Emerging Trends in Crisis Informatics

transcript

Emergent Trends and Tools in Crisis Informatics

Adam PapendieckJan 30, 2014

Objectives

1. Gain an understanding of key trends in ICT innovation which are influencing/disrupting crisis informatics.

2. Be able to trace these trends through discussions later this semester, and understand their influence and potential.

3. Introduce visualization lab

Conventional, Centralized Info Management

Source: Harvard Humanitarian Initiative. Disaster Relief 2.0

Crisis Information Ecosystem:Complex Adaptive System

• Some information needs are clear and structured.

• But the actual information ecosystems in emergencies are complex and changing rapidly.

• Individual technologies, information systems and their relationship to others are ephemeral, even in the short-to-medium term. They evolve.

Crisis Information Ecosystem:Complex Adaptive System

• Rapid, adaptive collaboration can be advantageous• complex adaptive systems are built upon feedback

loops• Shift from institutions to collaborations• Closed, rigid institutions Open, fluid cooperation

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Five most common categories of reports to the Ushahidi Haiti Crisis Map over the first 90 days

Food Shortage Shelter Needed Water Shortage Vital Lines Emergency

Reports

Information Feedback Loop

Data Capture

Curation

Analysis

Dissemination

ksAgency effort, resources

Agency effort, resources

Value StreamConventional Emergent

Humanitarian Information Systems

Emergent ICT(Trends)

1. Improved Global Connectivity2. The Cloud3. Semantic Web and Open Standard4. Mobile5. Networks6. Data Mining

http://www.submarinecablemap.com/

TREND: Improved Global Connectivity

Global Submarine Cables (2012)

NSFNet (1986)

Mobile Phone Subscribers per 100 Individuals

TREND: The Cloud

• Centralization of computing power and standardization of data– Semantic Web, XML, APIs– Subscription-based “Software as a Service” (SaaS)

Source: http://resource.onlinetech.com/cloud-computing-prompts-2012-data-center-expansion-plans/

Software as a Service (SaaS)

TREND: Semantic web

• Old characteristics of the web: HTML, text, individual static web pages

• New characteristics: XML, APIs (Application Programming Interfaces), webservices, open standards, dynamic and interactive web pages

TREND: Semantic web

• Augments information on web pages with machine-readable metadata and relationship information.

• Enables the “mashup”• Example tools: Yahoo pipes, Google API,

Calais, Yahoo Terms, Google Maps

How Systems Communicate: XML

Other standard formats: JSON, RDF, CSV

How Systems Communicate: APIs(Application Programming Interfaces)

Yahoo Pipes

Mashups and Dashboards

TREND: Mobile Computing

• Proliferation of thin clients (our various “screens”) to access cloud– API’s, XML etc.

• Sensor devices connected to the cloud– human sensors– internet of things– enables more continuous assessment across time

and geography than ever before

Informed Human Sensors

http://opendatakit.org/

http://www.amazonteam.org/index.php/193/Participatory_Ethnographic_Mapping_Mapping_Indigenous_Lands

Report 295: Buras, LA. 05/13/2010 “I have a sore throat and headache!!! And I can not go run my crab traps because my fishing grounds are closed, now for the 14th day..”

Report 1646: Plaquemines, LA. 08/02/2010 “While walking on a beach in an area heading toward South pass, we got stuck in 2 "baby" sinkholes of oil buried beneath the sand. We started poking the holeswith sticks and oil came oozing out. The first sinkholewas 4 feet wide and 6" deep. The second sinkhole was 2x2 diameter. The tide must be bringing in sand covering up the oil.”

Report 130: California Point, LA. 05/06/2010 Crabman out of work. “I have crabbed in the California Point area inside Breton Sound for well over 20 years. I also fish shad in this area and sell it for crawfish bait. I also shrimp seasonally. I am 52 years old and I am very concerned about the future of commercial fishing, my family responsibilities, my livelihood and way of life.”

TREND 4: Social Networking

Proliferation of networking and collaboration tools

Clay Shirky: Social Media makes Collaboration Efficient

• TV is uni-directional: we just consume.

• Social media is bi-directional: Participants produce and consume information

• This transition yields a “cognitive surplus”– All the time we used to spend consuming TV can

now be used for producing something new, together.

Clay Shirky: How Cognitive Surplus Will Change the World http://goo.gl/ZIgA

So, what do we do with this surplus?

The “Long Tail” of Contributors

Institutions vs. Collaboration

Crowdsourcing and Micro-tasking

http://vimeo.com/9182869

Collaborative, Community-driven and Open Source Development Models

• Depend upon:– feedback loops– some level of openness and sharing

Crowdmap: SaaS for Crowdsourcing

TREND: Data Mining

• Open data• Big Data– Our “digital exhaust”

• Emphasis on Trend Visualization– Dynamic– Info-graphics

Open Data

• Standardized formats, APIs• Share, Share Alike– CRED EM-DAT– World Bank http://data.worldbank.org– USG– Ushahidi

Big Data• web logs• sensor networks (e.g. mobile phones, RFIDs)• social networks (who’s connected to who)• social data (what’s being shared and generated)• teaching and learning management systems• financial transaction data and large-scale e-commerce• Internet text and documents• Internet search indexing• call detail records• military surveillance; • medical records; • photography archives; • video archives;• astronomy, atmospheric science, genomics, biogeochemical, biological, and

other complex and/or interdisciplinary scientific research;

Importance of Innovation in Data Visualization/Analysis

• Time, energy and resources are moving from data collection & curation to data interpretation & use.

What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.

(Herb Simon, quoted in Scientific American, 2005)

Bengtsson, L., Lu, X., Thorson, A., Garfield, R., & Schreeb, J. von. (2011). Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti. PLOS Med, 8(8), e1001083. http://doi.org/10.1371/journal.pmed.1001083

FluTrends Video & Website: http://goo.gl/ZcgVSource Paper: http://goo.gl/nMFvDz

Google Flu Trends

Global Pulse Research Case Studies

Cases: 1. Commodities E-Index: http://goo.gl/tzCb0z2. Twitter & Crisis Stress: http://goo.gl/LVPtf3. Unemployment & Social Media: http://goo.gl/RuRTb

Questions4. How were things done before?5. How is big data visualization being used to do things

differently or add something new?6. Strengths, weaknesses, opportunities?

Bread Index based on online pricing information

Source: UN Global Pulse

Twitter and Crisis-related Stress

Social Media and Unemployment

Source: UN Global Pulse

Open and Big Data will Require Protection Measures

Source: Big Data, Communities and Ethical Resilience: A Framework for Action (PopTech Fellows) http://goo.gl/LAKrjF

Interactive Data Visualization Lab

Background for Lab Exercises

Two Parts

1. Individual Assignment - Today– Get to know software and data site– Get started with independent work – Due Wed

2. Group Synthesis – Next week– Expand on visualization types, data, tools– Integrate with RLP

Visualization Lab Exercise

• On Blackboard:– All instructions, links and submission details• http://goo.gl/eZlh8z

– Visualization Lab Discussion Forum is for asking questions and posting data and other resources. • http://goo.gl/1VFHX6

Next time: Visualization Tools

• End-user cloud databases and services– Google Maps, Google Spreadsheets, – Zoho Creator

• Visualization APIs and Kits for the web– D3, MIT Simile Project

• Web-based end-user geodata and mapping platforms– Geocommons

• Web-based dynamic visualization platforms:– IBM Many Eyes– Infogr.am

• Desktop platforms for creating dynamic visualization– Tableau (Windows only, OSX soon)

• Big Data open to the public– http://

www.quora.com/Data/Where-can-I-find-large-datasets-open-to-the-public

Caveats

• Awareness of privacy / security is importany• Protect your data! – Keep an eye on your escape hatch– Use open, established standards

• Limits: query rate and database size• Attribution/Fair Use• Engage the tools but be critical– Pay attention to utility and face validity

Thanks!

• Adam Papendieck• apapendieck@gmail.com• 200 Broadway, Suite 203

Emerging Trends in Crisis Informatics

Technology