As multi-scale databases based on scale series of map data are built, conceptual models are needed to define proper multi-scale representation formulas and to extract model entities and the relationships among them. H...As multi-scale databases based on scale series of map data are built, conceptual models are needed to define proper multi-scale representation formulas and to extract model entities and the relationships among them. However, the results of multi-scale conceptual abstraction schema may differ, according to which cognition, abstraction and application views are utilized, which presents an obvious obstacle to the reuse and sharing of spatial data. To facilitate the design of unified, common and objective abstract schema views for multi-scale spatial databases, this paper proposes an ontology-based analysis method for the multi-scale modeling of geographical features. It includes a three-layer ontology model, which serves as the framework for common multi-scale abstraction schema; an explanation of formulary abstractions accompanied by definitions of entities and their relationships at the same scale, as well as different scales,which are meant to provide strong feasibility, expansibility and speciality functions; and a case in point involving multi-scale representations of road features, to verify the method's feasibility.展开更多
In this paper,we present the virtual knowledge graph(VKG)paradigm for data integration and access,also known in the literature as Ontology-based Data Access.Instead of structuring the integration layer as a collection...In this paper,we present the virtual knowledge graph(VKG)paradigm for data integration and access,also known in the literature as Ontology-based Data Access.Instead of structuring the integration layer as a collection of relational tables,the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge.We explain the main notions of this paradigm,its tooling ecosystem and significant use cases in a wide range of applications.Finally,we discuss future research directions.展开更多
Since the boom of biomedical big data studies,various big data processing technologies have been developed rapidly.As an important form of knowledge representation,ontology has become an important means for the utiliz...Since the boom of biomedical big data studies,various big data processing technologies have been developed rapidly.As an important form of knowledge representation,ontology has become an important means for the utilization and integration of biomedical big data.The emergence of new technologies for ontology development has resulted in the generation of many biomedical ontologies by many ontology development communities.The Open Biological and Biomedical Ontology Foundry,an academic organization for bio-ontology developers,has provided a set of principles to guide community-based open ontology construction.The Open Biological and Biomedical Ontology Foundry have also built many widely used ontologies,such as Gene Ontology,Human Phenotype Ontology,and Chemical Entities of Biological Interest.Other various ontology repositories have also been created and used to support ontology reuse.Many efficient tools for ontology applications,such as data annotation and terms mapping,have also been developed.High quality ontologies are also being used to develop new methods and tools for biomedical data analysis.The applications of Gene Ontology and Human Phenotype Ontology for data analysis and integration in recent years are reviewed here.To promote the development and applications of biomedical ontologies in China,a research community,OntoChina,was founded recently.OntoChina aims to support the development of reference ontologies,especially bilingual and Chinese translated ontologies.OntoChina also encourages ontology developers to follow the Open Biological and Biomedical Ontology Foundry principles.展开更多
Achieving continuous innovation in organizations requires a balance between exploiting yet acquired knowledge and exploring new knowledge. In addition to having the adequate resources, change and innovation capabiliti...Achieving continuous innovation in organizations requires a balance between exploiting yet acquired knowledge and exploring new knowledge. In addition to having the adequate resources, change and innovation capabilities require specific management support and organizational structures. Recent research has pointed out the importance of social network structure and of the activity of agents that work across domains or disciplines in the innovation-oriented behaviour of organizations. As a consequence, information systems should ideally be able to support the analysis, development and management of such social structure for the benefit of organizational objectives. Current social network interfaces provide an established mental model to workers that can be hypothesized to be adequate for supporting activities that foster innovative behaviour. That behaviour is facilitated through exposing the activities of other workers across organizational structures. This paper reports on the design of a user interface specifically targeted to manage the social aspects of innovation based on some aspects of Hargadon＇s model of innovation and knowledge brokering. The emergent nature of interactions in social network sites is used as the metaphor to foster situated cognition. The interface design assessment is described and some metrics for innovative behaviour that could be derived for such an interface are sketched.展开更多
Modern information systems require the orchestration of ontologies,conceptual data modeling techniques,and efficient data management so as to provide a means for better informed decision-making and to keep up with new...Modern information systems require the orchestration of ontologies,conceptual data modeling techniques,and efficient data management so as to provide a means for better informed decision-making and to keep up with new requirements in organizational needs.A major question in delivering such systems,is which components to design and put together to make up the required“knowledge to data”pipeline,as each component and process has trade-offs.In this paper,we introduce a new knowledge-to-data architecture,KnowID.It pulls together both recently proposed components and we add novel transformation rules between Enhanced Entity-Relationship(EER)and the Abstract Relational Model to complete the pipeline.KnowID’s main distinctive architectural features,compared to other ontology-based data access approaches,are that runtime use can avail of the closed world assumption commonly used in information systems and of full SQL augmented with path queries.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.40471090)the Science Innovation Group of Beijing.
文摘As multi-scale databases based on scale series of map data are built, conceptual models are needed to define proper multi-scale representation formulas and to extract model entities and the relationships among them. However, the results of multi-scale conceptual abstraction schema may differ, according to which cognition, abstraction and application views are utilized, which presents an obvious obstacle to the reuse and sharing of spatial data. To facilitate the design of unified, common and objective abstract schema views for multi-scale spatial databases, this paper proposes an ontology-based analysis method for the multi-scale modeling of geographical features. It includes a three-layer ontology model, which serves as the framework for common multi-scale abstraction schema; an explanation of formulary abstractions accompanied by definitions of entities and their relationships at the same scale, as well as different scales,which are meant to provide strong feasibility, expansibility and speciality functions; and a case in point involving multi-scale representations of road features, to verify the method's feasibility.
文摘In this paper,we present the virtual knowledge graph(VKG)paradigm for data integration and access,also known in the literature as Ontology-based Data Access.Instead of structuring the integration layer as a collection of relational tables,the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge.We explain the main notions of this paradigm,its tooling ecosystem and significant use cases in a wide range of applications.Finally,we discuss future research directions.
基金This work was supported by Chinese Academy of Medical Science(CAMS)Innovation Fund for Medical Sciences(CIFMS)(No.2018-I2M-AI-009 to XY)Independent Subject Project Funded by Basic Scientific Research Fund of Chinese Academy of Chinese Medical Science(No.zz110318 to YZ)the University of Michigan Global Reach Award(to YH).
文摘Since the boom of biomedical big data studies,various big data processing technologies have been developed rapidly.As an important form of knowledge representation,ontology has become an important means for the utilization and integration of biomedical big data.The emergence of new technologies for ontology development has resulted in the generation of many biomedical ontologies by many ontology development communities.The Open Biological and Biomedical Ontology Foundry,an academic organization for bio-ontology developers,has provided a set of principles to guide community-based open ontology construction.The Open Biological and Biomedical Ontology Foundry have also built many widely used ontologies,such as Gene Ontology,Human Phenotype Ontology,and Chemical Entities of Biological Interest.Other various ontology repositories have also been created and used to support ontology reuse.Many efficient tools for ontology applications,such as data annotation and terms mapping,have also been developed.High quality ontologies are also being used to develop new methods and tools for biomedical data analysis.The applications of Gene Ontology and Human Phenotype Ontology for data analysis and integration in recent years are reviewed here.To promote the development and applications of biomedical ontologies in China,a research community,OntoChina,was founded recently.OntoChina aims to support the development of reference ontologies,especially bilingual and Chinese translated ontologies.OntoChina also encourages ontology developers to follow the Open Biological and Biomedical Ontology Foundry principles.
文摘Achieving continuous innovation in organizations requires a balance between exploiting yet acquired knowledge and exploring new knowledge. In addition to having the adequate resources, change and innovation capabilities require specific management support and organizational structures. Recent research has pointed out the importance of social network structure and of the activity of agents that work across domains or disciplines in the innovation-oriented behaviour of organizations. As a consequence, information systems should ideally be able to support the analysis, development and management of such social structure for the benefit of organizational objectives. Current social network interfaces provide an established mental model to workers that can be hypothesized to be adequate for supporting activities that foster innovative behaviour. That behaviour is facilitated through exposing the activities of other workers across organizational structures. This paper reports on the design of a user interface specifically targeted to manage the social aspects of innovation based on some aspects of Hargadon＇s model of innovation and knowledge brokering. The emergent nature of interactions in social network sites is used as the metaphor to foster situated cognition. The interface design assessment is described and some metrics for innovative behaviour that could be derived for such an interface are sketched.
文摘Modern information systems require the orchestration of ontologies,conceptual data modeling techniques,and efficient data management so as to provide a means for better informed decision-making and to keep up with new requirements in organizational needs.A major question in delivering such systems,is which components to design and put together to make up the required“knowledge to data”pipeline,as each component and process has trade-offs.In this paper,we introduce a new knowledge-to-data architecture,KnowID.It pulls together both recently proposed components and we add novel transformation rules between Enhanced Entity-Relationship(EER)and the Abstract Relational Model to complete the pipeline.KnowID’s main distinctive architectural features,compared to other ontology-based data access approaches,are that runtime use can avail of the closed world assumption commonly used in information systems and of full SQL augmented with path queries.
