Big Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data,especially for managing satellite time series.These infrastructures build on the concept of multidimensional data m...Big Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data,especially for managing satellite time series.These infrastructures build on the concept of multidimensional data model(data hypercube)and are complex systems engaging different disciplines and expertise.For this reason,their interoperability capacity has become a challenge in the Global Change and Earth System science domains.To address this challenge,there is a pressing need in the community to reach a widely agreed definition of Data-Cube infrastructures and their key features.In this respect,a discussion has started recently about the definition of the possible facets characterizing a Data-Cube in the Earth Observation domain.This manuscript contributes to such debate by introducing a view-based model of Earth Data-Cube systems to design its infrastructural architecture and content schemas,with the final goal of enabling and facilitating interoperability.It introduces six modeling views,each of them is described according to:its main concerns,principal stakeholders,and possible patterns to be used.The manuscript considers the Business Intelligence experience with Data Warehouse and multidimensional“cubes”along with the more recent and analogous development in the Earth Observation domain,and puts forward a set of interoperability recommendations based on the modeling views.展开更多
为了借助信息化手段高效驱动非常规油气资源开发、解决页岩气地质工程协同研究中专业数据的共享与分析问题,采用数据立方体模型结合商业智能(Business Intelligence, BI)工具进行数据管理,搭建了页岩气地质工程一体化数据分析平台(以下...为了借助信息化手段高效驱动非常规油气资源开发、解决页岩气地质工程协同研究中专业数据的共享与分析问题,采用数据立方体模型结合商业智能(Business Intelligence, BI)工具进行数据管理,搭建了页岩气地质工程一体化数据分析平台(以下简称一体化平台)。研究结果表明:①通过建设数据汇集区,能够有效解决数据来源问题,实现一体化平台对页岩气各专业数据的统一汇集与存储;②通过建设数据资产区,以“勘探开发数据模型(EPDM)+业务宽表”(EPDM,Exploration and Production Data Model)形成专业数据仓库,能够有效解决数据质量问题,以获取高品质专业数据,并为数据立方体的构建奠定基础;③通过构建支撑多个专业应用场景的一系列数据立方体,能够统一指标口径,为场景应用提供数据支撑;④通过构建核心指标看板,对各类关键指标进行可视化展示,可以形成若干可复用的数据看板组件和特定功能模块,为场景应用提供应用支撑;⑤通过建设钻井动态、压裂动态、返排动态、生产动态等专业应用场景,可以形成业务主题域,从而建立起全面的科研生产管理体系。结论认为:①所搭建的一体化平台能够十分便捷地将多维度数据进行可视化展示,快速响应用户的查询需求,并且数据可以在不同维度来回切换之间保持闭合;②该成果可以为页岩气地质工程协同研究提供技术支撑,对类似BI应用平台的建设也有参考借鉴意义。展开更多
基金This research was supported by the European Commission in the framework of the H2020 ECOPOTENTIAL project(ID 641762)the H2020 SeaDataCloud project(ID 730960),and the FP7 EarthServer project(ID 283610).
文摘Big Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data,especially for managing satellite time series.These infrastructures build on the concept of multidimensional data model(data hypercube)and are complex systems engaging different disciplines and expertise.For this reason,their interoperability capacity has become a challenge in the Global Change and Earth System science domains.To address this challenge,there is a pressing need in the community to reach a widely agreed definition of Data-Cube infrastructures and their key features.In this respect,a discussion has started recently about the definition of the possible facets characterizing a Data-Cube in the Earth Observation domain.This manuscript contributes to such debate by introducing a view-based model of Earth Data-Cube systems to design its infrastructural architecture and content schemas,with the final goal of enabling and facilitating interoperability.It introduces six modeling views,each of them is described according to:its main concerns,principal stakeholders,and possible patterns to be used.The manuscript considers the Business Intelligence experience with Data Warehouse and multidimensional“cubes”along with the more recent and analogous development in the Earth Observation domain,and puts forward a set of interoperability recommendations based on the modeling views.
文摘为了借助信息化手段高效驱动非常规油气资源开发、解决页岩气地质工程协同研究中专业数据的共享与分析问题,采用数据立方体模型结合商业智能(Business Intelligence, BI)工具进行数据管理,搭建了页岩气地质工程一体化数据分析平台(以下简称一体化平台)。研究结果表明:①通过建设数据汇集区,能够有效解决数据来源问题,实现一体化平台对页岩气各专业数据的统一汇集与存储;②通过建设数据资产区,以“勘探开发数据模型(EPDM)+业务宽表”(EPDM,Exploration and Production Data Model)形成专业数据仓库,能够有效解决数据质量问题,以获取高品质专业数据,并为数据立方体的构建奠定基础;③通过构建支撑多个专业应用场景的一系列数据立方体,能够统一指标口径,为场景应用提供数据支撑;④通过构建核心指标看板,对各类关键指标进行可视化展示,可以形成若干可复用的数据看板组件和特定功能模块,为场景应用提供应用支撑;⑤通过建设钻井动态、压裂动态、返排动态、生产动态等专业应用场景,可以形成业务主题域,从而建立起全面的科研生产管理体系。结论认为:①所搭建的一体化平台能够十分便捷地将多维度数据进行可视化展示,快速响应用户的查询需求,并且数据可以在不同维度来回切换之间保持闭合;②该成果可以为页岩气地质工程协同研究提供技术支撑,对类似BI应用平台的建设也有参考借鉴意义。
