| 1. |
- Ivanova, Milena, et al.
(författare)
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Customizable parallel execution of scientific stream queries
- 2005
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Ingår i: 31st International Conference on Very Large Data Bases.
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Konferensbidrag (refereegranskat)abstract
- Scientific applications require processing high-volume on-line streams of numerical data from instruments and simulations. We present an extensible stream database system that allows scalable and flexible continuous queries on such streams. Application dependent streams and query functions are defined through an object-relational model. Distributed execution plans for continuous queries are described as high-level data flow distribution templates. Using a generic template we define two partitioning strategies for scalable parallel execution of expensive stream queries: window split and window distribute. Window split provides operators for parallel execution of query functions by reducing the size of stream data units using application dependent functions as parameters. By contrast, window distribute provides operators for customized distribution of entire data units without reducing their size. We evaluate these strategies for a typical high volume scientific stream application and show that window split is favorable when expensive queries are executed on limited resources, while window distribution is better otherwise.
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| 2. |
- Ivanova, Milena, et al.
(författare)
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Customizable Parallel Execution of Scientific Stream Queries
- 2005
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Scientific applications require processing high-volume on-line streams of numerical data from instruments and simulations. We present an extensible stream database system that allows scalable and flexible continuous queries on such streams. Application dependent streams and query functions are defined through an Object-Relational model. Distributed execution plans for continuous queries are described as high-level data flow distribution templates. Using a generic template we define two partitioning strategies for scalable parallel execution of expensive stream queries: window split and window distribute. Window split provides operators for customized parallel execution of query functions whose complexity depends on size of the data units on which they are applied. It reduces the size of stream data units using application dependent functions as parameters. By contrast, window distribute provides operators for customized distribution of entire data units without reducing their size. We evaluated these strategies for a typical high volume scientific stream application and show that window split is favorable when computational resources are limited, while window distribute is better when there are sufficient resources.
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| 3. |
- Ivanova, Milena, 1967-
(författare)
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Scalable Scientific Stream Query Processing
- 2005
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Scientific applications require processing of high-volume on-line streams of numerical data from instruments and simulations. In order to extract information and detect interesting patterns in these streams scientists need to perform on-line analyses including advanced and often expensive numerical computations. We present an extensible data stream management system, GSDM (Grid Stream Data Manager) that supports scalable and flexible continuous queries (CQs) on such streams. Application dependent streams and query functions are defined through an object-relational model. Distributed execution plans for continuous queries are specified as high-level data flow distribution templates. A built-in template library provides several common distribution patterns from which complex distribution patterns are constructed. Using a generic template we define two customizable partitioning strategies for scalable parallel execution of expensive stream queries: window split and window distribute. Window split provides parallel execution of expensive query functions by reducing the size of stream data units using application dependent functions as parameters. By contrast, window distribute provides customized distribution of entire data units without reducing their size. We evaluate these strategies for a typical high volume scientific stream application and show that window split is favorable when expensive queries are executed on limited resources, while window distribution is better otherwise. Profile-based optimization automatically generates optimized plans for a class of expensive query functions. We further investigate requirements for GSDM in Grid environments. GSDM is a fully functional system for parallel processing of continuous stream queries. GSDM includes components such as a continuous query engine based on a data-driven data flow paradigm, a compiler of CQ specifications into distributed execution plans, stream interfaces and communication primitives. Our experiments with real scientific streams on a shared-nothing architecture show the importance of both efficient processing and communication for efficient and scalable distributed stream processing.
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| 4. |
- Jack, Tullia, et al.
(författare)
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The Sustainability Implications of Single Occupancy Households
- 2021
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Ingår i: Buildings and Cities. - 2632-6655.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Single occupancy households consume more resources per capita, and demographics suggest single occupancy is now widespread in many countries. Environmental policies need to adjust to include per capita consumption to account for occupancy and efficient use of resources. Diana Ivanova, Tullia Jack, Milena Büchs and Kirsten Gram-Hanssen explain how the sharing of resources at domestic, neighbourhood and urban scales can have positive environmental and social impacts.
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| 5. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 6. |
- Osoegawa, Kazutoyo, et al.
(författare)
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Quality control project of NGS HLA genotyping for the 17th International HLA and Immunogenetics Workshop
- 2019
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Ingår i: Human Immunology. - : ELSEVIER SCIENCE INC. - 0198-8859 .- 1879-1166. ; 80:4, s. 228-236
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Tidskriftsartikel (refereegranskat)abstract
- The 17th International HLA and Immunogenetics Workshop (IHIW) organizers conducted a Pilot Study (PS) in which 13 laboratories (15 groups) participated to assess the performance of the various sequencing library preparation protocols, NGS platforms and software in use prior to the workshop. The organizers sent 50 cell lines to each of the 15 groups, scored the 15 independently generated sets of NGS HLA genotyping data, and generated "consensus" HLA genotypes for each of the 50 cell lines. Proficiency Testing (PT) was subsequently organized using four sets of 24 cell lines, selected from 48 of 50 PS cell lines, to validate the quality of NGS HLA typing data from the 34 participating IHIW laboratories. Completion of the PT program with a minimum score of 95% concordance at the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci satisfied the requirements to submit NGS HLA typing data for the 17th IHIW projects. Together, these PS and PT efforts constituted the 17th IHIW Quality Control project. Overall PT concordance rates for HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4 and HLA-DRB5 were 98.1%, 97.0% and 98.1%, 99.0%, 98.6%, 98.8%, 97.6%, 96.0%, 99.1%, 90.0% and 91.7%, respectively. Across all loci, the majority of the discordance was due to allele dropout. The high cost of NGS HLA genotyping per experiment likely prevented the retyping of initially failed HLA loci. Despite the high HLA genotype concordance rates of the software, there remains room for improvement in the assembly of more accurate consensus DNA sequences by NGS HLA genotyping software.
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