RDF - Semantic Web Standards
Overview RDF is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed. RDF extends the linking structure of the Web to use URIs to name the relationship between things as well as the two ends of the link (this is usually referred to as a “triple”). Using this simple model, it allows structured and semi-structured data to be mixed, exposed, and shared across different applications. This linking structure forms a directed, labeled graph, where the edges represent the named link between two resources, represented by the graph nodes. Recommended Reading The RDF 1.1 specification consists of a suite of W3C Recommendations and Working Group Notes, published in 2014. A number of textbooks have been published on RDF and on Semantic Web in general. Discussions on a possible next version of RDF
URL vs. URI vs. URN: The Confusion Continues
A year has passsed since my last post on URIs and URLs and it would seem that some of the concepts are still lost on some folks. With that said, I figured I’d throw up another post that I could try and address some of the questions raised in the comments of both posts. URLs and URNs are both URIs This is one point that can’t be stated enough. Examples of URLs and URNs: People have also suggested that these posts could have been more helpful if I had provided some examples that illustrate the difference between a URL and a URI. Again, all of the examples above are all valid examples of URIs. There’s a very informative page by Tim Berners-Lee that provides a lot of good deails on Uniform Resource Identifiers. “The only thing you can use an identifier for is to refer to an object. When you followed the link to this page, you didn’t have to do anything other than clicking it. Can we say that:“ No. Another commenter also asserted the following:
RelFinder - Visual Data Web
Are you interested in how things are related with each other? The RelFinder helps to get an overview: It extracts and visualizes relationships between given objects in RDF data and makes these relationships interactively explorable. Highlighting and filtering features support visual analysis both on a global and detailed level. The RelFinder is based on the open source framework Adobe Flex, easy-to-use and works with any RDF dataset that provides standardized SPARQL access. Check out the following links for some examples: The RelFinder can easily be configured to work with different RDF datasets. The RelFinder can also be more deeply integrated with your project: Integrating the RelFinder See the following examples of how the RelFinder is integrated into other projects: Ontotext applies the RelFinder to enable an exploration of relationships in the biomedical domain. All tools on this website are research prototypes that might contain errors.
Semantic Web
The promise of web standards W3C standards define an open web platform for application development. The web has the unprecedented potential to enable developers to build rich interactive experiences, that can be available on any device. The platform continues to expand, but web users have long ago rallied around HTML as the cornerstone of the web. Read more about W3C Standards Why W3C web standards? W3C publishes recommendations, that are considered web standards. W3C develops technical specifications according to the W3C Process, which is designed to maximize consensus, ensure quality, earn endorsement and adoption by W3C Members and the broader community. W3C web standards are optimized for interoperability, security, privacy, web accessibility, and internationalization. W3C's proven web standards process is based on fairness, openness, royalty-free, we make the web work, for everyone. Value of creating standards at W3C Wide array of applications
The US sub-prime crisis
The US sub-prime mortgage crisis has led to plunging property prices, a slowdown in the US economy, and billions in losses by banks. It stems from a fundamental change in the way mortgages are funded. Traditionally, banks have financed their mortgage lending through the deposits they receive from their customers. This has limited the amount of mortgage lending they could do. In recent years, banks have moved to a new model where they sell on the mortgages to the bond markets. This has made it much easier to fund additional borrowing, But it has also led to abuses as banks no longer have the incentive to check carefully the mortgages they issue. In the past five years, the private sector has dramatically expanded its role in the mortgage bond market, which had previously been dominated by government-sponsored agencies like Freddie Mac. They also included "jumbo" mortgages for properties over Freddie Mac's $417,000 (£202,000) mortgage limit. But no one is sure how long the slowdown will last.
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Heart Attack: Detecting Heartbleed Exploits in Real-Time
The OpenSSL Heartbleed vulnerability is proving to be one of the bigger vulnerabilities the security community has seen. As vendors and administrators scramble to patch their systems and users struggle to identify what sites are safe to use, hackers are taking full advantage of the vulnerability. Tripwire’s VERT team has quickly deployed the most robust coverage for detecting the vulnerability through IP360, PureCloud and SecureScan. What if we also want to monitor and be able to identify when the exploit is being used against us? Using a combination of an IDS and Tripwire Log Center allows us to do just that. Heartbleed & Honeypot There are several versions of the Heartbleed exploit actively in the wild, some are simply being used to test if systems are vulnerable, as well as more robust versions available in Metasploit and other frameworks. Successful Heartbleed Exploit Attempt I can now easily act on these alerts and correlate them to other events in my environment. Related Articles:
Large-scale RDF Graph Visualization Tools
AI3 Assembles 26 Candidate Tools The pending UMBEL subject concept “backbone” ontology will involve literally thousands of concepts. In order to manage and view such a large structure, a concerted effort to find suitable graph visualization software was mounted. This post presents the candidate listing, as well as some useful starting resources and background information. A subsequent post will present the surprise winner of our evaluation. Starting Resources See Various Example Visualizations For grins, you may also like to see various example visualizations, most with a large-graph bent: Software Options Here is the listing of 26 candidate graph visualization programs assembled to date: Cytoscape – this tool, based on GINY and Piccolo (see below), is under active use by the bioinformatics community and highly recommended by Bio2RDF.org GINY implements a very innovative system for sub-graphing and allows for stunning visuals. headline: alternativeHeadline:
