This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech co...This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech companies into healthcare,the second will be the monetization of consumer data and the creation of health data marketplaces;and the third will be the growth of Asia as a leader in digital health.Big tech already has the advantage of a massive consiuner base,data and analytics which enable them to understand consumers;and complementary technologies,like wearables,that will drive the consumerization of healthcare.This expansion can happen quickly and already is creating challenges for regulators as they try to catch up.The vast volumes of data and the ability of technology such as blockchain to enable data owners to monetize their data,will lead to the development of health data marketplaces,which can connect and monetize data for data owners and make it available for scientific discovery.The developments in self-sovereign identity,will make it possible for individuals to monetize their health data in the future.Finally,we see the emergence of Asia as a powerhouse for the digital health of the future,with vast populations,mobile technology and increasing adoption of wearable devices.Consumer focused health care driven by data will change the institutional models of the past.展开更多
The environmental,social,and governance(ESG)report is globally recognized as a keystone in sustainable enterprise development.However,current literature has not concluded the development of topics and trends in ESG co...The environmental,social,and governance(ESG)report is globally recognized as a keystone in sustainable enterprise development.However,current literature has not concluded the development of topics and trends in ESG contexts in the twenty-first century.Therefore,we selected 1114 ESG reports from global firms in the technology industry to analyze the evolutionary trends of ESG topics by text mining.We discovered the homogenization effect toward low environmental,medium governance,and high social features in the evolution.We also designed a strategic framework to look closer into the dynamic changes of firms’within-industry representiveness and cross-sector distinctiveness,which demonstrates corporate social responsibility and sustainability.We found that companies are gradually converging toward the third quadrant,which indicates that firms contribute less to industrial outstanding and professional distinctiveness in ESG reporting.Firms choose to imitate ESG reports from each other to mitigate uncertainty and enhance behavioral legitimacy.展开更多
There is a growing demand for time series data analysis in industry areas.Apache loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O performance.With User-Defined Func...There is a growing demand for time series data analysis in industry areas.Apache loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O performance.With User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB directly.To satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache loTDB.This library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,etc.loTDQ enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability analysis.It provides a framework for users to examine loT time series with data quality problems.Experiments show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users.展开更多
文摘This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech companies into healthcare,the second will be the monetization of consumer data and the creation of health data marketplaces;and the third will be the growth of Asia as a leader in digital health.Big tech already has the advantage of a massive consiuner base,data and analytics which enable them to understand consumers;and complementary technologies,like wearables,that will drive the consumerization of healthcare.This expansion can happen quickly and already is creating challenges for regulators as they try to catch up.The vast volumes of data and the ability of technology such as blockchain to enable data owners to monetize their data,will lead to the development of health data marketplaces,which can connect and monetize data for data owners and make it available for scientific discovery.The developments in self-sovereign identity,will make it possible for individuals to monetize their health data in the future.Finally,we see the emergence of Asia as a powerhouse for the digital health of the future,with vast populations,mobile technology and increasing adoption of wearable devices.Consumer focused health care driven by data will change the institutional models of the past.
基金supported by the Major Program of the National Natural Science Foundation of China[grant number 72394375].
文摘The environmental,social,and governance(ESG)report is globally recognized as a keystone in sustainable enterprise development.However,current literature has not concluded the development of topics and trends in ESG contexts in the twenty-first century.Therefore,we selected 1114 ESG reports from global firms in the technology industry to analyze the evolutionary trends of ESG topics by text mining.We discovered the homogenization effect toward low environmental,medium governance,and high social features in the evolution.We also designed a strategic framework to look closer into the dynamic changes of firms’within-industry representiveness and cross-sector distinctiveness,which demonstrates corporate social responsibility and sustainability.We found that companies are gradually converging toward the third quadrant,which indicates that firms contribute less to industrial outstanding and professional distinctiveness in ESG reporting.Firms choose to imitate ESG reports from each other to mitigate uncertainty and enhance behavioral legitimacy.
文摘There is a growing demand for time series data analysis in industry areas.Apache loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O performance.With User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB directly.To satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache loTDB.This library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,etc.loTDQ enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability analysis.It provides a framework for users to examine loT time series with data quality problems.Experiments show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users.
