STI Summit 2011 - Shortipedia
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Shortipedia is a website that collects assertions from various sources on the semantic web and displays them in an easy to understand format. It finds information about requested topics from Wikipedia, SameAs.org, and Sindice. Users can bind linked entities, see data from related entities, add their own assertions, and integrate additional data. Key lessons learned include that semantic web data can be noisy, hard to understand, and labels are unreliable. Representing diverse knowledge and deciding semantics is also challenging.
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STI Summit 2011 - di@scale
The document discusses data integration challenges at large Fortune 100 companies. It notes that these companies typically have around 10,000 information systems and databases, with hundreds added each year. Data integration accounts for around 40% of software project costs due to the need to combine data from thousands of source databases across various business units. The conclusion is that every large organization depends critically on effective data and data integration to support their complex, interconnected information ecosystems.
STI Summit 2011 - A personal look at the future of Semantic Technologies
STI Summit 2011 - A personal look at the future of Semantic TechnologiesSemantic Technology Institute International
1. The future of Semantic Technologies lies not in the current Semantic Web technology stack but in the underlying principles, such as making domain knowledge editable, shareable and linkable.
2. There are still many exciting topics for the future, such as pushing the boundaries of complex information processing in databases and using web-like data integration to tackle very large-scale data integration problems for entire enterprises or scientific fields.STI Summit 2011 - Visual analytics and linked data
This document discusses using visual analytics techniques on linked data. It begins by motivating the combination of these fields by noting that while linked data services excel at data access, they lack support for complex analytical scenarios. It then provides examples of how visual analytics has been used in other domains like analyzing financial data, patent trends, and simulating biological processes. Finally, it outlines how visual analytics could be applied to linked data, including aggregating and filtering data, implementing analytical workflows, and using visualization techniques to enable discovery and presentation of insights to domain experts. The goal would be supporting collaborative analytical tasks on a global scale.
STI Summit 2011 - LS4 LS Khaos
1) Producing life sciences linked open data presents challenges as biologists want to publish and control their data but providing query and analysis services is expensive. They need technical assistance and funding support.
2) Consuming linked data in life sciences means connecting data to existing standards like pathways and proteins. Data analysis, mining, crawling and reasoning services are needed but expensive for individual database owners.
3) Scalability issues arise when reasoning over complex ontologies like BioPAX Level 3 with large datasets, as state-of-the-art reasoners cannot handle inconsistencies or provide query endpoints for such data.
STI Summit 2011 - Making linked data work
The document discusses building semantic web applications using linked data. It describes typical applications, current approaches to supporting applications over linked data using representative architectures and crawling patterns. The document argues that semantics can help by providing SDKs underpinned by datasets and ontologies, supporting collaborative development, and using common front ends and application descriptions. Finally, it presents MicroWSMO and WSMO-Lite as ways to describe minimal service models and service lifecycles for semantic web applications.
STI Summit 2011 - Beyond privacy
This document discusses issues surrounding privacy and data integration. It explores arguments for reduced privacy protections, such as the idea that individuals have zero privacy anyway and companies should be allowed to freely use customer data to enable innovation. However, others argue that a post-privacy society where all data is freely shared may not be desirable. The document examines stakeholders' perspectives and wider issues regarding data ownership and business models in a world with integrated data.
More from Semantic Technology Institute International (20)
STI Summit 2011 - A personal look at the future of Semantic Technologies
STI Summit 2011 - A personal look at the future of Semantic Technologies
STI Summit 2011 - Visual analytics and linked data
STI Summit 2011 - Visual analytics and linked data
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STI Summit 2011 - Shortipedia
- 1. i shortipedia Second-hand facts. For free. Denny Vrandečić (KIT / Wikimedia.de), Varun Ratnakar (USC), Markus Kröztsch (Oxford), Yolanda Gil (USC)
- 2. What is Shortipedia? o Website o Based on Semantic MediaWiki o Collects assertions about everything i o Provenance of these assertions o Multilingual labels for everything o Displays data from the Semantic Web o Allows easy integration of that data
- 3. What does Shortipedia do? o Creates a page on requested topic o Finds Wikipedia (for identity) o Uses SameAs.org and Sindice i o Let users bind linked entities o Displays data from linked entities o Let users integrate assertions o Let users create new assertions
- 4. Demo time! i
- 5. Design decisions o Wikipedia / DBpedia as identity provider o Don’t trust the triples o Consistency not required i o Triples are immutable o First map, then add o sameAs is different
- 6. Lessons learned o Data is noSi_y o Data is hard to understand o Labels are hard to get / unreliable o The Semantic Web is slow i o No idea how to represent the diverse knowledge o Semantics decided by ‘commoners’, not experts o Semantic Web researchers should build a Semantic Web application