商业上赋予研究的关联开放数据生态系统 - 代码方法Commercially empowered Linked Open Data Ecosystems in Research – The CODE Approach |
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课程网址: | http://videolectures.net/dataforum2012_lindstaedt_code/ |
主讲教师: | Stefanie Lindstaedt |
开课单位: | 技术中心有限公司 |
开课时间: | 2010-07-16 |
课程语种: | 英语 |
中文简介: | 链接开放数据(LOD)显示出成为WWW下一个重大进化步骤的巨大潜力。然而,由于缺少使用和商业化策略,这种潜力仍未得到充分利用.CODE的愿景是为基于Web的商业化生态系统建立基础链接开放数据的基础。该生态系统在数据市场中的传统(例如数据提供者和消费者)和非传统(例如数据分析师)角色之间建立了可持续的商业价值创造链。货币激励措施将激励人们分析,组织和整合LOD与非结构化信息源,从而提高数据质量和数量。我们的用例侧重于研究论文作为挖掘事实的来源以及它们与LOD存储库和轻量级本体的集成。因此,我们将通过创建链接科学数据云,在语义,机器可读级别上利用研究出版物中包含的丰富知识。这个云将通过使科学知识更容易和透明来对创新驱动的业务产生影响。因此,我们将研究和开发:众包采用语义丰富和集成技术,将非结构化信息中包含的事实整合到LOD cloudfederated,来源启用查询LOD存储库中的事实发现方法基于可视化分析界面,支持基于人类的分析,整合和组织在预想的生态系统中实现的事实社会经济因素角色,收入模型和价值链。 |
课程简介: | Linked Open Data (LOD) shows enormous potential in becoming the next big evolutionary step of the WWW. However, this potential remains largely untapped due to missing usage and commercialisation strategies. CODE’s vision is to establish the foundation for a web-based, commercially oriented ecosystem for Linked Open Data. This ecosystem establishes a sustainable and commercial value-creation-chain among traditional (e.g. data provider and consumer) and non-traditional (e.g. data analyst) roles in data marketplaces. Monetary incentives will motivate people to analyse, organise and integrate LOD with unstructured information sources thereby increasing data quality and quantity. Our use case focuses on research papers as a source for mining facts and their integration into LOD repositories and light-weight ontologies. Hence, we will leverage the wealth of knowledge contained in research publications on a semantic, machine-readable level by creating the Linked Science Data cloud. This cloud will have an impact on innovation driven businesses by making scientific knowledge more accessible and transparent. Therefore, we will research and develop: crowd-sourcing enabled semantic enrichment & integration techniques for integrating facts contained in unstructured information into the LOD cloud federated, provenance-enabled querying methods for fact discovery in LOD repositories web-based visual analysis interfaces to support human based analysis, integration and organisation of facts socio-economic factors - roles, revenue-models and value chains - realisable in the envisioned ecosystem. |
关 键 词: | 链接开放数据; 商业化生态系统; 商业价值创造链 |
课程来源: | 视频讲座网 |
最后编审: | 2019-03-17:cwx |
阅读次数: | 46 |