FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2765858082> ?p ?o ?g. }

• W2765858082 abstract "Caution: Danger Ahead (with Big Data) Matt Bishop Dept. of Computer Science University of California at Davis 1 Shields Ave. Davis, CA 95616-8562 USA email: bishop@ucdavis.edu Abstract. “Big data” is revolutionizing our view of science, and has the potential to do the same for the social sciences and humanities. With the benefits come very serious potential problems, ranging from invasion of personal privacy to enabling spectacular failures of analytics. This discusses some of them. Introduction. “Big data” encompasses the gathering, management, analysis, and synthesis of very large amounts of data. Having tremendous amounts of data available enables much more detailed, and much broader, analyses than ever before; we can record large-scale astronomical data for later analysis, or probe the basis for life to understand heredity, diseases, and evolution. For example, the Large Synoptic Survey Telescope project (LSST) [1] will use an 8.4-meter telescope in Chile to survey the visible sky every week with a three billion pixel camera, in order to enable scientists to analyze the changes in the sky over a period of years. This project will produce 30 terabytes of data per night. The data will be sent from Chile to Illinois, where it will be shared with collaborators throughout the world. Storing and providing the tools to search this data for astrophysical phenomena of interest will require the development of new methods, tools, and powerful storage and networking facilities. Other types of big data involve personal or sensitive information. Retailers use “loyalty cards” to offer discounts to consumers and to collect information on what they purchase. Financial institutions inform credit reporting agencies about the state of consumers’ finances, and in turn receive reports aggregating information from other such institutions (and, indeed, from creditors in general). In science, the study of the human genome has led to the collection of massive amounts of data about the biological constructs that encode personal characteristics of human beings. Medical data is aggregated and correlated to provide insight into the origins and causes of epidemics, and discern ways to stop or slow their spread. The collection of any sensitive information raises serious questions about the effects of the propagation of data upon privacy—and big data exacerbates these problems. This is usually framed as the need to protect personal privacy. An equally interesting, but rarely raised, form is the need to ensure that the inferences acted upon are correct. Page 1" @default.
• W2765858082 created "2017-11-10" @default.
• W2765858082 creator A5053448222 @default.
• W2765858082 date "2013-10-01" @default.
• W2765858082 modified "2023-09-27" @default.
• W2765858082 title "Caution: Danger Ahead (with Big Data)" @default.
• W2765858082 hasPublicationYear "2013" @default.
• W2765858082 type Work @default.
• W2765858082 sameAs 2765858082 @default.
• W2765858082 citedByCount "0" @default.
• W2765858082 crossrefType "journal-article" @default.
• W2765858082 hasAuthorship W2765858082A5053448222 @default.
• W2765858082 hasConcept C111919701 @default.
• W2765858082 hasConcept C199683683 @default.
• W2765858082 hasConcept C2522767166 @default.
• W2765858082 hasConcept C41008148 @default.
• W2765858082 hasConcept C75684735 @default.
• W2765858082 hasConceptScore W2765858082C111919701 @default.
• W2765858082 hasConceptScore W2765858082C199683683 @default.
• W2765858082 hasConceptScore W2765858082C2522767166 @default.
• W2765858082 hasConceptScore W2765858082C41008148 @default.
• W2765858082 hasConceptScore W2765858082C75684735 @default.
• W2765858082 hasIssue "10" @default.
• W2765858082 hasLocation W27658580821 @default.
• W2765858082 hasOpenAccess W2765858082 @default.
• W2765858082 hasPrimaryLocation W27658580821 @default.
• W2765858082 hasRelatedWork W2046654294 @default.
• W2765858082 hasRelatedWork W2128030282 @default.
• W2765858082 hasRelatedWork W2150047590 @default.
• W2765858082 hasRelatedWork W2165093166 @default.
• W2765858082 hasRelatedWork W2210510458 @default.
• W2765858082 hasRelatedWork W2210600602 @default.
• W2765858082 hasRelatedWork W2292725934 @default.
• W2765858082 hasRelatedWork W2293852254 @default.
• W2765858082 hasRelatedWork W2317128301 @default.
• W2765858082 hasRelatedWork W2341776788 @default.
• W2765858082 hasRelatedWork W2557539694 @default.
• W2765858082 hasRelatedWork W2569163957 @default.
• W2765858082 hasRelatedWork W2734695534 @default.
• W2765858082 hasRelatedWork W2743677945 @default.
• W2765858082 hasRelatedWork W2785155339 @default.
• W2765858082 hasRelatedWork W2964488450 @default.
• W2765858082 hasRelatedWork W3116716467 @default.
• W2765858082 hasRelatedWork W3190463106 @default.
• W2765858082 hasRelatedWork W818559660 @default.
• W2765858082 hasRelatedWork W2548567768 @default.
• W2765858082 hasVolume "11" @default.
• W2765858082 isParatext "false" @default.
• W2765858082 isRetracted "false" @default.
• W2765858082 magId "2765858082" @default.
• W2765858082 workType "article" @default.