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The blue social bookmark and publication sharing system.
- "Indexing & Organizing 11,106,374 [growing figure] Biological Names"
- Working list of all known plant species in collaboration between the Royal Botanic Gardens, Kew and Missouri Botanical Garden. Provides the accepted Latin ...Working list of all known plant species in collaboration between the Royal Botanic Gardens, Kew and Missouri Botanical Garden. Provides the accepted Latin name, synonyms and rejected forms. (Aims to be comprehensive for vascular plant).
- database of the names and associated basic bibliographical details of seed plants
- Open Journal of Soil Science (OJSS) is an international journal dedicated to the latest advancement of soil science. The goal of this journal is to provide...Open Journal of Soil Science (OJSS) is an international journal dedicated to the latest advancement of soil science. The goal of this journal is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of soil science.
- A Taxonomy of meta-programming systems. In a meta-programming system meta-programs manipulate object-programs. Meta-programs may construct object-programs,...A Taxonomy of meta-programming systems. In a meta-programming system meta-programs manipulate object-programs. Meta-programs may construct object-programs, combine object-program fragments into larger object-programs, observe the structure and other properties of object-programs, and execute object-programs to obtain their values. There are two important kind of meta-programming scenarios: program generators, and program analyses. Each has a number of distinguishing characteristics 1. Generator 1. Representation: Strings vs. Algebraic datatype vs. Quasi-quote 2. Automatic vs. Manual annotation 3. Static vs. Runtime Generator 4. Homo vs. Heterogeneous 5. Typed vs. un-Typed 1. Statically vs. Dynamically Typed 6. 2-stage vs. N-stage 2. Analysis 1. Homo vs. Heterogeneous 2. HOAS vs. First Order Syntax 3. Typed vs. un-Typed
- A Revised Taxonomy of Social Networking Data Lately I've been reading about user security and privacy -- control, really -- on social networking sites. ...A Revised Taxonomy of Social Networking Data Lately I've been reading about user security and privacy -- control, really -- on social networking sites. The issues are hard and the solutions harder, but I'm seeing a lot of confusion in even forming the questions. Social networking sites deal with several different types of user data, and it's essential to separate them. Below is my taxonomy of social networking data, which I first presented at the Internet Governance Forum meeting last November, and again -- revised -- at an OECD workshop on the role of Internet intermediaries in June. * Service data is the data you give to a social networking site in order to use it. Such data might include your legal name, your age, and your credit-card number. * Disclosed data is what you post on your own pages: blog entries, photographs, messages, comments, and so on. * Entrusted data is what you post on other people's pages. It's basically the same stuff as disclosed data, but the difference is that you don't have control over the data once you post it -- another user does. * Incidental data is what other people post about you: a paragraph about you that someone else writes, a picture of you that someone else takes and posts. Again, it's basically the same stuff as disclosed data, but the difference is that you don't have control over it, and you didn't create it in the first place. * Behavioral data is data the site collects about your habits by recording what you do and who you do it with. It might include games you play, topics you write about, news articles you access (and what that says about your political leanings), and so on. * Derived data is data about you that is derived from all the other data. For example, if 80 percent of your friends self-identify as gay, you're likely gay yourself. There are other ways to look at user data. Some of it you give to the social networking site in confidence, expecting the site to safeguard the data. Some of it you publish openly and others use it to find you. And some of it you share only within an enumerated circle of other users. At the receiving end, social networking sites can monetize all of it: generally by selling targeted advertising. Different social networking sites give users different rights for each data type. Some are always private, some can be made private, and some are always public. Some can be edited or deleted -- I know one site that allows entrusted data to be edited or deleted within a 24-hour period -- and some cannot. Some can be viewed and some cannot. It's also clear that users should have different rights with respect to each data type. We should be allowed to export, change, and delete disclosed data, even if the social networking sites don't want us to. It's less clear what rights we have for entrusted data -- and far less clear for incidental data. If you post pictures from a party with me in them, can I demand you remove those pictures -- or at least blur out my face? (Go look up the conviction of three Google executives in Italian court over a YouTube video.) And what about behavioral data? It's frequently a critical part of a social networking site's business model. We often don't mind if a site uses it to target advertisements, but are less sanguine when it sells data to third parties. As we continue our conversations about what sorts of fundamental rights people have with respect to their data, and more countries contemplate regulation on social networking sites and user data, it will be important to keep this taxonomy in mind. The sorts of things that would be suitable for one type of data might be completely unworkable and inappropriate for another.
- Indexing the worlds known species.
- University of California Press, (2001)
- East Bay Municipal Utility District, (2004)
- LuLu Press, (2010)
- (2012)
- Bioinformatics 16(4):406-407 (2000)
- Springer-Verlag London Limited, New York, (2007)
- Springer, New York, (2009)
- (2006)http://tagont.googlecode.com/files/TagOntPaper.pdf .
- Journal of Information Science 32(2):198--208 (2006)
- (2005)
- (2011)
- Artificial Intelligence Review 19(4):285-330 (2003)
- Educational Psychologist 31(2):105--113 (1996)
- HYPERTEXT '06: Proceedings of the seventeenth conference on Hypertext and hypermedia, page 31--40. New York, NY, USA, ACM, (2006)
- Longmans Green, New York, (1956)
- Inf. Process. Manage. (May 2008)
- SIGIR Forum (September 2002)
- Proceedings of the Fourth Workshop on Information Credibility on the Web, page 3--10. ACM, (April 2010)
- (1987)
- Hiersemann, (2010)


