China Scientific Data最新文献

A dataset of soil monitoring of the Liaohe Estuary Wetland during 2016–2021 2016-2021 年辽河口湿地土壤监测数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0084.zh

Xingyue Su

{"title":"A dataset of soil monitoring of the Liaohe Estuary Wetland during 2016–2021","authors":"Xingyue Su","doi":"10.11922/11-6035.csd.2023.0084.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0084.zh","url":null,"abstract":"The Liaohe Estuary wetland falls into category of northern coastal estuary wetlands. Dominated by species such as Phragmites australis (Cav.) Trin. ex and Steud Suaeda salsa (L.) Pall., the primary soil type in this wetland is coastal salt marsh soil. This dataset includes the long-term positioning observations from Liaoning Panjin Wetland Ecosystem National Field Scientific Observation and Research Station during 2016—2021. The primary data observation indicators include soil bulk density, saturated water conductivity, soil water content, pH, REDOX potential, calcium ions, potassium ions, magnesium ions, sodium ions, carbonate ions, bicarbonate ions, chloride ions, sulfate ions, total nitrogen, nitrite nitrogen, total phosphorus, available phosphorus, total potassium, organic matter, organic carbon, heavy metal ions, and other physical and chemical properties. In the observation data, apart from the oxidation-reduction potential observed in situ at the observation sites using a portable instrument, all other indicators are collected as soil samples at fixed observations sites. The samples are then taken back to the laboratory and analyzed using standardized instruments to determine various indicators. The establishment of observation datasets furnishes basic data for enhancing the regional wetland soil environmental quality monitoring system and establishing the soil quality environmental monitoring network. It is expected to contribute to exploring the patterns of change, ecological process, evolution trend, and driving mechanism of regional wetland soil ecosystems. Moreover, it can provide long-term data support for solving basic and key problems in the research of northern coastal wetlands as well as regional environment and social public services.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"33 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140358269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of daily meteorological elements of the Guangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station during 2021–2022 2021-2022 年广东南岭森林生态系统国家野外科学观测研究站日气象要素数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0123.zh

Zhaowei Tan

{"title":"A dataset of daily meteorological elements of the Guangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station during 2021–2022","authors":"Zhaowei Tan","doi":"10.11922/11-6035.csd.2023.0123.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0123.zh","url":null,"abstract":"The mountainous forest and biodiversity ecological functional area of the Nanling Mountain forest ecosystem is one of the 25 key ecological functional areas in China, covering a variety of forest vegetation types, including tropical and subtropical moist broadleaf forests, coniferous broad-leaved evergreen mixed forest, and mountain top evergreen broad-leaved dwarf forest. The tropical and subtropical moist broadleaf forests are the most typical vegetation type in the Nanling Mountains. Monitoring the meteorological elements in the community can help understand the response mechanism of the tropical and subtropical moist broadleaf forests in the Nanling Mountains to climate change. Based on the Nanling Forest Ecosystem National Field Scientific Observation Research station (\"Nanling Station\" for short) in the Nanling Mountains, Guangdong, we carried out positioning research in Nanling National Nature Reserve. In this paper, we disclosed the raw data of 10 min average wind speed, precipitation, air temperature, air pressure, solar radiation (i.e. total radiation, reflected radiation, ultraviolet radiation, net radiation, photosynthetically active radiation) as well as relative humidity continuously collected in the subtropical evergreen broad-leaved forest area of the Nanling Station from 2021-2022 on a daily scale after data processing, quality control and evaluation. The dataset accessible to the public can serve as a valuable resource for further insights into the Nanling Mountain Forest Ecosystem, and provide foundation for efforts related to the restoration and protection of forest ecosystems.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"121 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140359817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of observing bottom fishery stocks in the adjacent waters of Changdao Islands, Shandong Province, 2021 山东省长岛群岛邻近海域底层渔业资源观测数据集，2021 年

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2022.0104.zh

Na Li

{"title":"A dataset of observing bottom fishery stocks in the adjacent waters of Changdao Islands, Shandong Province, 2021","authors":"Na Li","doi":"10.11922/11-6035.csd.2022.0104.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0104.zh","url":null,"abstract":"As one of the most representative areas of the shelf-edge sea, the waters adjacent to offshore islands are important sea-land transition areas. The ecosystems in these areas are diverse and complex due to the dual regulation of natural environmental variabilities and human activities. The adjacent waters of the Changdao Island are characterized by typical island ecology and are key migration channels, spawning grounds and habitats of fishery resources in the Bohai Sea and Yellow Sea, which are of great significance to the food web process of fishery organisms in this area. From March to December 2021, the Shandong Changdao Fishery Resources National Observation and Research Station conducted a month-by-month survey of bottom fishery stocks with 10 stations per cruise and sample measurements in the waters adjacent to the Changdao Island. Afterwards, the index of relative importance (IRI), species replacement rate, catch per unit effort (CPUE), D (Margalef richness index), H′ (Shannon-Wiener diversity index) and J′ (Pielou evenness index) were calculated from the biological measurement data of the catches that formed the present dataset. The review and proofreading of this dataset was thoroughly conducted through extensive full-sample cross-checks by multiple reviewers to guarantee the standardization and accuracy. This dataset can provide data support for the study of spatial and temporal patterns of bottom fishery stocks in the Bohai Sea and Yellow Sea and the study of special island fishery ecosystems with migratory passage characteristics.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"68 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140360111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of soil respiration in a subtropical evergreen broad-leaved forest at Ailao Mountain from 2010 to 2014 2010 年至 2014 年隘老山亚热带常绿阔叶林土壤呼吸数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0065.zh

Yanyun Yi

{"title":"A dataset of soil respiration in a subtropical evergreen broad-leaved forest at Ailao Mountain from 2010 to 2014","authors":"Yanyun Yi","doi":"10.11922/11-6035.csd.2023.0065.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0065.zh","url":null,"abstract":"Subtropical forests, as the largest forest type in China, play an important role in regulating global climate change and maintaining atmospheric carbon balance. The carbon emitted by soil through respiration is the main contributor of atmospheric CO2 levels, so even slight changes in soil carbon pool can significantly affect the concentration of atmospheric CO2. Therefore, at present, the magnitude and dynamic change characteristics of soil carbon storage in subtropical forests are attached great importance to. Ailao Mountain in Yunan Province stands as a crucial region for the distribution of subtropical forests in China. This study used a multichannel automated chamber system to estimate soil respiration in a subtropical evergreen broad-leaved forest ecosystem of Ailao Mountain. Ailao Mountain Station for Subtropical Forest Ecosystem Studies is a national field station and a basic observation station of the Chinese Ecosystem Research Network. We gathered soil respiration data from the subtropical evergreen broad-leaved forest in Ailao Mountain from 2011 to 2014, including soil temperature 5cm (TS), soil moisture content 10cm (SWC) and soil respiration data (RS), organized at daily, monthly and annual scales. This dataset is of great significance in revealing the effects of climate change on soil ecological processes in subtropical evergreen broad-leaved forests. It can facilitate precise evaluation of soil organic carbon emissions and forest ecosystem management, and provide both empirical and theoretical basis for further research on the effects of global changes (e.g. climate warming) on soil respiration components, especially with a focus on soil organic carbon emissions.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"83 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140360415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Policies and planning for advancing scientific data development in the EU 推进欧盟科学数据发展的政策和规划

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0140.zh

Yaonan Zhang

{"title":"Policies and planning for advancing scientific data development in the EU","authors":"Yaonan Zhang","doi":"10.11922/11-6035.csd.2023.0140.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0140.zh","url":null,"abstract":"The continual advancement of global scientific and technological innovation capabilities has spurred a rapid growth of scientific data. As a global benchmark for scientific data management and sharing, the European Union (EU) constantly place a high priority on the management and development of scientific data, and has formed a comprehensive array of policies and plans to advance scientific data development. Through network investigation and literature analysis, this paper focuses on consolidating and summarizing the EUs scientific data support and regulatory bodies, management policies, development plans, and evaluates the effectiveness and challenges in data application practices. Moreover, it also outlines the issues confronting the development of scientific data in China and puts forward insightful recommendations. The analysis shows that the EU’s efforts to promote open science and open scientific data, the scientific data development policy system and sustainable development program are crucial to the open sharing, effective scientific management, maximizing benefits and sustainable development of scientific data in the EU, making the EU stand at the forefront of open scientific data and open science in the world. Furthermore, the ongoing integration of science data centers into the science and innovation infrastructure system of the EU. These practices of the EU can serve as valuable references for China in the development of scientific data, the construction of scientific data centers, the formulation of scientific data policies and development plans, and the play of scientific benefits.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"23 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140360889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and practices of the national standard for Data paper publication metadata 数据文件出版物元数据国家标准的制定与实践

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0187.zh

Yuwei Gao

{"title":"Development and practices of the national standard for Data paper publication metadata","authors":"Yuwei Gao","doi":"10.11922/11-6035.csd.2023.0187.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0187.zh","url":null,"abstract":"In August 2023, the national standard for GB/T 42813-2023 Data paper publication metadata was officially released. This standard specifies the content and framework of metadata required for data paper publication, including dataset metadata, data paper metadata, as well as their description methods, extension principles, and methods. It is applicable to the description, preservation, online publishing, and sharing services associated with data papers and their corresponding datasets. The release of this standard marks the first comprehensive agreement at the national level regarding the new mode of data paper publishing, namely the open sharing of scientific data, which has addressed the prior absence of standardized guidance in the field of data publishing. It facilitates data publishing institutions in promptly releasing data papers and their associated data, providing support for the rights and protection of scientific data. The standard holds significant importance in promoting the establishment of an open and shared ecosystem for scientific data. Since its publication, certain data journals or scientific data publishing platforms have begun adopting the elements and definitions specified in the standard, thus engaging in a more extensive practice.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"30 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140359009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of observatory meteorological vertical physical parameters from Beijing Observatory during 2021–2022 北京天文台 2021-2022 年观测站气象垂直物理参数数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0122.zh

Yajun Xiong

引用次数: 0

MedicalQA: A dataset of medical domain for machine reading comprehension MedicalQA：用于机器阅读理解的医学领域数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2022.0030.zh

Ning Ma

{"title":"MedicalQA: A dataset of medical domain for machine reading comprehension","authors":"Ning Ma","doi":"10.11922/11-6035.csd.2022.0030.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2022.0030.zh","url":null,"abstract":"Machine reading comprehension aims to make the computer understand the paragraph semantics and answer the questions raised by users using algorithms. The quality of the dataset used in this task can directly affect the experimental results of the model. In order to enrich the medical domain dataset of machine reading comprehension, this paper constructs MedicalQA, a medical domain dataset for machine reading comprehension, employing a combination of web crawlers and manual annotation techniques. The dataset takes two medical platforms (i.e. Xunyiwenyao Network and 39 Health Network) as main data sources, and includes 19,502 paragraphs and Q & A pairs, covering 9 medical departments, such as internal medicine, surgery, obstetrics and gynecology. The dataset is formatted as an Excel file, organized with 5e columns. The first column denotes the paragraph ID; the second column indicates the department to which the paragraph belongs; the third column contains the paragraph content; the fourth column lists the questions, and the fifth column provides corresponding answers to the questions. The construction of this dataset is conducive to the establishment of machine reading comprehension models in the medical domain, and can also promote the sharing of medical datasets in the field of machine reading comprehension.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"13 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140358619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of meteorology, PM2.5 concentration and gaseous pollutants in Xi 'an City from 2019 to 2020 2019-2020年西安市气象、PM2.5浓度和气态污染物数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.csd.2023.0020.zh

Weikang Ran

{"title":"A dataset of meteorology, PM2.5 concentration and gaseous pollutants in Xi 'an City from 2019 to 2020","authors":"Weikang Ran","doi":"10.11922/11-6035.csd.2023.0020.zh","DOIUrl":"https://doi.org/10.11922/11-6035.csd.2023.0020.zh","url":null,"abstract":"Air pollution in China has improved in recent years, but Central Shaanxi region continues to face great pressure and challenges in pollution control due to its unique geographical location and climatic conditions. The regional and complex air pollution, characterized by ozone (O3) and fine particulate matter (PM2.5), is becoming increasingly serious. More meticulous observation data are needed to clarify the causes of air pollution and provide scientific support for control policies. This dataset comprises the data on the concentrations of nitrogen oxides, sulfur dioxide, ozone and carbon monoxide in the atmosphere obtained by gas analyzer in Gaoxinzi Observation Site of the National Observation and Research Station of Regional Ecological Environment Change and Comprehensive Management in Guanzhong Plain. Weather stations collected data on temperature, humidity, air pressure, solar radiation, wind speed, wind direction and other meteorological parameters around the station. Offline PM2.5 filter membranes were measured and the mass concentrations were analyzed. The observation site is located in the urban area of Xi 'an, Shaanxi Province. The data covers the period from January 2019 to December 2020 with a resolution of 5 minutes for pollution gas data, one minute for meteorological data, and PM2.5 collected every 24 hours. Online instruments are calibrated monthly to ensure data quality, while the offline PM2.5 sampler is calibrated and maintained weekly to ensure its data quality. This dataset can provide fundamental data records for the atmospheric environment in Central Shaanxi Province and offer data support for further pollution evaluation, control, and treatment. Moreover, it can give researchers scientific insights into the processes, casual mechanisms, as well as prevention and control of atmospheric pollution in Central Shaanxi Province.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"4 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140359770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of Coccinellidae and Syrphidae in Yangling from 2018 to 2022 2018年至2022年杨凌蝉科和蚜科数据集

China Scientific Data Pub Date : 2024-03-31 DOI: 10.11922/11-6035.nasdc.2023.0018.zh

Bo Wang

{"title":"A dataset of Coccinellidae and Syrphidae in Yangling from 2018 to 2022","authors":"Bo Wang","doi":"10.11922/11-6035.nasdc.2023.0018.zh","DOIUrl":"https://doi.org/10.11922/11-6035.nasdc.2023.0018.zh","url":null,"abstract":"Agriculture holds a significant strategic position in Yangling.In crop cultivation management, the strategic use of insect natural enemies can effectively reduce the reliance on pesticides and mitigate the potential harm caused by pesticide residues. Among these natural enemies, Coccinellidae and Syrphidae are the most prevalent and valuable guilds preying on many pests including aphids, in the field. However, there was limited knowledge of the species and occurrence of Coccinellidae and Syrphidae due to a lack of systematic monitoring in Yangling farmland. In order to clarify the resources of Coccinellids and Syrphids in Yangling, we monitored these two groups using both Malaise traps and regular surveys in farmland in Yangling, Shaanxi Province from 2018 to 2022. In the past five years, a total of 914 predatory Coccinellids and 1440 Syrphids have been collected. Among Coccinellids, 22 species of Coccinellids were identified, with 16 species and 6 genera. Additionally, there were 14 species of Syrphids, with 12 species and 2 genera identified. The screening and identification of natural enemy insects were conducted by professionals to ensure data quality. This dataset provides basic data on the species, quantity, and occurrence dynamics of predatory Coccinellids and Syrphids. Moreover, it also offers a large number of natural enemy insect specimen photos, ecological photos, Malaise trap photos, specimen bottle photos, and photos of the surrounding environment. It can serve as valuable references for future endeavors aimed at the protection and utilization of predatory insects.","PeriodicalId":248373,"journal":{"name":"China Scientific Data","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140359929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0