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In earlier work dealing with Data Papers, emphasis initially focused on its definition, the construction of a standardized template in compiling its component parts, its further publication, access and data preservation1. this was followed by a study seeking to engage the citation and referencing of data papers and the further sharing and reuse of the data described therein2. a more recent work outside GreyNet's immediate community of practice3 addressed the diverse formats used to compile and publish data papers. that study also discussed the automatic generation of data papers, and the differing opinions as to whether they contribute to data, information and/or knowledge production. drawing on the results of the abovementioned work, this case study seeks to demonstrate how the data paper provides an innovative tool for information and data management, as part of an "ecosystem" of conference proceedings, journal articles, research data and open repositories. it relies upon GreyNet's current collection of 41 published datasets and 11 data papers4. this study highlights the importance of the human contribution for the writing of data papers and the enrichment of their metadata. To this end, key shared components of GreyNet's collection of data papers are discussed, namely the stakeholders, linked metadata, open data archiving, preservation, and issues of quality and information rights. The study concludes from a user perspective by addressing the value of data papers drawn from available usage statistics. The results of this study are expected to move beyond a simple case study to a use case in which the key components of data papers can be implemented in other communities of practice dealing with non-conventional 'grey' literature. [ABSTRACT FROM AUTHOR]

In earlier work dealing with Data Papers, emphasis initially focused on its definition, the construction of a standardized template in compiling its component parts, its further publication, access and data preservation1. this was followed by a study seeking to engage the citation and referencing of data papers and the further sharing and reuse of the data described therein2. a more recent work outside GreyNet's immediate community of practice3 addressed the diverse formats used to compile and publish data papers. that study also discussed the automatic generation of data papers, and the differing opinions as to whether they contribute to data, information and/or knowledge production. drawing on the results of the abovementioned work, this case study seeks to demonstrate how the data paper provides an innovative tool for information and data management, as part of an "ecosystem" of conference proceedings, journal articles, research data and open repositories. it relies upon GreyNet's current collection of 41 published datasets and 11 data papers4. this study highlights the importance of the human contribution for the writing of data papers and the enrichment of their metadata. To this end, key shared components of GreyNet's collection of data papers are discussed, namely the stakeholders, linked metadata, open data archiving, preservation, and issues of quality and information rights. The study concludes from a user perspective by addressing the value of data papers drawn from available usage statistics. The results of this study are expected to move beyond a simple case study to a use case in which the key components of data papers can be implemented in other communities of practice dealing with non-conventional 'grey' literature. [ABSTRACT FROM AUTHOR]

The number of studies investigating the effects of ocean acidification on marine organisms and communities increases every year. Results are not easily comparable since the carbonate chemistry and ancillary data are not always reported in similar units and scales and are not calculated using similar sets of constants. To facilitate data comparison, a data compilation hosted by the PANGAEA Data Publisher was initiated in 2008 and is updated on a regular basis (10.1594/PANGAEA.962556; Ocean Acidification International Coordination Centre (OA-ICC), 2023). By November 2023, a total of 1501 datasets (over 25 million data points) from 1554 papers had been archived. To easily filter and access relevant biological response data from this compilation, a user-friendly portal (https://oa-icc.ipsl.fr , last access: 9 November 2023) was launched in 2018. Here, we present an update of this data compilation since its second description by Yang et al. (2016) and provide an overview of the OA-ICC portal for ocean acidification biological response data, launched in 2018. Most of the study sites from which data have been archived are in the North Atlantic Ocean, North Pacific Ocean, South Pacific Ocean, and Mediterranean Sea, while polar oceans are still relatively poorly represented. Mollusca and Cnidaria are still the best-represented taxonomic groups. The biological processes most reported in the datasets are growth and morphology. Other variables that can potentially be affected by ocean acidification and are often reported include calcification/dissolution, primary production/photosynthesis, and biomass/abundance. The majority of the compiled datasets have considered ocean acidification as a single stressor, but their relative contribution has decreased from 68 % before 2015 to 57 % today, showing a clear tendency towards more data archived from multifactorial studies. [ABSTRACT FROM AUTHOR]

The article discusses the importance of reproducibility in academic research, particularly in the field of structural engineering. It acknowledges the challenges in achieving reproducibility, such as data storage and computing requirements, as well as proprietary issues. The authors argue for the development of a reproducibility policy in the Journal of Structural Engineering and the Journal of Bridge Engineering, taking into account the nature and culture of research in these subdisciplines. They propose a classification system that emphasizes the availability of data and metadata, and encourage authors to go beyond data availability by making models and other materials accessible. To incentivize research and data availability, the journals will provide a visible recognition badge for papers with open data/models/codes and may consider special recognition for these papers. The authors also outline the review process for data-verified papers, which involves three associate editors verifying the availability and representativeness of the data. [Extracted from the article]

This article discusses the importance of reproducibility in academic research, specifically in the field of bridge engineering. The authors argue that reproducibility is challenging due to factors such as paper documentation, technology constraints, and proprietary issues. They propose implementing a policy that encourages researchers to make their data and models available to others, although they acknowledge that full reproducibility may not always be practical. To incentivize this practice, the Journal of Bridge Engineering plans to introduce a visible recognition badge for papers that provide open data, models, and codes. The authors also outline the review process for papers seeking the "Data Verified Paper" designation. [Extracted from the article]

Background Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability. Objective We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript. Methods An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases. Findings The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing. Conclusion The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility. [ABSTRACT FROM AUTHOR]

Purpose – This study aims to examine a comparative analysis of electronic- and paper-based data collection methods. Design/methodology/approach – Survey research approach was adopted to conduct the study. A total of 500 library and information science (LIS) researcher/information professionals selected randomly from seven states in Nigeria represent the sample for the study. A self-designed questionnaire was used to gather data from the respondents. Six objectives were developed to guide the study. Findings – The findings reveal that there is preference for paper-based than the electronic-based data collection methods, and similarly, respondents indicated they cannot use any other data collection methods other than paper-based. Electronic data collection method is beneficial in terms of gathering a representative sample within a short period compared to the paper-based method. The researcher has control over access to the survey in the paper-based method compared to the electronic method, and there is opportunity to monitor the progress of the research and clarify ambiguity by the researcher. The electronic method is limited in terms of collecting data from only the respondents who are computer-literate with good Web skills, while the paper-based method is limited by higher attrition rate, money and time consumption. Research limitations/implications – The study did not consider the time needed to gather data with each method or the amount of time needed for data entry, cleaning and coding. It is possible that a time-motion study would reveal clear superiority of either one method or the other. The total sample of participants in the study is also limited, considering the total number of LIS researcher/information professionals in Nigeria. Practical implications – The study has underlined the value of electronic/Web-based collection as a cost- and time-saving instrument in modern LIS research. Regardless of method and trial, electronic data collection could fulfill in all examined parameters, its promises, realizing cost savings of up to a 50 per cent in comparison with the paper-based data collection method. Originality/value – The paper is solely the idea of the author. [ABSTRACT FROM AUTHOR]

We attempted to replicate 67 macroeconomic papers using author-provided data and code files by following a preanalysis plan. Excluding 6 papers that used confidential data, we obtained data and code replication files for 29 of 35 papers (83 percent) that were required to provide such files as a condition of publication, compared to 11 of 26 papers (42 percent) that were not required to provide such files. Also excluding the 2 papers that used software we did not possess, we replicated 29 of 59 papers (49 percent) with assistance from the authors. We conclude with recommendations on improving replication of economics research. [ABSTRACT FROM AUTHOR]

This article reports on my attempt to replicate Sachs and Warner’s 1995 and 1997 resource curse working papers. The 1995 paper is not replicable for lack of a data archive. Pure replication of the 1997 paper is achieved. Statistical replication determines that the proposed institutional causes of the resource curse are not robust to country sample. Scientific replication shows that findings of a resource curse are not sensitive to different measures of resource intensiveness, though they are sensitive to estimation technique. Typographical errors in the published paper reveal the value of researchers making both their data and code available. [ABSTRACT FROM PUBLISHER]

In this article we study three types of uncitedness in Library and Information Science journals: uncitedness for articles, authors and topics. One important aspect in this study is giving accurate definitions of the indicators for measuring uncited papers, uncited authors and uncited topics. It is found that for the period 1991–2010 ratios of uncited papers fluctuate within the interval [0,0.1]. This ratio is relatively stable and not very high. Comparison of average number of pages, average number of references, average number of authors per paper and percentage of single-authored papers between cited and uncited papers shows that no matter the journal, the first three indicators’ values for uncited papers are lower, while the values of the fourth indicator are higher, than the corresponding values for cited papers. The fact that almost all uncited authors in a journal published only one paper in this journal illustrates that a journal's uncited authors are the least productive authors in this journal. Yet, productive and highly cited authors also publish uncited papers. As to why some topics fall into the group of uncited topics, the hypothesis is that the combination of unfamiliar keywords forms an unfamiliar topic, a topic authors have elected not to study further. Another assumption is that some uncited topics fall outside the field of Library and Information Science. Retrieval results in the Web of Science for a set of uncited keywords and keyword combinations support this assumption. [ABSTRACT FROM AUTHOR]

Science funders, publishers, and data archives make decisions about how to responsibly allocate resources to maximize the reuse potential of research data. This paper introduces a dataset developed to measure the impact of archival and data curation decisions on data reuse. The dataset describes 10,605 social science research datasets, their curation histories, and reuse contexts in 94,755 publications that cover 59 years from 1963 to 2022. The dataset was constructed from study-level metadata, citing publications, and curation records available through the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan. The dataset includes information about study-level attributes (e.g., PIs, funders, subject terms); usage statistics (e.g., downloads, citations); archiving decisions (e.g., curation activities, data transformations); and bibliometric attributes (e.g., journals, authors) for citing publications. This dataset provides information on factors that contribute to long-term data reuse, which can inform the design of effective evidence-based recommendations to support high-impact research data curation decisions. [ABSTRACT FROM AUTHOR]

Copyright of Arachnology Letters / Arachnologische Mitteilungen is the property of Arachnologische Gesellschaft e.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Semantic Web in general and the Linked Open Data Initiative, in particular, are a growing movement for organisations to make their existing data available in a machine-readable format. Thus, institutions are highly encouraged to publish, share and interlink their data publicly. The more data are opened on the Web (Open Data), the more integrated sets of data will be connected in the Semantic Web (Linked Open Data). Within this context, libraries can complement their data by linking it to other, external data sources. The purpose of this article is to identify papers that refer to linked data in libraries, emphasising the ways that linked data empower libraries to put their knowledge in the context of the open-world, thus enhancing semantic technology innovations. The study considered papers published between 2008 and 2019 in English and presents the collected literature by grouping it according to the topic each paper refers to. The results show that libraries are facing a period of continuing change which present several challenges and indicate that they are moving towards developing new practices, policies and services. [ABSTRACT FROM AUTHOR]

As large enterprises embrace Digital Transformation, it is obvious that merely scanning paper documents to digital form is inadequate to achieve their broader goals. These must be transformed into more granular data that are version controlled, configuration managed and connected - i.e., a digital thread. As a digital thread begins to span the product lifecycle, its complexity increases exponentially with the number of lifecycle phases and application areas that it encompasses. This quickly becomes intractable, given the "normal" approach to finding and presenting data in PLM platforms. The goal of creating these enormous and rapidly growing networks of data is not just to archive the data. They must empower the product teams to be productive and to make the most effective use of this dynamic data network to meet the rapidly changing goals of the corporation as it reacts to the market's needs. This requires various graphical query and visualization tools. [ABSTRACT FROM AUTHOR]

Digital reading promotion service is a service way for libraries to provide readers with a series of digital resources, enjoy the service functions, and share the experience of using them in various digital reading platforms, which is to meet the reading interests and reading needs of more readers, and is also the focus of the current library work. In the era of new media, the characteristics of digital reading are subtly changing the readers' needs for reading environment, reading content, and reading style. Libraries should keep pace with the development of the times and provide readers with diversified, intelligent, and targeted digital reading platforms. The digital reading platform should continuously improve the digital reading service functions, broaden the service scope and dissemination channels, and finally realize the diversification, interest, and intelligence of digital reading service. This paper takes the digital reading platform of libraries in the region as the research theme and carries out research work on libraries. The province is divided into three regions according to the geographical map: southeastern region, central region, and northwestern region. The digital reading platforms of 14 prefecture-level public libraries and 58 libraries of higher education institutions in each region were accessed. Firstly, we check the construction of digital resources within the library websites, secondly, we count the opening of digital reading platform functions, and finally, we check the opening of digital reading platforms. Through the research, it is found that there are problems of unbalanced distribution of digital reading resources in regional libraries; unattractive design of readers' interface and inadequate reading service functions; lack of continuous training of readers' guidance; insufficient publicity and promotion; low efficiency of staff in responding to consultation; and low degree of platform openness and weak awareness of sharing. Finally, the problems found in the research are summarized, and the solution measures for the regional digital reading platform are proposed. Libraries in the digital era should give priority to systems that can manage all library resources comprehensively and effectively, adapt to more flexible library workflows, and enable libraries to provide better services to users. [ABSTRACT FROM AUTHOR]

Version 1.1 of the editorial of Geoscientific Model Development (GMD), published in 2015 , introduced clarifications to the policy on publication of source code and input data for papers published in the journal. Three years of working with this policy has revealed that it is necessary to be more precise in the requirements of the policy and in the narrowness of its exceptions. Furthermore, the previous policy was not specific in the requirements for suitable archival locations. Best practice in code and data archiving continues to develop and is far from universal among scientists. This has resulted in many manuscripts requiring improvement in code and data availability practice during the peer-review process. New researchers continually start their professional lives, and it remains the case that not all authors fully appreciate why code and data publication is necessary. This editorial provides an opportunity to explain this in the context of GMD. The changes in the code and data policy are summarised as follows: The requirement for authors to publish source code, unless this is impossible for reasons beyond their control, is clarified. The minimum requirements are strengthened such that all model code must be made accessible during the review process to the editor and to potentially anonymous reviewers. Source code that can be made public must be made public, and embargoes are not permitted. Identical requirements exist for input data and model evaluation data sets in the model experiment descriptions. The scope of the code and data required to be published is described. In accordance with Copernicus' own data policy, we now specifically strongly encourage all code and data used in any analyses be made available. This will have particular relevance for some model evaluation papers where editors may now strongly request this material be made available. The requirements of suitable archival locations are specified, along with the recommendation that Zenodo is often a good choice. In addition, since the last editorial, an "Author contributions" section must now be included in all manuscripts. [ABSTRACT FROM AUTHOR]

This paper updates and complements a previously published evaluation of computational methods for total and partial cross sections, relevant to modeling the photoelectric effect in Monte Carlo particle transport. It examines calculation methods that have become available since the publication of the previous paper, some of which claim improvements over previous calculations; it tests them with statistical methods against the same sample of experimental data collected for the previous evaluation. No statistically significant improvements are observed with respect to the calculation method identified in the previous paper as the state of the art for the intended purpose, encoded in the EPDL97 data library. Some of the more recent computational methods exhibit significantly lower capability to reproduce experimental measurements than the existing alternatives. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos Judaicos (0718-8749) is the property of Universidad de Chile, Facultad de Filosofia y Humanidades and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ancient DNA is producing a rich record of past genetic diversity in humans and other species. However, unless the primary data is appropriately archived, its long-term value will not be fully realised. I surveyed publicly archived data from 42 recent ancient genomics studies. Half of the studies archived incomplete datasets, preventing accurate replication and representing a loss of data of potential future use. No studies met all criteria that could be considered best practice. Based on these results, I make six recommendations for data producers: (1) archive all sequencing reads, not just those that aligned to a reference genome, (2) archive read alignments too, but as secondary analysis files, (3) provide correct experiment metadata on samples, libraries and sequencing runs, (4) provide informative sample metadata, (5) archive data from low-coverage and negative experiments, and (6) document archiving choices in papers, and peer review these. Given the reliance on destructive sampling of finite material, ancient genomics studies have a particularly strong responsibility to ensure the longevity and reusability of generated data. [ABSTRACT FROM AUTHOR]

Scientific data are essential to advancing scientific knowledge and are increasingly valued as scholarly output. Understanding what drives dataset downloads is crucial for their effective dissemination and reuse. Our study, analysing 55,473 datasets from 69 data repositories, identifies key factors driving dataset downloads, focusing on interpretability, reliability, and accessibility. We find that while lengthy descriptive texts can deter users due to complexity and time requirements, readability boosts a dataset's appeal. Reliability, evidenced by factors like institutional reputation and citation counts of related papers, also significantly increases a dataset's attractiveness and usage. Additionally, our research shows that open access to datasets increases their downloads and amplifies the importance of interpretability and reliability. This indicates that easy access enhances the overall attractiveness and usage of datasets in the scholarly community. By emphasizing interpretability, reliability, and accessibility, this study offers a comprehensive framework for future research and guides data management practices toward ensuring clarity, credibility, and open access to maximize the impact of scientific datasets. [ABSTRACT FROM AUTHOR]

Franchising has played a pivotal role in driving China's economic growth in recent years. With the prominent problem of franchise asymmetry, the protection of franchisees has emerged as a significant concern. This paper conducts a comparative study of franchisee protection practices under franchising regulation in China and certain jurisdictions such as the United States, Australia, and Malaysia. This paper aims to analyze three aspects of franchisee protection, including information disclosure, registration, liability, and relief for violations. To this end, the researchers adopted library data collection methods. Franchisingrelated laws, regulations, rules, and cases are the primary data sources, while journals, books, industry reports, and network resources are the secondary data sources. The results of this study show that although China's franchisee protection is generally in line with international practice, there is still room for further improvement. The authors proposed recommendations such as strictly implementing registration requirements, introducing a disclosure exemption system, specifying the exact duration of the cooling-off period, and diversifying dispute resolution. The contribution of this paper is to learn from the advanced experience of foreign franchisee protection and improve the current franchisee protection system in China. [ABSTRACT FROM AUTHOR]

Accounting and finance are intricately intertwined with the global quest for environmental sustainability by applying accounting and finance tools for carbon reduction initiatives. Clean energy financial investment is one of the many alternative tools through which accounting contributes to carbon reduction. Accordingly, this paper analysed the impact of separate and integrated clean energy investment alternatives on carbon reduction. Data on clean energy financial investment and carbon emission per capita were collected from the International Energy Agency (IEA) and Our World in Data archives, respectively. Data was analysed by using multiple pooled OLS to evaluate the impact of individual clean energy financial investments on carbon reduction and the impact of integrating the various clean energy financial investment alternatives on carbon reduction separately. Findings show that individual clean energy financial investments may not separately offer desired carbon reduction, hence, albeit some negative coefficients, individual clean investments showed no significant impact on carbon reduction. However, furthering the test by pooling all the clean energy financial investment alternatives shows a significant negative effect of clean energy financial investment on carbon reduction at a P-value of 0.05. This shows that an integration of different alternatives of clean energy financial investment may offer an enhanced reduction of carbon emission, which outweighs the effect of relying on a single clean energy investment alternative. The findings offer significant insight for policy makers' future strategies towards a combination of multiple clean energy financial investments. Furthermore, the findings from this paper are a further testament that accounting and finance are connected with the global quest for environmental sustainability through the application of accounting and financial investment tools in conducting clean energy financial investment. [ABSTRACT FROM AUTHOR]

To store voluminous data of the enterprises and organizations opt for cloud storage. Outsourcing data in the cloud allows many autho- rized users to access the data from different geographical locations. The service provider stores the users data in data centers at remote lo- cations. Cloud Service provides infrastructure and web services to the users retrieving an unlimited data and paying the service consumed by the user. The cryptographic primitives use digital signatures for data integrity checking on the remote data. The client is unable to download the whole data stored in data center to validate its integrity. Therefore, efficient techniques required to prove the integrity of their outsourced data with least amount of communication, and computa- tion cost. This paper describes the digital signature schemes used in auditing techniques at client and its performance. [ABSTRACT FROM AUTHOR]

The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in research findings, and developments such as the Final Data Management and Sharing Policy from the U.S. National Institutes of Health and a memorandum on increasing public access to federally funded research, issued by the U.S. Office of Science and Technology Policy. This paper explores the pivotal role of data repositories in biomedical research and open science, emphasizing their importance in managing, preserving, and sharing research data. Our objective is to familiarize readers with the functions of data repositories, set expectations for their services, and provide an overview of methods to evaluate their capabilities. The paper serves to introduce fundamental concepts and community-based guiding principles and aims to equip researchers, repository operators, funders, and policymakers with the knowledge to select appropriate repositories for their data management and sharing needs and foster a foundation for the open sharing and preservation of research data. [ABSTRACT FROM AUTHOR]

The article discusses the importance of integrity, transparency, and accessibility in publishing research in the field of developmental biology. It highlights the need for open exchange of data, materials, and methods, as well as maximum transparency in reporting research results. The journal, Development, upholds high standards for data and materials presentation and availability, and encourages authors to provide access to 'omic data and follow guidelines for reporting animal research, sex/gender equity, and stem cell research. The article also outlines specific requirements for data transparency and integrity, such as using appropriate graphs and providing raw images of western blots. The journal aims to promote best practices in data presentation and reporting to ensure the usefulness of published papers for readers. [Extracted from the article]

The article "Editors' notes: Assessing needs and developing solutions" is from the IASSIST Quarterly journal. It discusses various topics related to assessing needs and developing solutions in the field of data management. The article highlights papers that introduce tools developed by different institutions to address operational challenges. These tools include a self-assessment checklist for data repositories, a method to identify needs and challenges faced by members of the World Data System and Canadian CoreTrustSeal Pilot, national surveys to gauge institutions' readiness for developing research data management strategies, and a controlled vocabulary for mapping social sciences survey variables. Additionally, the article describes a project that digitized a collection of old Yoruba newspapers in Nigeria to preserve their historical value. [Extracted from the article]

Purpose: Many libraries and archives maintain collections of research documents, such as administrative records, with paper-based formats that limit the documents' access to in-person use. Digitization transforms paper-based collections into more accessible and analyzable formats. As collections are digitized, there is an opportunity to incorporate deep learning techniques, such as Document Image Analysis (DIA), into workflows to increase the usability of information extracted from archival documents. This paper describes the authors' approach using digital scanning, optical character recognition (OCR) and deep learning to create a digital archive of administrative records related to the mortgage guarantee program of the Servicemen's Readjustment Act of 1944, also known as the G.I. Bill. Design/methodology/approach: The authors used a collection of 25,744 semi-structured paper-based records from the administration of G.I. Bill Mortgages from 1946 to 1954 to develop a digitization and processing workflow. These records include the name and city of the mortgagor, the amount of the mortgage, the location of the Reconstruction Finance Corporation agent, one or more identification numbers and the name and location of the bank handling the loan. The authors extracted structured information from these scanned historical records in order to create a tabular data file and link them to other authoritative individual-level data sources. Findings: The authors compared the flexible character accuracy of five OCR methods. The authors then compared the character error rate (CER) of three text extraction approaches (regular expressions, DIA and named entity recognition (NER)). The authors were able to obtain the highest quality structured text output using DIA with the Layout Parser toolkit by post-processing with regular expressions. Through this project, the authors demonstrate how DIA can improve the digitization of administrative records to automatically produce a structured data resource for researchers and the public. Originality/value: The authors' workflow is readily transferable to other archival digitization projects. Through the use of digital scanning, OCR and DIA processes, the authors created the first digital microdata file of administrative records related to the G.I. Bill mortgage guarantee program available to researchers and the general public. These records offer research insights into the lives of veterans who benefited from loans, the impacts on the communities built by the loans and the institutions that implemented them. [ABSTRACT FROM AUTHOR]

• This paper utilizes novel connected vehicle (CV) emulated data to predict real-time crash potential for arterials. • The CV emulated data are flexible to obtain. Different speed-related variables are estimated based on the CV emulated data to depict continuous traffic conditions • The results proved the feasibility of using CV emulated data for real-time crash potential prediction • The proposed methods can be applied to other types of vehicles Real-time crash potential prediction could provide valuable information for Active Traffic Management Systems. Fixed infrastructure-based vehicle detection devices were widely used in the previous studies to obtain different types of data for crash potential prediction. However, it was difficult to obtain data in large range through these devices due to the costs of installation and maintenance. This paper introduced a novel connected vehicle (CV) emulated data for real-time crash potential prediction. Different from the fixed devices' data, CV emulated data have high flexibility and can be obtained continuously with relatively low cost. Crash and CV emulated data were collected from two urban arterials in Orlando, USA. Crash data were archived by the Signal for Analytics system (S4A), while the CV emulated data were obtained through the data collection API with a high frequency. Different data cleaning and preparation techniques were implemented, while various speed-related variables were generated from the CV emulated data. A Long Short-term Memory (LSTM) neural network was trained to predict the crash potential in the next 5−10 min. The results from the model illustrated the feasibility of using a novel CV emulated data to predict real-time crash potential. The average and 50th percentile speed were the two most important variables for the crash potential prediction. In addition, the proposed LSTM outperformed Bayesian logistics regression and XGBoost in terms of sensitivity, Area under Curve (AUC), and false alarm rate. With the rapid development of the connected vehicle systems, the results from this paper can be extended to other types of vehicles and data, which can significantly enhance traffic safety. [ABSTRACT FROM AUTHOR]

Copyright of Bibliotheksdienst is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The MET Norway Ice Service (NIS) celebrated its fiftieth year as a formal operational sea ice information provider in 2020. Prior to the 1970's, support to navigation had started off with ad-hoc observations from coastal stations on Svalbard in the 1930's, before developing as a research programme in the 1960's. Activity in the region has steadily increased, and now the NIS also supports a large number of research, tourist, and resource exploration vessels, in addition to the ice chart archive being a resource for climate change research. The Ice Service has always been at the forefront in the use of satellite Earth Observation technologies, beginning with the routine use of optical thermal infrared imagery from NASA TIROS and becoming a large user of Canadian RADARSAT-2 Synthetic Aperture Radar (SAR), and then European Copernicus Sentinel-1, in the 2000's and 2010's. Initially ice charts were a weekly compilation of ice information using cloud-free satellite coverage, aerial reconnaissance, and in situ observations, drawn on paper at the offices of the Norwegian Meteorological Institute (MET Norway) in Oslo. From 1997 production moved to the Tromsø office using computer-based Geographical Information System (GIS) software and the NIS developed the ice charting system Bifrost. This allowed the frequency of production to be increased to every weekday, with a greater focus on detailed sea ice concentrations along the ice edge and coastal zones in Eastern Greenland and in the Svalbard fjords. From 2010, the NIS has also provided a weekly austral summer ice chart for the Weddell Sea and Antarctic Peninsula. To further develop its capabilities, NIS engages in a number of national and international research projects and led the EU Horizon 2020 project, Key Environmental monitoring for Polar Latitudes and European Readiness (KEPLER). This paper summarises the overall mandate and history of the NIS, and its current activities including the current state of routine production of operational ice charts at the NIS for maritime safety in both the Arctic and Antarctic, and future development plans. [ABSTRACT FROM AUTHOR]

In identifying the status of cloud computing in a state of sustainability in terms of contribution and impact of cloud computing, the authors have gathered articles and journals and applied different methods to achieve the purpose of the study. The author hopes to identify the dominant challenges or issues that data centers have faced today in achieving cloud sustainability, specifically in the context of promoting greener practices within companies. Furthermore, the study will try to evaluate how cloud computing technologies help businesses in economics, environment, and social systems, also focusing on their environmental impact reduction strategies. Lastly, assessing the Gartner Hype Cycle for 2023, particularly to Cloud Sustainability, exploring when cloud sustainability is expected to reach its plateau of productivity, which is projected to occur within 2 to 5 years from the current timeframe. The study used a qualitative analysis framework that focuses on collecting data through experiences, opinions, and ideas related to the topic. Further, the author used thematic analysis to deeply understands the collected data systematically. Lastly, the author used mind mapping to provide a visual presentation and easily categorized the collected data. The paper discussed the contribution and advantages of cloud computing in economics, environment, and social systems. Furthermore, it also identified challenges and issues of data centers that offer cloud services. Thus, Data Centers are now starting to address these issues and this paper discusses all possible solutions that data centers are now starting to implement. Moreover, to support this argument this paper cited top 5 data center companies promoting sustainability. The authors conclude cloud computing contributes to all businesses enhancing their efficiency and competitiveness in the market. Further, cloud computing helps other technologies to enhance their capacity. However, since there is no 100% perfect technology there are implication in cloud computing. Thus, businesses and data centers provide solutions and keep on improving and capacitate these solutions to achieve sustainability. [ABSTRACT FROM AUTHOR]

Industrial control terminals play an important role in industrial control scenarios. Due to the special nature of industrial control networks, industrial control terminal systems are vulnerable to malicious attacks, which can greatly threaten the stability and security of industrial production environments. Traditional security protection methods for industrial control terminals have coarse detection granularity, and are unable to effectively detect and prevent attacks, lacking real-time responsiveness to attack events. Therefore, this paper proposes a real-time dynamic credibility evaluation mechanism based on program behavior, which integrates the matching and symmetry ideas of credibility evaluation. By conducting a real-time dynamic credibility evaluation of function call sequences and system call sequences during program execution, the credibility of industrial control terminal application program behavior can be judged. To solve the problem that the system calls generated during program execution are unstable and difficult to measure, this paper proposes a partition-based dynamic credibility evaluation method, dividing program behavior during runtime into function call behavior and system call behavior within function intervals. For function call behavior, a sliding window-based function call sequence benchmark library construction method is proposed, which matches and evaluates real-time measurement results based on the benchmark library, thereby achieving symmetry between the benchmark library and the measured data. For system call behavior, a maximum entropy system call model is constructed, which is used to evaluate the credibility of system call sequences. Experiment results demonstrate that our method performs better in both detection success rate and detection speed compared to the existing methods. [ABSTRACT FROM AUTHOR]

The Journal of Fish and Wildlife Management is a peer-reviewed journal that publishes original scientific papers on the conservation and management of native North American fish, wildlife, plants, and their habitats. The journal accepts articles, notes, surveys, and issues and perspectives that directly relate to North American species or conservation issues. The content of the journal is in the public domain and can be reproduced or copied without permission, with citation of the source requested. The journal is indexed by various databases and is freely available through multiple search tools. The papers published in the journal contain a disclaimer stating that the views expressed are those of the authors and do not necessarily represent the views of the U.S. Fish and Wildlife Service. The journal also has a data archiving policy that requires supporting data for published papers to be publicly available. There are no fees to publish or access papers in the journal. The journal is edited by John K. Wenburg and has a team of associate editors from various institutions. The front cover of the journal features a photo of a male Cerulean Warbler. [Extracted from the article]

OpenGrey, System for Information on Grey Literature in Europe, is your open access to 1 014 872 bibliographic references of grey literature produced in Europe and allows you to export records and locate the documents. Examples of grey (gray) literature include technical and research reports, doctoral dissertations, conference papers, official publications, and other types of grey literature. In 1980, this information resource first began as a bibliographic database under the name SIGLE. In 2006, the records migrated to OpenSIGLE - an open access database. In 2010 its name was changed to the OpenGrey Repository given that full-texts documents began to be ingested and preserved. And in 2020, Inist-CNRS (service provider) gave notice that OpenGrey will be discontinued. In order to guarantee open access to this resource, it is now archived as a database in DANS EASY - a data archive certified with the Nestor and CoreTrustSeal. [ABSTRACT FROM AUTHOR]

Engineering design has proven to be a rich context for applying artificial intelligence (AI) methods, but a categorization of such methods applied in AI-based design research works seems to be lacking. This paper presents a focused literature review of AI-based methods mapped to the different stages of the engineering design process and describes how these methods assist the design process. We surveyed 108 AI-based engineering design papers from peer-reviewed journals and conference proceedings and mapped their contribution to five stages of the engineering design process. We categorized seven AI-based methods in our dataset. Our literature study indicated that most AI-based design research works are targeted at the conceptual and preliminary design stages. Given the open-ended, ambiguous nature of these early stages, these results are unexpected. We conjecture that this is likely a result of several factors, including the iterative nature of design tasks in these stages, the availability of open design data repositories, and the inclination to use AI for processing computationally intensive tasks, like those in these stages. Our study also indicated that these methods support designers by synthesizing and/or analyzing design data, concepts, and models in the design stages. This literature review aims to provide readers with an informative mapping of different AI tools to engineering design stages and to potentially motivate engineers, design researchers, and students to understand the current state-of-the-art and identify opportunities for applying AI applications in engineering design. [ABSTRACT FROM AUTHOR]

This systematic review synthesised existing research papers that explore the available metadata standards to enable researchers to preserve, discover, and reuse research data in repositories. This review provides a broad overview of certain aspects that must be taken into consideration when creating and assessing metadata standards to enhance research data preservation discoverability and reusability strategies. Research papers on metadata standards, research data preservation, discovery and reuse, and repositories published between January 2003 and April 2023 were reviewed from a total of five databases. The review retrieved 1597 papers, and 13 papers were selected in this review. We revealed 13 research articles that explained the creation and application of metadata standards to enhance preservation, discovery, and reuse of research data in repositories. Among them, eight presented the three main types of metadata, descriptive, structural, and administrative, to enable the preservation of research data in data repositories. We noted limited evidence on how these metadata standards can be used to enhance the discovery and reuse of research data in repositories to enable the preservation, discovery, and reuse of research data in repositories. No reviews indicated specific higher education institutions employing metadata standards for the research data created by their researchers. Repository designs and a lack of expertise and technology know-how were among the challenges identified from the reviewed papers. The review has the potential to influence professional practice and decision-making by stakeholders, including researchers, students, librarians, information communication technologists, data managers, private and public organisations, intermediaries, research institutions, and non-profit organizations. [ABSTRACT FROM AUTHOR]

The ability to auto-generate databases of optical properties holds great potential for advancing optical research, especially with regards to the data-driven discovery of optical materials. An optical property database of refractive indices and dielectric constants is presented, which comprises a total of 49,076 refractive index and 60,804 dielectric constant data records on 11,054 unique chemicals. The database was auto-generated using the state-of-the-art natural language processing software, ChemDataExtractor, using a corpus of 388,461 scientific papers. The data repository offers a representative overview of the information on linear optical properties that resides in scientific papers from the past 30 years. Public availability of these data will enable a quick search for the optical property of certain materials. The large size of this repository will accelerate data-driven research on the design and prediction of optical materials and their properties. To the best of our knowledge, this is the first auto-generated database of optical properties from a large number of scientific papers. We provide a web interface to aid the use of our database. Measurement(s) refractive indices • dielectric constants Technology Type(s) natural language processing [ABSTRACT FROM AUTHOR]

A Clinical Data Repository (CDR) is a dynamic database capable of real-time updates with patients' data, organized to facilitate rapid and easy retrieval. CDRs offer numerous benefits, ranging from preserving patients' medical records for follow-up care and prescriptions to enabling the development of intelligent models that can predict, and potentially mitigate serious health conditions. While several research works have attempted to provide state-of-the-art reviews on CDR design and implementation, reviews from 2013 to 2023 cover CDR regulations, guidelines, standards, and challenges in CDR implementation without providing a holistic overview of CDRs. Additionally, these reviews need to adequately address critical aspects of CDR; development and utilization, CDR architecture and metadata, CDR management tools, CDR security, use cases, and artificial intelligence (AI) in CDR design and implementation. The collective knowledge gaps in these works underscore the imperative for a comprehensive overview of the diverse spectrum of CDR as presented in the current study. Existing reviews conducted over the past decade, from 2013 to 2023 have yet to comprehensively cover the critical aspects of CDR development, which are essential for uncovering trends and potential future research directions in Africa and beyond. These aspects include architecture and metadata, security and privacy concerns, tools employed, and more. To bridge this gap, in particular, this study conducts a comprehensive systematic review of CDR, considering critical facets such as architecture and metadata, security and privacy issues, regulations guiding development, practical use cases, tools employed, the role of AI and machine learning (ML) in CDR development, existing CDRs, and challenges faced during CDR development and deployment in Africa and beyond. Specifically, the study extracts valuable discussions and analyses of the different aspects of CDR. Key findings revealed that most architectural models for CDR are still in the theoretical phase, with low awareness and adoption of CDR in healthcare environments, susceptibility to several security threats, and the need to integrate federated learning in CDR systems. Overall, this paper would serve as a valuable reference for designing and implementing cutting-edge clinical data repositories in Africa and beyond. [ABSTRACT FROM AUTHOR]

Optimization of electrical discharge machining (EDM) processes is a critical issue due to complex material removal mechanism, presence of multiple input parameters and responses (outputs) and interactions among them and varying interest of different stakeholders with respect to relative importance assigned to the considered responses. Multi-criteria decision making (MCDM) techniques have become potent tools in solving parametric optimization problems of the EDM processes. In this paper, more than 130 research articles from SCOPUS database published during 2013-22 are reviewed extracting information with respect to experimental design plans employed, materials machined, dielectrics used, process parameters and responses considered and MCDM tools applied along with their integration with other mathematical techniques. A detailed analysis of those reviewed articles reveals that the past researchers have mostly preferred Taguchi's L9 orthogonal array as the experimental design plan; EDM oil as the dielectric fluid; medium and high carbon steels as the work materials; peak current and pulse-on time as the input parameters; material removal rate, tool wear rate and surface roughness as the responses; and grey relational analysis as the MCDM tool during conducting and optimizing EDM operations. This review paper would act as a data repository to the future researchers in understanding the stochastic behaviour of EDM processes and providing guidance in setting the tentative operating levels of varying input parameters along with achievable response values. The extracted dataset can be treated as an input to any of the machine learning algorithms for subsequent development of appropriate prediction models. This review also outlines potential future research avenues, emphasizing advancements in EDM technology and the integration of innovative multi-criteria decisionmaking tools. [ABSTRACT FROM AUTHOR]

This paper gives an overview over all currently available data sets for the European Long-term Ecosystem Research (eLTER) monitoring site Gesäuse-Johnsbachtal. The site is part of the LTSER platform Eisenwurzen in the Alps of the province of Styria, Austria. It contains both protected (National Park Gesäuse) and non-protected areas (Johnsbachtal). Although the main research focus of the eLTER monitoring site Gesäuse-Johnsbachtal is on inland surface running waters, forests and other wooded land, the eLTER whole system (WAILS) approach was followed in regard to the data selection, systematically screening all available data in regard to its suitability as eLTER's Standard Observations (SOs). Thus, data from all system strata was included, incorporating Geosphere, Atmosphere, Hydrosphere, Biosphere and Sociosphere. In the WAILS approach these SOs are key data for a whole system approach towards long term ecosystem research. Altogether, 54 data sets have been collected for the eLTER monitoring site Gesäuse-Johnsbachtal and included in the Dynamical Ecological Information Management System – Site and Data Registry (DEIMS-SDR), which is the eLTER data platform. The presented work provides all these data sets through dedicated data repositories for FAIR use. This paper gives an overview on all compiled data sets and their main properties. Additionally, the available data are evaluated in a concluding gap analysis with regard to the needed observation data according to WAILS, followed by an outlook on how to fill these gaps. [ABSTRACT FROM AUTHOR]

Purpose: Prior research shows that religiosity affects the degree of managers' risk aversion. As a result, religious firms are less likely to invest in R&D activities. Moreover, US GAAP treats these investments as expenses. For this reason, religious firms have fewer expenses in their earnings and are less likely to be in financial distress. Design/methodology/approach: Data are collected from Worldscope and the Churches and Church Membership files of the American Religion Data Archive website from 1985 to 2018. With 18,199 observations in US context, the authors used the marginal effect to test the mediating effect of R&D accounting treatment. Findings: The authors find that the marginal effect of religiosity on financial distress with US GAAP is higher than the marginal effect of religiosity on financial distress with capitalization of R&D costs, which means that accounting treatment can explain the relation between religiosity and financial distress in the US context. Research limitations/implications: The authors used linear interpolation and linear extrapolation data to be able to conduct this research over a period of 1985–2018. For future researches, the authors propose to test other factors which can explain the relationship between religiosity and financial distress based on the ethics element. Practical implications: These results should be of interest to regulators because treating R&D activities as expenses can destroy the accounting performance of firms that prefer investing in risky projects. This favoritism prevents the comparison between two firms in the same industry with different risk-taking behaviors. This problem is more prevalent if the authors have two firms with different ratios of religiosity. This paper suffers from a major limitation related to data availability. Originality/value: This may be the first study that investigates why religious firms are less likely to be in financial distress. This paper notes that religious firms are less likely to be in financial distress because their conservative behavior towards R&D activities coincides with the conservative R&D accounting treatment. In fact, the mismatch between expenses and revenues from R&D activities can cause financial distress. [ABSTRACT FROM AUTHOR]

From July 2022 to December 2022, the World Data System (WDS) International Technology (ITO) and International Program (IPO) Offices conducted a review of strategic plans and technical roadmaps of all current WDS members and the set of Canadian repositories that participated in the Digital Research Alliance of Canada's CoreTrustSeal Certification Support and Funding Pilotv (Digital Research Alliance of Canada, 2022). In this paper, we describe how a new organizational assessment method was designed and utilized to identify the needs and challenges faced by the WDS and Canadian CTS Pilot members. Our method relied on reviewing public-facing documentation provided by the repositories, with a priority on strategic plans and technical road maps. In total, we reviewed 95 sources of information, including 33 strategic plans and 3 technical roadmaps describing a total of 95 out of the original 147 target organizations. In this paper, we also describe our assessment tool and the overarching challenges and goals we identified through the usage of this tool. Finally, we will describe the limitations of our methodology and provide recommendations from the World Data System on how best to assist the WDS members and the cohort of Canadian data repositories based on our findings. [ABSTRACT FROM AUTHOR]

To achieve a dynamic comprehensive risk assessment of road transport of hazardous chemicals, this paper first collected 213 road transport accidents involving hazardous chemicals that occurred between 2015 and 2020 to build a case library. Then, it established a risk assessment system (including 9 primary indicators and 28 secondary indicators) based on the frequencies of reasons for accident cases and explored the quantification methods for indicators based on their definitions. Subsequently, this paper calculated the weights of indicators based on the backpropagation neural network algorithm and the data in the case library and formulated a model for dynamic risk assessment of road transport of hazardous chemicals. The model takes into account the impact of comprehensive indicators such as drivers, vehicles, goods, roads, and the environment. The accuracy of the model calculation results is 93%. Eventually, the study verified the model using simulation data in real scenarios. The validation results show that the model could achieve a dynamic comprehensive assessment of risks in road transport of hazardous chemicals. [ABSTRACT FROM AUTHOR]