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Exploring Data Nature with Dataology

Understand the concept of nature in computer systems and how data is stored and utilized. Learn about data structures, rules, and applications in Dataology for exploring real-world phenomena.

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Exploring Data Nature with Dataology

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  1. Introduction to Dataology Yangyong Zhu05/07/2009

  2. Outline 6 1 2 5 4 3 What is Data Nature What is Dataology The Framework of Dataology Challenges Applications of Dataology What are the Differences

  3. What is Data Nature

  4. Nature (Real Nature) Nature, in the broadest sense, is equivalent to the natural world, physical world or material world. "Nature" refers to the phenomena of the physical world, and also to life in general.

  5. Data Nature The phenomena of nature are stored in computer systems • GIS • Digital Earth Plan • Human Genome Plan • ……………

  6. Data Nature Human behaviors are stored in computer systems • Communication • (Telephone/Mobile phone/ Email/MSN…) • Behavior patterns • (Credit card usage) • Activities • (Government/Enterprises) • …………………..

  7. Data Tribe Data Country Data Zone Data Nature The usage of computers is the procedure ofproducing data. • Web data • Biological data • Public data • Private data • Data may (or may not) be managed by DBMS Data Nature Data Nature

  8. Data Nature Data Nature Data Nature

  9. Real natureData nature Data Nature The Second Life

  10. Data Nature The Second Life NASA

  11. Data Nature The Second Life IBM

  12. 3 2 4 1 Out of Control Impossible for human to control • Diversity • In- INTERNET/ • Out-of-INTERNET • public/private • audio/video • Complexity • Involve various languages • All trades and professions • Spatial, oceanic, DNA data, etc Unknown Human do not understand Data Nature Data in computer systems exhibit all the characteristics of real nature.

  13. What is Dataology

  14. Dataology Dataology is the theories, methods and technologies for studying data nature. • To study the structures of a dataset in data nature • To acquire usage data from data nature • To prove the rules of data nature by theoretical methods • To discover the rules of data nature by experimental modes • To develop and utilize the data resource in data nature

  15. Dataology • Existing researches of Dataology : • Data Collection and Data Integration • Data Mining • Data Reasoning (AI) • Data Security • Data Visualization • Developing continuously…..

  16. Dataology • Prospective Researches of Dataology: • Data Experiment • Data Camouflage / Data perception • Data Taxonomy • Data Aware • Dataology for Specific Domains

  17. Dataology • Data Experiment: • Discover the features and rules from a dataset. • Focus on the random of methods and the unpredictability of results. • Different from data mining

  18. Dataology • Data Camouflage / Data perception: • Tocamouflage the private data which are exposed in the public • To percept the camouflageddata. • Different from data security (privacy protection, privacy mining)

  19. Dataology • Data Taxonomy: • Classify data to form the pedigree of data and the history of development. • Similar to the classification for the species, history and culture • Data types, utilities and relationships

  20. Dataology • Data Aware: • To make data visualable, sniffable, audible, tangible. • People want to feel data nature as feeling nature. • To develop various technologies of data aware.

  21. Dataology • Specific Domains: • Universal Dataology • Life Dataology • Behavior Dataology • and so on…

  22. What are the Differences

  23. Why not computer science Computer science consists of hardware and software Machine language Translate Computer Software To use Translate Computer Hardware Nature Language

  24. pull Computer Software Why not computer science The software research pulls the software to nature language Assemble language High level language 4GL HORN clauses First order logic High order logic ？？？？？？？ It means to model nature language, and to model the nature Computer Hardware Nature language Machine language

  25. pull Computer Software Why not computer science The hardware research improves the capability of computing and storage Assemble language High level language 4GL HORN clauses First order logic High order logic ？？？？？？？ Super-computer Grid Computing Cloud Computing Computer Hardware GB TB PB … Nature language Machine language

  26. Knowledge Information Data Why not information science Data Anything stored in Computer Systems • Data is one of symbol representation of information • Information is the interpretation of data

  27. The Differences Dataology Computer Science To explore, develop and utilize, etc Applications Modeling Acquiring Data Nature Real Nature Data Set • Study data in computer systems • Theoretically, independent from computer Computer & Network

  28. Human Being Nature Science Social Science Real nature Universal & Life Human Behavior Society , Laws, Economic…. Dataology Data nature Anything stored in computer systems The relationship

  29. The Framework of Dataology

  30. Life Dataology Universal Dataology Behavior Dataology 。。。。。。。。 cyclopaedia The Framework of Dataology Applications of Dataology Data Acquire Data Aware Data Analysis Foundations of Dataology Data Explore Data Visualization Data Experiment Data Camouflage Data Sniffable Data Mining Data Perception Data Audiblization Data Integration Data Taxonomy Data Tangiblization Data Management

  31. Applications of Dataology

  32. Behavior Informatics Bio informatics Social Networks 。。。。。。。。 Life Dataology Universal Dataology Behavior Dataology 。。。。。。。。 They all work on Data Nature Applications of Dataology

  33. Challenges

  34. Challenges What are the foundational theories of Dataology? Does the unique theory of Data Nature exist? How to Develop and UtilizeData Resource? How to know what we get from Data Nature are true? How human beings survive in Data Nature?

  35. Thanks yyzhu@fudan.edu.cn www.dataology.fudan.edu.cn

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