Strategic planning for national biomedical big data infrastructure in China

The promise that big data will revolutionize scientific discovery and technology innovation is now being widely recognized. With the explosive growth of biomedical data, life science is being transformed into a digital science in which novel insights are gained from in-depth data analysis and modeling. Extensive and innovative utilization of biomedical big data is a key to the success of precision medicine. Therefore, constructing a centralized national-level biomedical big data infrastructure becomes crucial and urgent for China. Such infrastructure should achieve superb capacity of safe data storage, standardized data processing and quality control, systematic data integration across multiple types, and in-depth data mining and effective data sharing. Full data chain service including information retrieval, knowledge discovery and technology support can be provided to data centers, research institutes and healthcare industries. Relying on Shanghai Institutes for Biological Sciences, agreements have been signed that a main node of the infrastructure will be located in Shanghai, and a backup node will be set up in Guizhou Province. After a construction period of five years, the infrastructure should greatly enhance China＇s core competence in collection, interpretation and application of biomedical big data.

Bibliometric evaluation of the status of Picea research and research hotspots:comparison of China to other countries

Picea Mill.species are important components of boreal and subalpine forests.They have a wide geographical range in the Northern Hemisphere,extending from the Eurasian continent to North America.In this study,publications on Picea species from 2002 to 2016 were identified via the Web of Science(WoS)and the China National Knowledge Infrastructure(CNKI)databases,and subjected to relationship network visualization using CiteSpace software.This study represents the first such analysis of Picea and provides a reference for bibliometrics in forest tree species research.The results show that the total number of publications on Picea archived in WoS was20,958 and that the number of papers published annually has increased over time,peaking at 1725 in 2013.The studies were mainly conducted in North America,Europe and Asia;among them,Canada published the most papers and showed the strongest betweenness centrality(0.11).Among research institutions,the Swedish University of Agricultural Sciences in Uppsala had the highest publication record.The research contributions of the Chinese Academy of Sciences,the Chinese Academy of Forestry,and Beijing Forestry University have improved rapidly in recent years,greatly enhancing the international impact of Chinese research in this field.The research contents were grouped into five categories:forest ecosystems,pest resistance,extraction and functional analyses of active ingredients from various plant organs,nursery and afforestation techniques,and timber quality research.In China,the number of papers from the CNKI database was4532,increasing at an even pace.The research topics on Picea included forest ecosystems,seedling and afforestation techniques,basic studies on individual species and populations,and pests and diseases.Within and outside China,hotspots in Picea research included the relationships between Picea and environmental factors,and the genomic sequences of Picea.

Thirty years(1984–2014) of groundwater science teaching and research in China: A dissertation-based bibliometric survey

In order to track the footprint of groundwater science teaching and research in China during the past years, a bibliometric analysis was conducted based on the database of China National Knowledge Infrastructure(CNKI), which covered the time span from 1984 to present and included more than 2.6 million master and doctoral dissertations from hundreds of institutions of China's Mainland. The bibliometric analysis summarized output, geographical, and institutional patterns, as well as research directions and hotspots in groundwater studies in China in the period of 1984-2014. A total of 1 396 groundwater-related dissertations including 1 161 master dissertations and 235 doctoral dissertations, contributed by 128 institutions distributed in 53 cities nationwide, were searched out in the database. It can be seen obviously that, the groundwater science teaching and research in China has experienced a notable growth in the past three decades especially during 2000-2014. Groundwater modeling, resource, and exploitation were the top three major subject categories; China University of Geosciences(Beijing), Jilin University and Chang’an University were the top three productive institutions together accounting for more than one third of the total dissertations and 50% of the doctoral dissertations, which further prompted the cities(Beijing, Changchun, and Xi’an) to become the top three productive cities. The dissertations generally covered all the international research topics, which indicated that hydrogeologists in China have tracked the international frontier closely during the past decades. The keywords analysis revealed that,(1) numerical modeling was still the hottest topic and PHREEQC, MODFLOW, GMS, and FEFLOW were the four most used softwares;(2) the topics related with groundwater pollution and quality developed steadily and rapidly;(3) environmental isotopes and GIS were frequently used tools for hydrogeological condition analysis, and spatial data processing respectively; and(4) the unsaturated zone as an integral part of aquifers attracted more and more attentions from hydrogeologists focus on saturated zone.

Sustainable development and geospatial information:a strategic framework for integrating a global policy agenda into national geospatial capabilities

The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the next 15 years.Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature.Many of the issues impacting sustainable development can be analyzed,modeled,and mapped within a geographic context,which in turn can provide the integrative framework necessary for global collaboration,consensus and evidence-based decision-making.However,and despite significant advances in geospatial information technologies,there is a lack of awareness,understanding and uptake,particular at the policy and decision-making level,of the vital and integrative role of geospatial information and related enabling architectures such as National Spatial Data Infrastructures.This paper reasons that the role of geospatial information in contributing to sustainable development has not adequately been described by either the sustainable development policy practice or by the geospatial professional community.This lack of policy and guidance,with commensurate critical gaps and connection points with national geospatial frameworks,is a visible impediment to developing countries and those most affected by the challenges and need to achieve sustainable development.The global geospatial community now has a unique opportunity to integrate and connect geospatial information into the global development agenda in a more holistic and sustainable manner,specifically in contributing their data resources toward measuring and monitoring the 17 Sustainable Development Goals,and their 169 associated targets,through the global indicator framework that anchors the 2030 Agenda for Sustainable Development.This paper introduces and discusses a new strategic framework for linking a global policy to national geospatial capabilities.

Building geospatial infrastructure

Many visions for geospatial technology have been advanced over the past half century.Initially researchers saw the handling of geospatial data as the major problem to be overcome.The vision of geographic information systems arose as an early international consensus.Later visions included spatial data infrastructure,Digital Earth,and a nervous system for the planet.With accelerating advances in information technology,a new vision is needed that reflects today’s focus on open and multimodal access,sharing,engagement,the Web,Big Data,artificial intelligence,and data science.We elaborate on the concept of geospatial infrastructure,and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.

How is pandemic perceived in China?A case study of COVID-19

To help the government better understand and manage public sentiments,and help the public establish the values of rational participation in online discussions related to COVID-19,it is necessary to explore the themes and emotions of different subjects discussing the pandemic on social media platforms.The study takes a comprehensive view by combining social media and scholarly outputs data.In particular,WeChat articles are investigated to reveal the public concern and public sentiment towards COVID-19,and WeChat mentions to scholarly papers are identified to show the interaction between the public and researchers.Text analysis is conducted to construct co-occurrence networks and reveal the distribution of themes.VOSviewer is applied to network visualization.Statistical and comparative analysis showed that discussion about COVID-19 keeps hot on WeChat.WeChat offical accounts from the information industry dominate,suggesting a free and flexible discussing environment.Topics on WeChat overlap with that of scholarly papers but have a much broader scope.WeChat mentions to scholarly papers has bridged the public with the research and has a high coverage of 61.7%.Public sentiment in WeChat is positive,demonstrating good confidence in defeating the pandemic.These findings are helpful in understanding the social attitude towards and comprehensive perception of COVID-19 in China.

DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support Digital Earth initiatives

This paper proposes a novel data indexing scheme,the distributed access pattern R-tree(DAPR-tree),for spatial data retrieval in a distributed computing environment.As compared to traditional distributed indexing schemes,the DAPR-tree introduces the data access patterns during the indexing utilization stage so that a more balanced indexing structure can be provided for spatial applications(e.g.Digital Earth data warehouse).In this new indexing scheme,(a)an indexing penalty matrix is proposed by considering the balance of data number,topology and access load between different indexing nodes;(b)an‘access possibility’element is integrated to a classic‘Master-Client’structure for a distributed indexing environment;and(c)indexing algorithm for the DAPR-tree is provided for index implementations.By using a duplication of official GEOSS Clearinghouse system as a case study,the DAPR-tree was evaluated in a number of scenarios.The results show that our indexing schemes generally outperform(around 9%)traditional distributed indices with the utilization of data access patterns.Finally,we discuss the applicability of the DARP-tree and document DARP-tree shortcomings to encourage researchers pursuing related topics in Big Data indexing for Digital Earth and other geospatial initiatives.