Journal of Librarianship and Information Science, Ahead of Print.
Overlay journals are characterised by their articles being published on open access repositories, often already starting in their initial preprint form as a prerequisite for submission to the journal prior to initiating the peer-review process. In this study we aimed to identify currently active overlay journals and examine their characteristics. We utilised an explorative web search and contacted key service providers for additional information. The final sample consisted of 34 overlay journals. While the results show that new overlay journals have been actively established within recent years, the current presence of overlay journals remains diminutive compared to the overall number of open access journals. Most overlay journals publish articles in natural sciences, mathematics or computer sciences, and are commonly published by groups of academics rather than formal organisations. They may also rank highly within the traditional journal citation metrics. None of the investigated journals required fees from authors, which is likely related to the cost-effective aspects of the overlay publishing model. Both the growth in adoption of open access preprint repositories and researchers’ willingness to publish in overlay journals will determine the model’s wider impact on scholarly publishing.
Author Archives: Antti Mikael Rousi
Overlay journals: A study of the current landscape
Journal of Librarianship and Information Science, Volume 56, Issue 1, Page 15-28, March 2024.
Overlay journals are characterised by their articles being published on open access repositories, often already starting in their initial preprint form as a prerequisite for submission to the journal prior to initiating the peer-review process. In this study we aimed to identify currently active overlay journals and examine their characteristics. We utilised an explorative web search and contacted key service providers for additional information. The final sample consisted of 34 overlay journals. While the results show that new overlay journals have been actively established within recent years, the current presence of overlay journals remains diminutive compared to the overall number of open access journals. Most overlay journals publish articles in natural sciences, mathematics or computer sciences, and are commonly published by groups of academics rather than formal organisations. They may also rank highly within the traditional journal citation metrics. None of the investigated journals required fees from authors, which is likely related to the cost-effective aspects of the overlay publishing model. Both the growth in adoption of open access preprint repositories and researchers’ willingness to publish in overlay journals will determine the model’s wider impact on scholarly publishing.
Overlay journals are characterised by their articles being published on open access repositories, often already starting in their initial preprint form as a prerequisite for submission to the journal prior to initiating the peer-review process. In this study we aimed to identify currently active overlay journals and examine their characteristics. We utilised an explorative web search and contacted key service providers for additional information. The final sample consisted of 34 overlay journals. While the results show that new overlay journals have been actively established within recent years, the current presence of overlay journals remains diminutive compared to the overall number of open access journals. Most overlay journals publish articles in natural sciences, mathematics or computer sciences, and are commonly published by groups of academics rather than formal organisations. They may also rank highly within the traditional journal citation metrics. None of the investigated journals required fees from authors, which is likely related to the cost-effective aspects of the overlay publishing model. Both the growth in adoption of open access preprint repositories and researchers’ willingness to publish in overlay journals will determine the model’s wider impact on scholarly publishing.
Using current research information systems to investigate data acquisition and data sharing practices of computer scientists
Journal of Librarianship and Information Science, Volume 55, Issue 3, Page 596-608, September 2023.
Without sufficient information about research data practices occurring in a particular research organisation, there is a risk of mismatching research data service efforts with the needs of its researchers. This study describes how data acquiring and data sharing occurring within a particular research organisation can be investigated by using current research information system publication data. The case study organisation’s current research information system was used to identify the sample of investigated articles. A sample of 193 journal articles published by researchers in the computer science department of the case study’s university during 2019 were extracted for scrutiny from the current research information system. For these 193 articles, a classification of the main study types was developed to accommodate the multidisciplinary nature of the case department’s research agenda. Furthermore, a coding framework was developed to capture the key elements of data acquiring and data sharing. The articles representing life sciences and computational research relatively frequently reused open data, whereas data acquisition of experimental research, human interaction studies and human intervention studies often relied on collecting original data. Data sharing also differed between the computationally intensive study types of life sciences and computational research and the study types relying on collection of original data. Research data were not available for reuse in only a minority of life science (n = 2; 7%) and computational research (n = 15; 14%) studies. The study types of experimental research, human interaction studies and human intervention studies less frequently made their data available for reuse. The findings suggest that research organisations representing computer sciences may include different subfields that have their own cultures of data sharing. This study demonstrates that analyses of publications listed in current research information systems provide detailed descriptions how the affiliated researchers acquire and share research data.
Without sufficient information about research data practices occurring in a particular research organisation, there is a risk of mismatching research data service efforts with the needs of its researchers. This study describes how data acquiring and data sharing occurring within a particular research organisation can be investigated by using current research information system publication data. The case study organisation’s current research information system was used to identify the sample of investigated articles. A sample of 193 journal articles published by researchers in the computer science department of the case study’s university during 2019 were extracted for scrutiny from the current research information system. For these 193 articles, a classification of the main study types was developed to accommodate the multidisciplinary nature of the case department’s research agenda. Furthermore, a coding framework was developed to capture the key elements of data acquiring and data sharing. The articles representing life sciences and computational research relatively frequently reused open data, whereas data acquisition of experimental research, human interaction studies and human intervention studies often relied on collecting original data. Data sharing also differed between the computationally intensive study types of life sciences and computational research and the study types relying on collection of original data. Research data were not available for reuse in only a minority of life science (n = 2; 7%) and computational research (n = 15; 14%) studies. The study types of experimental research, human interaction studies and human intervention studies less frequently made their data available for reuse. The findings suggest that research organisations representing computer sciences may include different subfields that have their own cultures of data sharing. This study demonstrates that analyses of publications listed in current research information systems provide detailed descriptions how the affiliated researchers acquire and share research data.