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The interaction and exchange between local culture and Islamic culture dominate in influencing the social system. This research aims to explore the perspective of Hadith on the Gerudo and Topeng celebrations in Jambi. This research relies on an analytical descriptive method based on collecting library data from various paper and electronic sources and field data through observation and interviews. The researcher then used thematic methods in the takhrīj of hadith, involving the search for hadiths based on sentences related to the topic. In analyzing hadith texts, the researcher has employed a contextual method with comparison approach and has compared them with the opinions of 'ulamā' who are both supportive and critical of these approaches. The key finding of this research is that the taswīr prohibited by the Prophet Muhammad refers to taswīr that contains an 'illah or reason for its prohibition. This prohibition applies to taswīr used as a rival to Allah's creation, for worship, or due to elements in its form that contradict Islam. Therefore, Gerudo and Topeng are not considered prohibited taswīr because current practices no longer embody the reasons for their prohibition. [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 By November 2023, a total of 1501 datasets (over 25 million data points) from 1554 papers had been archived.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 Most of the study sites from which data have been archived are in the North Atlantic Ocean, North Pacific Ocean, South Pacific Ocean, and Mediterranean Sea, while polar oceans are still relatively poorly represented.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]

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]

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]

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.)

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]

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]

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.)

Complications of detrital zircons databases provide a means for statistically analysing a variety of significant geological problems. In this work, we tried to collect a database about the South China Phanerozoic detrital zircon geochronology data. The data statistics of this paper rely on the OneSediment Working Group of The Deep‐time Digital Earth program (DDE). By November 2022, the database contains a total of 699 samples with 55,532 U–Pb ages and 3,770 effective Hf isotope data, from 130 papers. Abundant information including reference title, sample ID, locality, rock type, research institution, GPS coordinates, U–Pb ages, εHf(t) values, etc., have been involved in our database, and all data can be downloaded from DDE Data Publish & Repository website, https://repository.deep‐time.org/. Through the integrated data, we can improve the previous studies and avoid the waste of resources caused by a large number of repeated studies. [ABSTRACT FROM AUTHOR]

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]

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]

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]

Detrital zircon U–Pb chronology database of Precambrian deposits provides a context for the interpretation of the origin and evolution of ancient crust. Here, we tried to summarize the published literature containing detrital zircon U–Pb ages and Hf isotope data of Precambrian deposits in South China and then established a database, which contains details of information, such as reference, sample ID, locality, rock type, research institution, GPS coordinates, U–Pb ages and εHf(t) values. The data statistics of this paper rely on the OneSediment Working Group of The Deep‐time Digital Earth program (DDE). By November 2022, 610 samples with 38,278 U–Pb ages and 8,798 Lu‐Hf isotope data were collected from 136 papers, and these data can be downloaded from DDE Data Publish & Repository website, https://repository.deep‐time.org/. The purpose of the establishment of the dataset is to provide guidance and convenience for the research direction of future generations in South China and to improve the previous studies through the integrated data to avoid the waste of resources caused by a large number of repeated studies. [ABSTRACT FROM AUTHOR]

Stable isotope data have made pivotal contributions to nearly every discipline of the physical and natural sciences. As the generation and application of stable isotope data continues to grow exponentially, so does the need for a unifying data repository to improve accessibility and promote collaborative engagement. This paper provides an overview of the design, development, and implementation of IsoBank (www.isobank.org), a community-driven initiative to create an open-access repository for stable isotope data implemented online in 2021. A central goal of IsoBank is to provide a web-accessible database supporting interdisciplinary stable isotope research and educational opportunities. To achieve this goal, we convened a multi-disciplinary group of over 40 analytical experts, stable isotope researchers, database managers, and web developers to collaboratively design the database. This paper outlines the main features of IsoBank and provides a focused description of the core metadata structure. We present plans for future database and tool development and engagement across the scientific community. These efforts will help facilitate interdisciplinary collaboration among the many users of stable isotopic data while also offering useful data resources and standardization of metadata reporting across eco-geoinformatics landscapes. [ABSTRACT FROM AUTHOR]

This paper describes a catalog of simultaneous observations of the Earth's magnetosheath by ESA's Cluster and NASA's MMS missions. The catalog is built from a visual inspection of summary plots provided by the two missions complemented by an analysis of high‐resolution magnetic field data. The catalog includes 117 events when Cluster 4 and MMS 4 crossed simultaneously the magnetosheath between January–April, 2017–2021. The dynamical and turbulent features of the magnetosheath are strongly influenced by θBn, the angle between the interplanetary magnetic field (IMF) and the shock normal direction. To facilitate such investigations, we also determine the bow shock geometry for each event based on two different approaches: (a) a minimum variance analysis of in‐situ magnetic field measurements, and (b) a geometrical approach which considers a bow shock model parameterized by OMNI data. A description of spacecraft trajectory during each event is also provided. Additional data describe the relative distances between Cluster 4 and MMS 4, a classification of each event as either quasi‐parallel or quasi‐perpendicular, and the distribution of events per magnetospheric flank. The time intervals for the Cluster ‐ MMS conjunctions are included in the catalog, as well as all associated figures and tables discussed in this paper are made available through an independent online data repository, and can be freely downloaded and used by any interested researcher. Key Points: We use in‐situ measurements from Cluster 4 and MMS 4 to build a catalog/database of simultaneous observations of the Earth's magnetosheathEmpirical models and minimum variance analysis of the magnetic field allow for an estimation of the bow‐shock orientation for each eventWe also provide details on the relative spacecraft position and an analysis of the bow‐shock geometry [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]

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]

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]

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]

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]

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]

This paper focuses attention on the problem of supporting multidimensional big data analytics tools over Big Web Knowledge Bases. These big data repositories are generated from web systems built on top of big datasets, as in several real-life examples such as web interfaces to social networks, e-government systems, smart city tools (e.g., for weather forecasting), and so forth. The problem of extracting actionable knowledge insights from big web knowledge bases is a relevant challenge now. In line with this emerging research field, the paper proposes models, issues and research trends in the context of multidimensional big data analytics over big web knowledge bases, along with a reference architecture that impersonates this paradigm. [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.)

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 paper addresses the challenge of transmitting a big number of files stored in a data center (DC), encrypting them by compilers, and sending them through a network at an acceptable time. Face to the big number of files, only one compiler may not be sufficient to encrypt data in an acceptable time. In this paper, we consider the problem of several compilers and the objective is to find an algorithm that can give an efficient schedule for the given files to be compiled by the compilers. The main objective of the work is to minimize the gap in the total size of assigned files between compilers. This minimization ensures the fair distribution of files to different compilers. This problem is considered to be a very hard problem. This paper presents two research axes. The first axis is related to architecture. We propose a novel pre-compiler architecture in this context. The second axis is algorithmic development. We develop six algorithms to solve the problem, in this context. These algorithms are based on the dispatching rules method, decomposition method, and an iterative approach. These algorithms give approximate solutions for the studied problem. An experimental result is implemented to show the performance of algorithms. Several indicators are used to measure the performance of the proposed algorithms. In addition, five classes are proposed to test the algorithms with a total of 2350 instances. A comparison between the proposed algorithms is presented in different tables discussed to show the performance of each algorithm. The result showed that the best algorithm is the Iterative-mixed Smallest-Longest-Heuristic (ISL) with a percentage equal to 97.7% and an average running time equal to 0.148 s. All other algorithms did not exceed 22% as a percentage. The best algorithm excluding ISL is Iterative-mixed Longest-Smallest Heuristic (ILS) with a percentage equal to 21,4% and an average running time equal to 0.150 s. [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]

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]

As cloud computing usage grows, cloud data centers play an increasingly important role. To maximize resource utilization, ensure service quality, and enhance system performance, it is crucial to allocate tasks and manage performance effectively. The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers. The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies, categories, and gaps. A literature review was conducted, which included the analysis of 463 task allocations and 480 performance management papers. The review revealed three task allocation research topics and seven performance management methods. Task allocation research areas are resource allocation, load-Balancing, and scheduling. Performance management includes monitoring and control, power and energy management, resource utilization optimization, quality of service management, fault management, virtual machine management, and network management. The study proposes new techniques to enhance cloud computing work allocation and performance management. Shortcomings in each approach can guide future research. The research's findings on cloud data center task allocation and performance management can assist academics, practitioners, and cloud service providers in optimizing their systems for dependability, cost-effectiveness, and scalability. Innovative methodologies can steer future research to fill gaps in the literature. [ABSTRACT FROM AUTHOR]

Digital repositories play a crucial role in organizing and preserving vast collections of digital content. Efficiently ingesting large amounts of data into these repositories is a common challenge faced by institutions. This paper explores the use of bulk upload techniques in DSpace, an open-source digital repository software, to streamline the ingestion process and enhance repository management. We discuss the benefits of bulk upload in terms of time savings, metadata consistency, and scalability. Additionally, we delve into the technical aspects of implementing bulk upload in DSpace, covering the Simple Archive Format (SAF), metadata mapping, and handling of digital files. Furthermore, we highlight real-world examples and best practices for utilizing bulk upload in DSpace. By adopting this approach, institutions can significantly improve their efficiency in managing and preserving digital content, ensuring a seamless user experience, and facilitating knowledge dissemination. Here, an experimental method of research/case study technique is utilized to evaluate the efficiency and effectiveness of the design model for implementation of the bulk uploading of documents in Dspace at Bennett University is practiced. The feedback is gathered in order to identify the flaws and make the necessary improvements. Simple Archive Format (SAF) is a utility that converts Bitstream/Content files plus a metadata.csv file into a Simple Archive Format package, making bulk uploads to the DSpace repository simple. All question papers were digitized using a high-quality scanner, an Excel file with Dublin core information was created, and Excel was converted to CSV format in order to import all old question papers in bulk into the Bennett University Digital Repository Services. The study indicates that it is essential to pay close attention to the precise format of metadata leveraging the Dublin core and the file's location. It is an experiment conducted by the Bennett University Library and the research was confined to Bennett University digital repository. [ABSTRACT FROM AUTHOR]

Europe has set a target to become a decarbonised continent by 2050. To achieve this, intervention in buildings is crucial, as they serve as significant energy consumers and greenhouse gas emitters. This intervention encompasses two essential pathways: renovation and digitalisation. The combination of these two aspects gives rise to elements such as the Digital Building Logbook (DBL), a digital data repository expected to enhance the pace and quality of renovation efforts. This paper introduces, for the first time, a European DBL data model with a specific focus on building renovation purposes—the DBrL. It outlines its initial requirements, constituent entities, relationships, and attributes. While acknowledging the need to address issues related to data protection, integration with existing data sources, and connections with Building Information Modelling (BIM) and Geographic Information System (GIS) in subsequent design phases, the study's outcome represents a significant stride in defining this tool. [ABSTRACT FROM AUTHOR]

The majority of available climate data in global digital archives consist of data only from the 1940s or 1950s onwards, and many of these series have gaps and/or are available for only a subset of the variables which were actually observed. However, there exist billions of historical weather observations from the 1700s, 1800s, and early 1900s that are still in hard‐copy form and are at risk of being lost forever due to deterioration. An assessment of changes in climate extremes in several IPCC regions was not possible in IPCC AR6 WGI owing, in many cases, to the lack of available data. One such region is Africa, where the climate impact research and the ability to predict climate change impacts are hindered by the paucity of access to consistent good‐quality historical observational data. The aim of this innovative project was to use classroom‐based participatory learning to help transcribe some of the many meteorological observations from Africa that are thus far unavailable to researchers. This project transcribed quickly and effectively station series by enrolling the help of second‐year undergraduate students at Maynooth University in Ireland. The newly digitized African data will increase the temporal and spatial coverage of data in this important data‐sparse region. Students gained new skills while helping the global scientific community unearth new insight into past African climate. The project managed to transcribe 79 months of data at Andapa in Madagascar and 56 months of data for Macenta in Guinea. The digitized data will be openly and freely shared with the scientific and wider community via the Pangaea data repository, the C3S Climate Data Store, and the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) data centre in the US. The project model has the potential for a broader roll‐out to other educational contexts and there is no shortage of data to be rescued. This paper provides details of the project, and all supporting information such as project guidelines and templates to enable other organizations to instigate similar programs. [ABSTRACT FROM AUTHOR]

Background: Lung cancer screening (LCS) using low-dose computed tomography (LDCT) is a strategy for early-stage diagnosis. The implementation of LDCT screening in countries with a high prevalence/incidence of tuberculosis (TB) is controversial. This systematic review and meta-analysis aim to identify whether LCS using LDCT increases early-stage diagnosis and decreases mortality, as well as the false-positive rate, in regions with a high prevalence of TB. Methods/Design: Studies were identified by searching BVS, PUBMED, EMBASE, and SCOPUS. RCT and cohort studies (CS) that show the effects of LDCT in LC screening on mortality and secondary outcomes were eligible. Two independent reviewers evaluated eligibility and a third judged disagreements. We used the Systematic Review Data Repository (SRDR+) to extract the metadata and record decisions. The analyses were stratified by study design and incidence of TB. We used the Cochrane "Risk of bias" assessment tool. Results: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) were used. Thirty-seven papers were included, referring to 22 studies (10 RCTs and 12 cohorts). Few studies were from regions with a high incidence of TB (One RCT and four cohorts). Nonetheless, the evidence is compatible with European and USA studies. RCTs and CS also had consistent results. There is an increase in early-stage (I-II) diagnoses and reduced LC mortality in the LCDT arm compared to the control. Although false-positive rates varied, they stayed within the 20 to 30% range. Discussion: This is the first meta-analysis of LDCT for LCS focused on its benefits in regions with an increased incidence/prevalence of TB. Although the specificity of Lung-RADS was higher in participants without TB sequelae than in those with TB sequelae, our findings point out that the difference does not invalidate implementing LDCT LCS in these regions. Trial registration: Systematic review registration Systematic review registration PROSPERO CRD42022309581. [ABSTRACT FROM AUTHOR]

This paper presents the open-source Python software OSADCP developed for the processing of vessel-mounted Acoustic Doppler Current Profiler (VMADCP) data. At this stage, the toolbox is designed for processing VMADCP measurements from open-ocean applications of Teledyne RDI Ocean Surveyor ADCPs and the data acquisition software VMDAS. Based on the VMDAS ENX binary output format, the software contains implementations for cleaning and vector-averaging of single-ping velocity data, verification of the position data, and applying misalignment and amplitude corrections. The procedures of OSADCP are described in detail to encourage the scientific community to use it for their own purposes. The toolbox is an integral part of a workflow implemented on the German marine research vessels in the framework of the Underway Research Data project of the German Marine Research Alliance (DAM). It aims to ensure standardized data acquisition measures, reliable data transfer from the ADCP to shore both near-real-time and in delayed-mode, processing and quality control, and dissemination of the curated data product in the data repository PANGAEA. From PANGAEA, data sets are forwarded to the European marine data hubs Copernicus Marine Service and EMODnet. The workflow that forms the framework for OSADCP is described here as an example of scientific data management that follows the FAIR data guidelines. [ABSTRACT FROM AUTHOR]

Modernizing existing buildings is vital to saving carbon emissions and counteracting global climate change. Many countries face the challenge of modernizing a considerable number of their buildings in the next two decades. Implementing related modernization measures requires a high number of craftworkers. However, current studies indicate that these craftworkers' current lack will increase. Examining the effects of craftworkers shortage on modernization strategies needs data concerning the realization time of modernization measures. We collected this data based on 90 expert interviews and provide it in this paper. The interview results comprise realization times for insulation measures of the envelope and changes in the heat supply system for typical buildings. This paper describes the data collection and presents the raw data available at a repository at Figshare. The data is internationally applicable in simulation and optimization approaches for building modernization. [ABSTRACT FROM AUTHOR]

Remaining useful life is one of the key indicators for mechanical equipment health and condition-based maintenance requirements. In fact, the field of prognostics and health management is heavily reliant on remaining useful life estimation. The availability of industrial big data has enabled promising research efforts in prognostics and health management. Deep learning techniques have been widely adopted, and proven to be successful in big data prognostics applications. However, deep learning approaches are considered black box approaches with interpretation difficulties and loss of information due to high-level feature extraction resulting from layer-by-layer processing. Enriching the deep learning input with temporal features can increase the performance of deep learning based approaches. This paper aims to improve the performance of deep learning techniques by incorporating dynamic mode decomposition into the deep learning schemes for the purposes of remaining useful life estimation. The developed method is capable of accurately predicting the remaining useful life in a data driven manner without prior knowledge of system equations. The input temporal information and health state are enriched by using dynamic mode decomposition which produces dynamic modes that approximate the infinite Koopman operator modes. The modes contain coherent time dynamics of the processed system which contribute to producing a health indicator that is representative of the system degradation. These time dependent dynamics are important characteristics of the system's health state. The degradation profile is incorporated into deep learning schemes that accurately predict the remaining useful life of the system. To validate the proposed model, two different experimental data repositories are used in this paper. The first one is a spiral bevel gear vibration dataset. The second one consists of turbofan engines vibration datasets. The validation results have shown improved remaining useful life estimation performance when dynamic mode decomposition technique is incorporated into the deep learning schemes presented in this paper. [ABSTRACT FROM AUTHOR]

Open access to research data is an important part of the concept of open science. The aim of this article was to identify Croatian authors/institutions that have recognized the importance of sharing research data, and that have given them access via one of the data repositories covered by Data Citation Index. A total of 265 documents were found in the database. Data papers by Croatian authors available on the Web of Science Core Collection platform were also analysed. Twenty-nine of them were found, mostly of multidisciplinary orientation. The authors of the largest number of data documents are affiliated to the University of Zagreb. Croatian researchers are archiving data in international repositories, because the infrastructure for their archiving at the national level has only recently been developed, and is just beginning to be used. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative solution to address the challenge of detecting latent malware in backup systems. The proposed detection system utilizes a multifaceted approach that combines similarity analysis with machine learning algorithms to improve malware detection. The results demonstrate the potential of advanced similarity search techniques, powered by the Faiss model, in strengthening malware discovery within system backups and network traffic. Implementing these techniques will lead to more resilient cybersecurity practices, protecting essential systems from hidden malware threats. This paper's findings underscore the potential of advanced similarity search techniques to enhance malware discovery in system backups and network traffic, and the implications of implementing these techniques include more resilient cybersecurity practices and protecting essential systems from malicious threats hidden within backup archives and network data. The integration of AI methods improves the system's efficiency and speed, making the proposed system more practical for real-world cybersecurity. This paper's contribution is a novel and comprehensive solution designed to detect latent malware in backups, preventing the backup of compromised systems. The system comprises multiple analytical components, including a system file change detector, an agent to monitor network traffic, and a firewall, all integrated into a central decision-making unit. The current progress of the research and future steps are discussed, highlighting the contributions of this project and potential enhancements to improve cybersecurity practices. [ABSTRACT FROM AUTHOR]

The recent and significant change in the architecture, engineering, and construction (AEC) industry is the increasing use of building information management (BIM) tools in design and how the generated digital data are consumed. Although designers have primarily published blueprints and model files, multiple parties are now involved in producing different aspects of the data and may be consuming data produced by others. This evolution has created new challenges in sharing and synchronizing information across organizational boundaries. Linked building data is a community effort identified as a potential means of overcoming the barriers to data interoperability. In this paper, we present how the industry can be strengthened using a peer-to-peer network based on the InterPlanetary File System (IPFS) framework to address the typical availability problems of web-based data. The paper particularly presents how Linked Data serialization of the Industry Foundation Classes (IFC) standard can be used in the context of IPFS and benchmarks the performance for the publication of models between IPFS versus HTTP protocol. We show that linked building data—in particular, IFC models converted into Resource Description Format (RDF) graphs according to the ifcOWL ontology—can be implemented using the framework, with initial indications of significant benefits of a peer-to-peer network in terms of performance, offline access, and immutable version history. Two use cases in distributed collaborative environments in the AEC/facility management (FM) sector using evolving multidomain models are used to evaluate the work. In a construction project, stakeholders must collaborate and share design data models for efficient and safe completion. Building information published using Linked Data techniques aims to facilitate data sharing between interested parties without a central intermediary. However, the challenges of Linked Data stem from using web protocols, resulting in limited availability, suboptimal performance, broken links, and lost history. This study explores using the InterPlanetary File System (IPFS), a communication protocol for computers to communicate with each other directly without needing an intermediary. It addresses issues related to data availability on the web and data-transfer performance. The study demonstrates the suitability of IPFS in addressing the challenges of sharing building data. The data are available even when the original publisher host is down. In addition, the content-based addressing provides a digital fingerprint that can ensure authenticity and uniqueness, eliminating the data's duplication. Therefore, it minimizes the storage space consumed by data backups and archives. However, because IPFS addresses and communication principles are incompatible with the Linked Data standard approach, we designed a way so that the construction data saved in IPFS can be accessed transparently as a part of the standard Linked Data network. [ABSTRACT FROM AUTHOR]

In a continuously evolving environment, organizations, including public administrations, need to quickly adapt to change and make decisions in real-time. This requires having a real-time understanding of their context that can be achieved by adopting an event-native mindset in data management which focuses on the dynamics of change compared to the state-based traditional approaches. In this context, this paper proposes the adoption of an event-centric knowledge graph approach for the holistic data management of all data repositories in public administration. Towards this direction, the paper proposes an event-centric knowledge graph model for the domain of public administration that captures these dynamics considering events as first-class entities for knowledge representation. The development of the model is based on a state-of-the-art analysis of existing event-centric knowledge graph models that led to the identification of core concepts related to event representation, on a state-of-the-art analysis of existing public administration models that identified the core entities of the domain, and on a theoretical analysis of concepts related to events, public services, and effective public administration in order to outline the context and identify the domain-specific needs for event modeling. Further, the paper applies the model in the context of Greek public administration in order to validate it and showcase the possibilities that arise. The results show that the adoption of event-centric knowledge graph approaches for data management in public administration can facilitate data analytics, continuous integration, and the provision of a 360-degree-view of end-users. We anticipate that the proposed approach will also facilitate real-time decision-making, continuous intelligence, and ubiquitous AI. [ABSTRACT FROM AUTHOR]

When large scale of UAV photogrammetry and Lidar for mapping a Taiwanese aboriginal settlement with stone slab houses has been carried out, terrestrial 3D photogrammetry and scanning are applied to middle and small-scale recording individual buildings to get architectural form with decorations in detail. When constructing the basic data of cultural assets, especially in the mountain area, it is necessary to apply new technology to carry out efficient and accurate settlement mapping works. In this paper, taking an old Paiwan aboriginal settlement an example, a detailed examination of a stone slab house with three different 3D techniques is put into practice. The 3D data can be further used for digital archive, virtual presentation, and data query through network resources. The results of this study show that, in a large-scale of settlement surveys, aerial surveying technology is efficient for constructing the topography of a settlement and provides competent and spatial information of authentic landscape form, while terrestrial photogrammetry and scanning for middle and small scales record individual buildings to provide more details of architectural forms. They both together construct authentic landscape and architectural form of a settlement and furthermore are able to reveal the hidden settlements of archaeological sites under dense forests. The application of 3D technology, greatly increasing the efficiency and accuracy of mapping and recording, is very much helpful for visualization, virtual restoration, and conservation of indigenous settlements cultural heritage, especially in such high and steep forest. [ABSTRACT FROM AUTHOR]