The Rise of Smart Oceans

Transcription

1 BIG DATA CONGRESS 2017 November 6-8, 2017 Halifax, Canada The Rise of Smart Oceans - From Marine Data to Wisdom - Renata Dividino, Ph.D. Institute for Big Data Analytics Dalhousie University 1

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3 How Big Data can reshape the Marine data industry? Transform data into actionable knowledge 3

4 1. Data 2. Information 3. Knowledge 4. Wisdom Ackoff, R. L., "From Data to Wisdom", Journal of 4 Applies Systems Analysis, Volume 16, 1989 p 3-9.

5 1. Data 5

6 Marine Data 6 Source: SISMER

7 Automatic Identification System Source: exactearth.com Originally mandated as an aid to collision avoidance in maritime shipping 7

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13 Marine Open Data it is about licenses to allow re-use 13

14 Raw Data 14

15 1. Data 2. Information 15

16 2. Information = Data + Context 16

17 Information organized or structured data, which has been processed in such a way that the information now has relevance for a specific purpose or context, Rowley, Jennifer (2007). "The wisdom hierarchy: representations of the DIKW hierarchy". Journal of Information and Communication Science. 33 (2):

18 This illustration draws on Satellite AIS data which are provided by exactearth Ltd. 2017, and processed courtesy of MEOPAR and 18the Institute for Big Data Analytics

19 Source: How To Use Structured Data the Right Way FeedOtter 19

20 Web of Things With the rise of the Web of Thing, actuators and the data they produce also become firstclass citizens of the Web. 20

21 Source: The Open Geospatial Consortium (OGC) 21

22 Web of Things Sensor Web Enablement (SWE) initiative of the Open Geospatial Consortium (OGC) 22

23 WoT & Linked Data Within the given standards, complementing building blocks are necessary to enable easy integration across WoT platforms and application domains. 23

24 Linked Data it is about technology for interoperability 24 Linked Data Tim Berners-Lee

25 5 Data Make data available on the Web (whatever format) under an open license Make it available as structured data (e.g., Excel instead of image scan of a table) Make it available in a non-proprietary open format (e.g., CSV instead of Excel) Use URIs to denote things, so that people can point at them Link your data to other data to provide context 25 Tim Berners-Lee

26 1. Data 2. Information 3. Knowledge 26

27 3. Knowledge = information + hidden connections 27

28 Hidden Connections Idea: thinking is deductive reasoning & learning from experiences is inductive reasoning 28

29 Hidden Connections A US law, the 1920 Merchant Marine Act, determines that all the transportation of goods between US ports has to be done by US vessels exclusively. 29

30 Hidden Connections deductive reasoning A: Port of Los Angeles is located in the San Pedro Bay B: San Pedro Bay is in the US Port of Los Angeles is located in the US C: Vessel is coming from the Port of Los Angeles D: Vessel is going to the Port of Seattle F: Vessel is from US 30 E: Port of Seattle is is located in the US

31 Hidden Connections inductive reasoning 31

32 Hidden Connections inductive reasoning Mission-relevant Information Management for Integrated Response 32

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34 34 Source: independent.co.uk

35 Hidden Connection - Fish Activities- Identify fishing activities in the data, i.e. identify when vessel is fishing and when is not. 35

36 Hidden Connection - Fish Activities- Longline Fishing Trawler Fishing 36

37 Using Expert Knowledge Fishing Non-Fishing de Souza, Erico N., et al. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning. PloS one 11.7 (2016): e

38 Using Expert Knowledge Fishing Non-Fishing de Souza, Erico N., et al. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning. PloS one 11.7 (2016): e

39 Fishing Activities Predict Model Labeled Data Machine Learning Algorithms Predictive Model Classified Output 39 Observations

40 Classification Results Fishing Detection Non-fishing Detection de Souza, Erico N., et al. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning. PloS one 11.7 (2016): e

41 Classification Results Fishing expert and algorithm Fishing expert label Fishing algorithm label Non-fishing - expert and algorithm de Souza, Erico N., et al. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning. PloS one 11.7 (2016): e

42 42 Credits to Johna Latouf Institute for Big Data Analytics

43 MPAs & Fish Activities 43

44 Fishing ships move like predators Lavielle M. Source: Environmental Defense Fund edf.org Lavielle M. Using penalized contrasts for the change-point problem. Signal Processing. 2005;85(8):

45 1. Data 2. Information 3. Knowledge 4. Wisdom 45

46 4. Wisdom = insights 46

47 Wisdom Knowledge Information Data

48 Smart Oceans 48 National Oceanic and Atmospheric Administration noaa.gov

49 Real-time Marine Data Online Access 49

50 Ballast water can contribute to oceanic environmental problems if the water is not disposed properly American National Standard Institute ansidotorg.blogspot.com 50

51 Aquatic Food Security 51

52 Marine Environmental Research Infrastructure for Data Integration and Application Network 52 Source: newsweek.com

53 Marine Big Data Challenges Data Discovery & Accessibility Smart Sensor Information Interoperability Linked Data Knowledge AI state-of-the art technologies Interplay between SW and ML Wisdom 53

54 Thank you 54