overview of RDR and its characteristic features.

The study aims to investigate the utilisation of open research data repositories (RDRs) for storing and sharing research data in higher learning institutions (HLIs) in Tanzania.

A survey research design was employed to collect data from postgraduate students at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania. The data were collected and analysed quantitatively and qualitatively. A census sampling technique was employed to select the sample size for this study. The quantitative data were analysed using the Statistical Package for the Social Sciences (SPSS), whilst the qualitative data were analysed thematically.

Less than half of the respondents were aware of and were using open RDRs, including Zenodo, DataVerse, Dryad, OMERO, GitHub and Mendeley data repositories. More than half of the respondents were not willing to share research data and cited a lack of ownership after storing their research data in most of the open RDRs and data security. HILs need to conduct training on using trusted repositories and motivate postgraduate students to utilise open repositories (ORs). The challenges for underutilisation of open RDRs were a lack of policies governing the storage and sharing of research data and grant constraints.

Research data storage and sharing are of great interest to researchers in HILs to inform them to implement open RDRs to support these researchers. Open RDRs increase visibility within HILs and reduce research data loss, and research works will be cited and used publicly. This paper identifies the potential for additional studies focussed on this area.

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 investigate the association of COVID-19 confirmed cases and deaths with mental health, unemployment and financial markets-related search terms for the USA, the UK, India and worldwide using Google Trends.

The authors use Spearman’s rank correlation coefficients to assess the relationship between relative search volumes (RSVs) and mental health, unemployment and financial markets-related search terms, with the total confirmed COVID-19 cases as well as deaths in the USA, UK, India and worldwide. The sample period starts from the day 100 cases were reported for the first time, which is 7 March 2020, 13 March 2020, 23 March 2020 and 28 January 2020 for the US, the UK, India and worldwide, respectively, and ends on 25 June 2020.

The results indicate a significant increase in anxiety, depression and stress leading to sleeping disorders or insomnia, further deteriorating mental health. The RSVs of employment are negatively significant, implying that people are hesitant to search for new jobs due to being susceptible to exposure, imposed lockdown and social distancing measures and changing employment patterns. The RSVs for financial terms exhibit the varying associations of COVID-19 cases and deaths with the stock market, loans, rent, etc.

This study has implications for the policymakers, health experts and the government. The state governments must provide proper medical facilities and holistic care to the affected population. It may be noted that the findings of this study only lead us to conclude about the relationship between COVID-19 cases and deaths and Google Trends searches, and do not as such indicate the effect on actual behaviour.

To the best of the authors’ knowledge, this is the first attempt to investigate the relationship between the number of COVID-19 cases and deaths in the USA, UK and India and at the global level and RSVs for mental health-related, job-related and financial keywords.

The rapid spread of the COVID-19 pandemic upended societies across the world, with billions forced into lockdowns. As countries contemplated instating and rolling back lockdown measures, and considered the impact of pandemic fatigue on policy measures, and furthermore to prepare for the improved management of future pandemics, this study examines the effectiveness of policy measures in limiting the spread of infections and fatalities.

The methodological approach in the study centres on a fixed effects panel regression analysis and employs the COVID-19 Government Response Stringency Index, which comprises eight containment measures and three health campaigns, with progressive degrees of stringency, in order to investigate the efficacy of government policies.

Findings suggest that some government policies were effective at reducing implicit mortality rates, infection cases and fatalities during the first four months of the COVID-19 pandemic. Solid stringency measures to reduce mortality rates include public gathering restrictions on more than 100 attendees, and international travel limits for developed countries and islands. Fatalities can further be reduced through the closing of public transport, whereas infection cases also experience benefits from public information campaigns. Comparable results are observed in a robustness test across 12 months.

Some non-pharmaceutical policies are shown to be more effective than others at reducing the spread of infections, fatalities and mortality rates, and support policymakers to manage future pandemics more effectively.

The purpose of this study was to understand the landscape of Indian research data repositories (RDRs) indexed in the re3data.org. The study analysed the metadata elements of Indian RDRs to identify their disciplinary orientations, typology, standards adopted, foreign collaborations, etc. The study ascertained the current status of the Indian RDRs by visiting their respective websites and tried to identify and map the exact disciplinary orientation of each RDR.

The study used “content analysis” of the metadata elements extracted from re3data.org along with the information analysis of the respective websites of the registered RDRs.

The study identified that only 80% of the Indian RDRs listed by the re3data.org is currently active. Most of the Indian RDRs are hosted by the central and state governments and are almost equally distributed among Life Sciences, Natural Sciences and Social Sciences domains. The data provided by the re3data.org for the Indian RDRs are not complete and up-to-date.

The findings indicate the presence of a good number of inactive RDRs in the re3data.org. The study suggests using a revised version of the DFG subject classification scheme or considering a standard classification scheme for subject indexing.

To the best of the authors’ knowledge, this study is the first of its kind that critically analysed the metadata values extracted and moved further to identify the current status of Indian RDRs.

Italy has been the first Western Country to suffer a massive outbreak of COVID-19. Starting from the 11^th of March 2020, the Italian Government approved a series of emergency restrictive measures to limit people’s movement and social contacts. The aim of this short paper is to test if the number of norm-violations (related to people’s movement) might contribute to the peaks of new COVID-19 positives after few days. We show that peaks in the violations of the lockdown norms correspond to peaks in new positive cases about 6 days later.

In the process of making agricultural production decisions in rural households, severe weather conditions, either extreme cold or heat, may squeeze the labor input in the agricultural sector, leading to a reallocation of labor between the agricultural and non-agricultural sectors. By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, reveal the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

This study utilizes data from Chinese meteorological stations and two waves of China Household Income Project to examine the impact and behavioral mechanism of extreme temperatures on rural labor reallocation.

(1) Extremely high and low temperatures had led to a reallocation of labor force from agricultural activities to non-farm employment, with a more pronounced effect from extreme high temperature events. (2) Extreme temperatures influence famers’ decision in abandoning farmland and reducing investment in agricultural machinery, thus creating an interconnected impact on labor mobility. (3) The reallocation effect of rural labor induced by extreme temperatures is particularly evident for males, persons that perceives economic hardship or labor in economically active areas.

By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, and reveals the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.