图 书 馆
完成工作的语义挑战Semantic Challenges in Getting Work Done |
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| 课程网址: | http://videolectures.net/iswc2014_gil_semantic_challenges/ |
| 主讲教师: | Yolanda Gil |
| 开课单位: | 南加州大学 |
| 开课时间: | 2014-10-19 |
| 课程语种: | 英语 |
| 中文简介: |  在新的千年中，工作涉及知识丰富且相互协作的越来越多的任务。我们正在研究语义如何在这两个方面提供帮助。我们的重点是科学工作，尤其是数据分析，在此方面，结合高度分散的科学界的知识和资源具有巨大的潜力。我们在语义工作流中捕获任务知识，并在用户指定高级任务时使用骨骼计划优化算法来帮助他们。但是，工作流的表述本身就是一种协作活动，是一种由任务组成的元工作流，例如查找所需数据或设计新算法以处理可用数据。我们正在研究“有机数据科学”，这是一种新的协作方法，它使科学家可以通过促进临时参与的开放框架来制定和解决科学任务。通过基于社交计算原理的设计，我们的方法使科学过程变得透明，并结合了任务及其属性的语义表示。这项工作涉及的语义挑战众多，并且具有巨大的潜力来改造Web，以帮助我们以更有生产力和出乎意料的方式进行工作。 |
| 课程简介: | In the new millennium, work involves an increasing amount of tasks that are knowledge-rich and collaborative. We are investigating how semantics can help on both fronts. Our focus is scientific work, in particular data analysis, where tremendous potential resides in combining the knowledge and resources of a highly fragmented science community. We capture task knowledge in semantic workflows, and use skeletal plan refinement algorithms to assist users when they specify high-level tasks. But the formulation of workflows is in itself a collaborative activity, a kind of meta-workflow composed of tasks such as finding the data needed or designing a new algorithm to handle the data available. We are investigating "organic data science", a new approach to collaboration that allows scientists to formulate and resolve scientific tasks through an open framework that facilitates ad-hoc participation. With a design based on social computing principles, our approach makes scientific processes transparent and incorporates semantic representations of tasks and their properties. The semantic challenges involved in this work are numerous and have great potential to transform the Web to help us do work in more productive and unanticipated ways. |
| 关 键 词: | 开放框架; 数据分析 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-12-29：zyk |
| 最后编审: | 2020-12-29：zyk |
| 阅读次数: | 39 |