cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.j00001.00347
title: Mongolian daily question and answer corpus dataset
title: 蒙古文日常问答语料数据集

description: This dataset is from the Chinese open question answering dataset. After preliminary screening and processing, it is translated into Mongolian and the corpus is manually corrected. Finally, a corpus of 50 thousand pairs of Mongolian question and answer is constructed.
description: This dataset is from the Chinese open question answering dataset. After preliminary screening and processing, it is translated into Mongolian and the corpus is manually corrected. Finally, a corpus of 50 thousand pairs of Mongolian question and answer is constructed.
DOI: 10.57760/sciencedb.j00001.00352
title: Ti-SUM
title: 面向文本摘要的藏文数据集

description: Automatic text summarization is a key task in natural language processing. High-quality datasets can effectively promote the research progress of summarization. Recent research is closer to generate abstractive summarizations by using the deep learning methods. However, there is a lack of high-quality and large-scale summarization datasets available to the public. Besides, it is difficult to construct this kind of dataset manually. The Tibetan text summarization task is still in its infancy due to the lack of public datasets. In order to promote the development of Tibetan informatization. we artificially constructed a small dataset of Tibetan text summarization in this paper, which is composed of 1,000 real Tibetan news articles, each with a short summary. In addition, we have also constructed more than 3,500 article keywords for each news article as a supplement to text summarization tasks.
description: Automatic text summarization is a key task in natural language processing. High-quality datasets can effectively promote the research progress of summarization. Recent research is closer to generate abstractive summarizations by using the deep learning methods. However, there is a lack of high-quality and large-scale summarization datasets available to the public. Besides, it is difficult to construct this kind of dataset manually. The Tibetan text summarization task is still in its infancy due to the lack of public datasets. In order to promote the development of Tibetan informatization. we artificially constructed a small dataset of Tibetan text summarization in this paper, which is composed of 1,000 real Tibetan news articles, each with a short summary. In addition, we have also constructed more than 3,500 article keywords for each news article as a supplement to text summarization tasks.
DOI: 10.57760/sciencedb.j00053.00001
title: Data set of 60 automobile manufacturing enterprises from 2017 to 2019
title: 60家汽车制造企业2017-2019年数据集

description: The enterprise information table is a summary of the average data of 60 listed automobile manufacturing enterprises from 2017 to 2019. The number of patent applications from 2017 to 2019 is obtained by CNRDS, and the total number of employees is obtained by querying the Wind database. The remaining six variables (executive compensation, R&D spending, government subsidies, market power and GDP per capita) are calculated using GTA data, and the units of measurement for each factor are indicated in the first column of the table.The fsQCA software calibration results are shown in a. CSV file. The operating requirements of fsQCA software must be saved in a. CSV file. Software calibration process: firstly, the calibration anchor points of each variable are calculated, and then the fsQCA software data are calibrated and converted into the corresponding membership degree of fuzzy set.Only after the data is calibrated single factor necessity analysis and multi - factor configuration adequacy analysis.
description: The enterprise information table is a summary of the average data of 60 listed automobile manufacturing enterprises from 2017 to 2019. The number of patent applications from 2017 to 2019 is obtained by CNRDS, and the total number of employees is obtained by querying the Wind database. The remaining six variables (executive compensation, R&D spending, government subsidies, market power and GDP per capita) are calculated using GTA data, and the units of measurement for each factor are indicated in the first column of the table.The fsQCA software calibration results are shown in a. CSV file. The operating requirements of fsQCA software must be saved in a. CSV file. Software calibration process: firstly, the calibration anchor points of each variable are calculated, and then the fsQCA software data are calibrated and converted into the corresponding membership degree of fuzzy set.Only after the data is calibrated single factor necessity analysis and multi - factor configuration adequacy analysis.
DOI: 10.57760/sciencedb.j00053.00013
title: data on patent layout and development trend of global gene editing technology
title: 基因编辑技术专利布局与发展态势分析数据

description: 以Incopat专利数据库为数据来源开展基因编辑相关专利检索，该数据库收录了全球120个国家、组织或地区，超过1.4亿件的专利文献，覆盖范围较全。数据采集范围为专利公开公告日自2016年至2020年的授权发明专利。在Incopat数据库中，以ZFN、TALEN、CRISPR、gene、genomic、base editing、prime editing等词进行组合检索（检索时间为2021年3月30日），检索结果经过数据清洗、人工剔除和专家判读，得到全球范围内授权发明专利1477项。
description: 以Incopat专利数据库为数据来源开展基因编辑相关专利检索，该数据库收录了全球120个国家、组织或地区，超过1.4亿件的专利文献，覆盖范围较全。数据采集范围为专利公开公告日自2016年至2020年的授权发明专利。在Incopat数据库中，以ZFN、TALEN、CRISPR、gene、genomic、base editing、prime editing等词进行组合检索（检索时间为2021年3月30日），检索结果经过数据清洗、人工剔除和专家判读，得到全球范围内授权发明专利1477项。
DOI: 10.57760/sciencedb.j00076.00084
title: Global Land Productivity Dynamic Dataset Product
title: Global Land Productivity Dynamic Dataset Product

description: The dataset contains 5 raster files 2 Excel files. The raster file is named "Land Productivity Dynamic Product" and "Indicator Dynamics Product". The spatial resolution of the "Land Productivity Dynamic Product" is 500m.The names of the excel files correspond to product. Each excel file contains the classification code of the raster. Excel file contains attributes of each column are: Code, Description and Product Classification. Users can correspond to the classification in the raster according to the classification code in Excel files.
description: The dataset contains 5 raster files 2 Excel files. The raster file is named "Land Productivity Dynamic Product" and "Indicator Dynamics Product". The spatial resolution of the "Land Productivity Dynamic Product" is 500m.The names of the excel files correspond to product. Each excel file contains the classification code of the raster. Excel file contains attributes of each column are: Code, Description and Product Classification. Users can correspond to the classification in the raster according to the classification code in Excel files.
DOI: 10.57760/sciencedb.j00104.00015
title: KnowID
title: KnowID

description: KnowID combines both recently proposed components and adds novel transformation rules between (a logic-based representation of) EER diagrams as application ontology and the Abstract Relational Model to complete the pipeline. The dataset includes examples and test cases: EER diagrams and ARM diagrams to load and transform.
description: KnowID combines both recently proposed components and adds novel transformation rules between (a logic-based representation of) EER diagrams as application ontology and the Abstract Relational Model to complete the pipeline. The dataset includes examples and test cases: EER diagrams and ARM diagrams to load and transform.
DOI: 10.57760/sciencedb.j00104.00022
title: XLORE2: Large-Scale Cross-Lingual Knowledge Graph Construction and Application
title: XLORE2: Large-Scale Cross-Lingual Knowledge Graph Construction and Application

description: One table and 11 figures. Table 1 shows XLORE2 statistics. Figure 1 shows the framework of XLORE2. Figure 2 is an example of cross-lingual knowledge linking. Figure 3 presents the framework of cross-lingual knowledge linking. Figure 4 is an example of cross-lingual property matching (attribute matching). Figure 5 shows the framework of cross-lingual property matching. Figure 6 presents an example of mistakenly derived facts. Figure 7 is the framework of cross-lingual knowledge validation. Figure 8 shows an example of fine-grained type inference. Figure 9 depicts the framework of fine-grained type inference. Figure 10 is an illustration of XLink. Figure 11 shows the interface of XLORE2 and XLink.
description: One table and 11 figures. Table 1 shows XLORE2 statistics. Figure 1 shows the framework of XLORE2. Figure 2 is an example of cross-lingual knowledge linking. Figure 3 presents the framework of cross-lingual knowledge linking. Figure 4 is an example of cross-lingual property matching (attribute matching). Figure 5 shows the framework of cross-lingual property matching. Figure 6 presents an example of mistakenly derived facts. Figure 7 is the framework of cross-lingual knowledge validation. Figure 8 shows an example of fine-grained type inference. Figure 9 depicts the framework of fine-grained type inference. Figure 10 is an illustration of XLink. Figure 11 shows the interface of XLORE2 and XLink.
DOI: 10.57760/sciencedb.j00001.00295
title: Lightning dataset in China Based on VLF/LF Lightning Location Monitoring System
title: 基于VLF/LF三维闪电定位系统的全国闪电数据集

description: On the one hand, lightning maintains the global atmospheric electricity balance, on the other hand, it is extremely destructive and seriously endangers the safety of production and life of human society. The VLF/LF lightning positioning system has been constructed since 2013, and there are more than 400 three-dimensional lightning detection stations in China. The detection range covers most of the mainland of China and the surrounding sea. The data processing center of VLF/LF Lightning Location Monitoring System receives the lightning electromagnetic pulse signals returned by detection stations, using the 3D time-of-arrival method to locate the lightning parameters, such as the time, type, latitude and longitude, height and peak current intensity of lightning in real time, and obtain the national lightning location dataset. This dataset can be used to study the location of lightning strikes, the distribution of lightning density and movement trends, and provide disaster reduction and prevention services for meteorological, civil aviation, electric power, forestry, petrochemical, and emergency management departments. It can also provide date support to the study of lightning disaster warnings, lightning activities, monitoring and early warning of thunderstorms, global climate change and solar-terrestrial physics research.
description: On the one hand, lightning maintains the global atmospheric electricity balance, on the other hand, it is extremely destructive and seriously endangers the safety of production and life of human society. The VLF/LF lightning positioning system has been constructed since 2013, and there are more than 400 three-dimensional lightning detection stations in China. The detection range covers most of the mainland of China and the surrounding sea. The data processing center of VLF/LF Lightning Location Monitoring System receives the lightning electromagnetic pulse signals returned by detection stations, using the 3D time-of-arrival method to locate the lightning parameters, such as the time, type, latitude and longitude, height and peak current intensity of lightning in real time, and obtain the national lightning location dataset. This dataset can be used to study the location of lightning strikes, the distribution of lightning density and movement trends, and provide disaster reduction and prevention services for meteorological, civil aviation, electric power, forestry, petrochemical, and emergency management departments. It can also provide date support to the study of lightning disaster warnings, lightning activities, monitoring and early warning of thunderstorms, global climate change and solar-terrestrial physics research.
DOI: 10.57760/sciencedb.j00001.00317
title: A dataset of water use efficiency in Central Asia ecosystems during 1980 to 2020
title: 1980-2020年中亚干旱区生态系统水分利用效率数据集

description: Water use efficiency characterizes the coupling relationship between water dissipation and carbon sequestration in terrestrial ecosystems. Understanding the temporal and spatial dynamics of water use efficiency and its response to complex climate change is a prerequisite for dealing with future climate change and man-made disturbances. The ecological model method is considered to be an effective way to assess the carbon and water dynamics of the regional large-scale ecosystem. This study is based on the Arid Region Ecosystem Model (AEM), using site flux data to optimize, verify, and parameterize the model, and build a dataset of water use efficiency of the arid region ecosystem in Central Asia. The time span of this data set is 1980-2020, involving six types of ecosystems including Central Asian coniferous forests, broad-leaved forests, grasslands, phreatophyte shrubs, non- phreatophyte shrubs and farmland. The region includes five Central Asian countries (Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan and Turkmenistan) and Xinjiang of China. This dataset provides support for understanding the carbon-water dynamics of ecologically fragile areas under the background of global change and maintaining the stability of the ecosystem.
description: Water use efficiency characterizes the coupling relationship between water dissipation and carbon sequestration in terrestrial ecosystems. Understanding the temporal and spatial dynamics of water use efficiency and its response to complex climate change is a prerequisite for dealing with future climate change and man-made disturbances. The ecological model method is considered to be an effective way to assess the carbon and water dynamics of the regional large-scale ecosystem. This study is based on the Arid Region Ecosystem Model (AEM), using site flux data to optimize, verify, and parameterize the model, and build a dataset of water use efficiency of the arid region ecosystem in Central Asia. The time span of this data set is 1980-2020, involving six types of ecosystems including Central Asian coniferous forests, broad-leaved forests, grasslands, phreatophyte shrubs, non- phreatophyte shrubs and farmland. The region includes five Central Asian countries (Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan and Turkmenistan) and Xinjiang of China. This dataset provides support for understanding the carbon-water dynamics of ecologically fragile areas under the background of global change and maintaining the stability of the ecosystem.
DOI: 10.57760/sciencedb.j00001.00303
title: A long-term monitoring dataset of air and soil temperature during 1996-2020 in Ansai Research Station
title: 1996–2020 年安塞试验站空气和土壤温度长期监测数据集

description: 本数据集由 2 部分数据表组成，分别为 1996–2003 年的日平均气温、日最高和最低气温、地表日平均温度、5 cm、10 cm、15 cm、20 cm、40 cm 日平均土壤温度以及 2004–2020 年的日平均气温、日最高和最低气温、地表日平均温度、5 cm、10 cm、15 cm、20 cm、40 cm、60 cm 和 100 cm 日平均土壤温度。
description: 本数据集由 2 部分数据表组成，分别为 1996–2003 年的日平均气温、日最高和最低气温、地表日平均温度、5 cm、10 cm、15 cm、20 cm、40 cm 日平均土壤温度以及 2004–2020 年的日平均气温、日最高和最低气温、地表日平均温度、5 cm、10 cm、15 cm、20 cm、40 cm、60 cm 和 100 cm 日平均土壤温度。
DOI: 10.57760/sciencedb.j00001.00329
title: Habitat datasets of Poyang Lake wintering swan geese (Anser cygnoides) based on GPS satellite tracking
title: 基于GPS卫星追踪的鸿雁栖息地数据集

description: Habitat provides essential space for species to survive and reproduce. Identifying and protecting East Asian waterfowl habitats is significant to the East Asian-Australasian Flyway (EAAF) migration route. Based on the satellite tracker data of swan geese (anser cygnoides) overwintering in Poyang Lake, Jiangxi obtained from 2018 to 2020. We received 48666 satellite sites of eight swan geese during the complete migration cycle after the data's quality control and status recognition were performed. The habitat datasets of swan geese were extracted through the home range analysis, including the habitat distribution data and the divided habitat distribution data according to the migration period and the individual. The dataset is stored in a vector data format, which attributes table includes species number, number of sites, habitat time, and habitat type such as wintering grounds, stopover sites, and breeding grounds, etc. It can provide primary data for the protection of East Asian migratory geese and their habitats and maintaining regional biodiversity stability.
description: Habitat provides essential space for species to survive and reproduce. Identifying and protecting East Asian waterfowl habitats is significant to the East Asian-Australasian Flyway (EAAF) migration route. Based on the satellite tracker data of swan geese (anser cygnoides) overwintering in Poyang Lake, Jiangxi obtained from 2018 to 2020. We received 48666 satellite sites of eight swan geese during the complete migration cycle after the data's quality control and status recognition were performed. The habitat datasets of swan geese were extracted through the home range analysis, including the habitat distribution data and the divided habitat distribution data according to the migration period and the individual. The dataset is stored in a vector data format, which attributes table includes species number, number of sites, habitat time, and habitat type such as wintering grounds, stopover sites, and breeding grounds, etc. It can provide primary data for the protection of East Asian migratory geese and their habitats and maintaining regional biodiversity stability.
DOI: 10.57760/sciencedb.j00001.00340
title: Evaluation data set of Word Segmentation technology in Minority Languages (MLWS2021)
title: 少数民族语言分词技术评测数据集MLWS2021

description: MLWS2021 word segmentation evaluation data set includes Mongolian, Tibetan and Uyghur languages. The evaluation object is the core technology of automatic word segmentation in Mongolian, Uyghur and Tibetan Languages. On the basis of MLWS2017, the data set is expanded from the previous news field to news, economy, law, entertainment and other fields; The data scale has also expanded from more than 30000 sentences before to 155000 sentences at present. The dataset includes three data files, including: (1) Tibetan.Zip is Tibetan word segmentation and annotation data, with a data volume of 25000 sentences and a file size of 1.52MB; (2) Mongolian.Zip is Mongolian word segmentation and annotation data, with a data volume of 65000 sentences and a file size of 3.16MB; (3)Uyghur.Zip is Uighur word segmentation and annotation data, with a data volume of 65000 sentences and a file size of 5.12MB.
description: MLWS2021 word segmentation evaluation data set includes Mongolian, Tibetan and Uyghur languages. The evaluation object is the core technology of automatic word segmentation in Mongolian, Uyghur and Tibetan Languages. On the basis of MLWS2017, the data set is expanded from the previous news field to news, economy, law, entertainment and other fields; The data scale has also expanded from more than 30000 sentences before to 155000 sentences at present. The dataset includes three data files, including: (1) Tibetan.Zip is Tibetan word segmentation and annotation data, with a data volume of 25000 sentences and a file size of 1.52MB; (2) Mongolian.Zip is Mongolian word segmentation and annotation data, with a data volume of 65000 sentences and a file size of 3.16MB; (3)Uyghur.Zip is Uighur word segmentation and annotation data, with a data volume of 65000 sentences and a file size of 5.12MB.
DOI: 10.57760/sciencedb.j00001.00359
title: Chinese-Fill-in-the-Blank（CFITB）
title: Chinese-Fill-in-the-Blank（CFITB）

description: In order to enrich the Chinese lexical choice data set, taking the people's daily corpus as the initial corpus source, this paper constructs a Chinese test dataset Chinese-Fill-in-the-Blank（CFITB）containing three target word parts of speech: nouns, verbs and adjectives. CFITB dataset contains 500 test samples. Each test sample contains three parts: "number", "test sentence" and "candidate", in which each test sentence contains a target word. Delete the target word and use "__" Instead, the corresponding candidate contains five Chinese words, and each Chinese word is brought into "__" The goal of modeling this dataset is to find the target word corresponding to the most standardized sentence in semantics and grammar from the five candidate sentences.
description: In order to enrich the Chinese lexical choice data set, taking the people's daily corpus as the initial corpus source, this paper constructs a Chinese test dataset Chinese-Fill-in-the-Blank（CFITB）containing three target word parts of speech: nouns, verbs and adjectives. CFITB dataset contains 500 test samples. Each test sample contains three parts: "number", "test sentence" and "candidate", in which each test sentence contains a target word. Delete the target word and use "__" Instead, the corresponding candidate contains five Chinese words, and each Chinese word is brought into "__" The goal of modeling this dataset is to find the target word corresponding to the most standardized sentence in semantics and grammar from the five candidate sentences.
DOI: 10.57760/sciencedb.j00104.00025
title: KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems
title: KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems

description: Table 1 shows statistics of the linkage results. Table 2 presents statistics of the evaluation data sets for the Freebase KB. Table 3 shows statistics of our subgraph for training TransE. Table 4 is performance comparison of different pmethods on the task of last-item recommendation. Four tables and three figues of this paper. Figure 1 presents a linkage example of MovieLens 20M items with Freebase entities. Note: We highlight the MovieLens IDs and Freebase IDs. Figure 2 examines the effect of popularity on the linkage results. Note: We use A, B, … to indicate the bin number in an ordered way. The first three subfigures correspond to the popularity analysis on Freebase, and the last three subfigures correspond to the popularity analysis on YAGO. Figure 3 examines the effect of recency on the linkage results. Note: We use A, B, … to indicate the bin number in an ordered way. The first subfigure corresponds to the recency analysis on Freebase, and the second subfigure corresponds to the recency analysis on YAGO.
description: Table 1 shows statistics of the linkage results. Table 2 presents statistics of the evaluation data sets for the Freebase KB. Table 3 shows statistics of our subgraph for training TransE. Table 4 is performance comparison of different pmethods on the task of last-item recommendation. Four tables and three figues of this paper. Figure 1 presents a linkage example of MovieLens 20M items with Freebase entities. Note: We highlight the MovieLens IDs and Freebase IDs. Figure 2 examines the effect of popularity on the linkage results. Note: We use A, B, … to indicate the bin number in an ordered way. The first three subfigures correspond to the popularity analysis on Freebase, and the last three subfigures correspond to the popularity analysis on YAGO. Figure 3 examines the effect of recency on the linkage results. Note: We use A, B, … to indicate the bin number in an ordered way. The first subfigure corresponds to the recency analysis on Freebase, and the second subfigure corresponds to the recency analysis on YAGO.