Ramesh Jain jain@ics.uci.edu Events in Data Science Ramesh Jain jain@ics.uci.edu

Data/Information/Knowledge Data, Data, everywhere. Not a bit of information to be found. Data is important, but people care for Information and Knowledge

We Live in Dynamic World.

Modeling the World Objects Events

Remember Newton Statics Mechanics Dynamics

Big Data Multimedia Realtime Credibility ICNC 2015 Anaheim, CA.

Events take place in the real world. Events result in Data and Documents

Tsunami 2004 Experiential Data Reports on the event Visualization using data

Events are ‘Connectors’ Events create ‘Context’ People Things Places Time Experiences Events Structural Temporal Causal Spatial DATA MODEL: To capture events we need a common event model in order to avoid obfuscating event exploration and event-driven access to media.We used E-Model that introduces 6 facets for events (the circle diagram in the next slide) as the initial basis for our data model. We are currently building the formalizations of our data model which is based on this circle diagram. We are formally defining each facet in our data model. Each facet may involve structures and/or induced sub-graphs in addition to the RDF structure. However this is our future work and we will not talk about that here. Experiential Informational 9

Massive collection of events. each month. Facebook and Twitter Reporting events as micro-blogs Massive collection of events. each month.

Events: A time-indexed database!!!

Events usually cause domino effect. Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?

From Micro-blogs to Situations From Tweets to Demonstrations

Theory of Control and Communication in Published first in 1942 Theory of Control and Communication in Animals Machines Societies What is Cyber Space? Who invented it?

Cybernetics: Real Time Feedback Control Physical World And Information Systems Environment and Resources Information Action Signals Matching Personal Situation and Needs Information

Cybernetics: Personal

Data Variety: From Data Streams to Abstracted Event Streams sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, human motions, etc… Not only heterogeneous, and unstructured, but time is a very important dimension. They all generate Events What about frameworks that consume events for knowledge discovery? In particular, the accommodation of time into mining techniques provides a window into the temporal arrangement of events and, thus, introduce the ability to suggest cause and effect that are overlooked when the temporal component is ignored or treated as a simple numerical attribute. Moreover, temporal data mining has the ability to mine the behavioral aspects of a system as opposed to mining rules that describe their states at a point in time. Hence, temporal data mining helps understanding why rather than merely understanding what. Data Management

From data streams to situations Conditions Event Streams Observation Streams Aggregation and Classification Understanding Verification Low-level Analysis

Computational Model of Events. Event Stream

Daily Life Activities: How we enter them? Chronicle of Daily Life Activities

Daily Life Activities: How we use time. Daily Life Activity ATUS: American Time Use Survey

We collect diverse signals.

Personal Event Streams in a Personicle Food Score Food Activity Activity Score Emotion Emotion Score Medical Medical Score Environment Environment Score Daily Activity

Future Health: Right Moment, Right Place, Right Decision, Right way. Personalized Predictive Precise Persuasive Preventive Right Moment, Right Place, Right Decision, Right way.

Your food and activity scores for the last 3 days are on low side. Coming Soon Near You Your food and activity scores for the last 3 days are on low side. Health Butler

Current Status Expect to see first version of Health Butler in 2nd quarter, 2017.