The construction of digital substations is the foundation of digital power grids. In view of technical basis of digital substation at present, the authors analyze main technical features reflecting the property of digital substation and point out that the non-conventional instrument transformer, the reliability of network communication, IED interoperability, time synchronization and information security are key technologies to implement digital substation. Finally the technical and economical significance of these new technologies are summarized.

The construction of digital substations is the foundation of digital power grids. In view of technical basis of digital substation at present, the authors analyze main technical features reflecting the property of digital substation and point out that the non-conventional instrument transformer, the reliability of network communication, IED interoperability, time synchronization and information security are key technologies to implement digital substation. Finally the technical and economical significance of these new technologies are summarized.

从总体可靠度和元件重要度两个方面对全数字化保护系统的可靠性进行研究。基于可靠性框图和邻接矩阵方法建立了总体可靠性模型，然后基于概率重要度和关键重要度，建立了全数字化保护系统元件重要度评价指标。其中，概率重要度用于发现系统中的薄弱环节，以指导和优化系统设计；关键重要度用于指导系统维修。为说明所提方法的有效性，提出了6种全数字化保护系统的典型结构，并利用上述方法，对其进行了详细的计算与分析。

从总体可靠度和元件重要度两个方面对全数字化保护系统的可靠性进行研究。基于可靠性框图和邻接矩阵方法建立了总体可靠性模型，然后基于概率重要度和关键重要度，建立了全数字化保护系统元件重要度评价指标。其中，概率重要度用于发现系统中的薄弱环节，以指导和优化系统设计；关键重要度用于指导系统维修。为说明所提方法的有效性，提出了6种全数字化保护系统的典型结构，并利用上述方法，对其进行了详细的计算与分析。

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.