Big Data: Challenges and Opportunities for Disaster Recovery


NII Shonan Meeting Seminar 082


Sanjay Madria, Missouri University of Science and Technology, USA

Takahiro Hara, University of Osaka, Japan

Cyrus Shahabi, University of Southern California, USA

Calton Pu, Georgia Tech, USA




Description of the meeting

The main purpose of this NII Shonan meeting is to bring together researchers from the multidisciplinary fields of data management and analytics; , mobiles,sensors and pervasive computing; geography and urban-panning; and disaster response and recovery with public agencies and commercial entities towards using big data for better decisionmaking and problem solving in the event of a disaster. To do so, we need to close the gaps between those who collect the data (data providers), those who could benefit from using the data (domain experts), and those who are capable of developing the methods for storing/managing/processing the data (technology enablers).

So-called “Big Data” began when the Enterprise era generated the first wave of data through various software applications such as inventory management or human resource applications. Soon the field of computer science realized that there were commonalities in how the data was being stored and accessed, which led to the development of databases. As the size of data grew due to broad adoption by many enterprises (Volume), new research fields emerged to deal with efficient access (parallel databases), integration (data warehouses) and analysis (data mining) of large datasets. However, the second wave of data, Human-generated data (the Web), exposed the fundamental challenges resulting from data heterogeneity (Variety); this data is semi-structured (text documents) or non-structured (pictures and videos) and is growing at a much higher rate. The rapid growth of web applications left academics with little opportunity to identify commonalities of data usage, leading to many independent tools that focus on a narrow aspect of data preparation for a given application type and requiring human in-the-loop data extraction and preparation. This worked to some extent, as human data creation processes led to a natural gap between data generation and data consumption. Machinegenerated data represents the newest wave as they are generated continuously at a high rate (Velocity) from various sensors in the physical world, starting with sensor instrumentation, e.g., pavement traffic loop detectors, SCADA industrial automation sensors, CCTV cameras, satellite- or plane-based LIDAR sensors, and continuing with inexpensive sensors in our mobile phones, refrigerators, watches, and soon, everything we wear. These three waves of data gave rise to numerous approaches benefiting from data use in critical decision-making (Big Data).

The time is ripe to embark on a fundamental approach to Big Data challenges by assembling stakeholders to review case studies, design and develop several prototypical end-to-end systems, identify the commonalities, and develop lessons learned stories. This is exactly the goal of our proposed meeting with a focus application of disaster response and recovery. This is because efficient and thorough data collection and its timely analysis are critical to any disaster response and recovery system in order to save people’s lives during disasters. However, access to comprehensive data in disaster areas and their quick analysis to transform the data to actionable knowledge are major data science challenges. Moreover, the effective presentation of the collected knowledge to human decision-makers is an open problem. Therefore, the proposed meeting is to study and share experiences in Big Data research, Education and Training as well as discuss challenges and disseminate solutions, blueprints, and prototypes focusing on the disaster recovery application domain.

Towards this end, experts from various disciplines, including application domain experts with knowledge about disaster response and recovery, need to interact and collaborate effectively. The purpose of this workshop is to bring together these experts with the common goal of improving disaster recovery through Big Data, from different countries to Japan to initiate information exchange and collaboration. Moreover, the shortage of a knowledgeable workforce presents a further challenges to the Big Data management and needs to be addressed through education and training. Therefore, this workshop can provide a forum for education and training of researchers from multiple disciplines in the complementary areas.


Interesting Topics:

The proposed meeting will address the following topics (the list is by no means exhaustive):

  • Data Acquisition (e.g., remote sensing, aerial vehicles, infrastructure sensors and CCTV, mobile devices, wearable sensors, and online sources)
  • Information Extraction and Representation
  • Data Integration
  • Data Analysis
  • Information Presentation and Visualization
  • Data Privacy, Trust, Quality, Integrity and Security
  • Scalable Data Systems
  • Data lifecycle management
  • Citizen Science and Crowdsourcing
  • Disaster Response and Recovery Applications


Final schedule:

Arrival Day (Sunday, 27th March)

15:00-18:30 Check-In in Shonan Center
19:00-20:30 Welcome Dinner
21:00- Free Time

Day 1 (Monday, 28th March

In one of the early seminar sessions, we will have an introduction round with all participants / organizers introducing themselves.
Please prepare a brief presentation of roughly 10 minutes for that purpose, outlining yourself and your research interests. Please explain how your research currently relate to big data and disaster recovery. These introductions should provide some interesting problems or provide fruitful insights which can be used to start further discussions.

07:30-09:00 Breakfast
09:00-09:20 Shonan Introduction by Staff
Opening briefing from organizers
09:10-12:00 Session 1: Tools and Frameworks for Big Data Analysis
Chair: Sanjay Madria (Missouri University of Science and Technology, USA)
– Session Introduction/overview
– Position talks from participants
* Kuo-yi Lin (Asia University, Taiwan)
“A Deep Learning-Based Forecasting Tool for Big Data”
* Matthias Renz (George Mason University, USA)
“Reliable Spatial and Spatio-Temporal Pattern Analysis to Support Decision making in disaster management applications”
* Hideki Hayashi (Hitachi, Ltd., Japan)
“Spatio-Temporal Data Retrieval for Disaster Estimation”
* Yasushi Sakurai (Kumamoto University, Japan)
“Mining and Forecasting of Big Time-series Data”
* Sanjay Madria (Missouri University of Science and Technology, USA)
“M-Grid : A Distributed Framework for Multidimensional Indexing and Querying”
– Discussion, Brainstorming Issues and Challenges
12:00-14:00 Lunch with Photo Shooting
14:00-15:00 Session 1 continued
15:00-18:00 Session 2: Social Media Analysis for Disaster Management
Chair: Takahiro Hara (University of Osaka, Japan)
– Session Introduction/overview
– Position talks from participants
* Takahiro Hara (University of Osaka, Japan)
“Big Data Framework for Integrating Sensor Data and Information Extracted from Social Media”
* Calton Pu (Georgia Tech, USA)
“Big Data Research Opportunities in Disaster Management: The LITMUS Landslide Information Service as an Illustrative Example”
* Kyoungsook Kim (AIST, Japan)
“Mining Social Media to Support Disaster Management”
– Discussion, Brainstorming Issues and Challenges
18:30-19:30 Dinner
19:30- Free Time

Day 2 (Tuesday, 29th March)

07:30-09:00 Breakfast
09:00-12:00 Session 3: Disaster Data Collection Using Crowdsourcing
Chair: Cyrus Shahabi (University of Southern California, USA)
– Session Introduction/overview
– Position talks from participants
* Stephen Jones (The MITRE Corporation, USA)
“Enabling the Crowd for Emergency Crisis Management”
* Seon Ho Kim (University of Southern California, USA)
“Effectively Crowdsourcing the Acquisition and Analysis of Visual Data for Disaster Response”
* Asanobu Kitamoto (National Institute of Informatics, Japan)
“Situational Awareness by Social Solutions: Textual Geo-Tagging and Photographic Crowd-Reporting”
* Nalini Venkatasubramanian (University of California-Irvine, USA)
– Discussion, Brainstorming Issues and Challenges
12:00-13:30 Lunch
13:30-14:30 Session 3 continued
14:30-18:00 Session 4: Big Data Analysis and Platform for Situational Awareness
Chair: Takahiro Hara (University of Osaka, Japan))
– Session Introduction/overview
– Position talks from participants
* Yoshihide Sekimoto (University of Tokyo, Japan)
“Estimation of People Movement from Mobile Phone Data using Data Assimulation Technology”
* Hiroki Ishizuka (KDDI R&D Laboratories, Inc., Japan)
“Traffic Flow Analysis for Urban Railway Networks using Self-learnt Cellular Handoff Patterns”
* Helmut Prendinger (National Institute of Informatics, Japan)
“A Situational Awareness Platform for Disaster Response based on the Supervision of Multiple Unmanned Aerial Vehicles”
– Discussion, Brainstorming Issues and Challenges
18:30-19:30 Dinner
19:30- Free Time

Day 3 (Wednesday, 30th March)

07:30-09:00 Breakfast
09:00-12:00 Session 5: Challenges on Big Data Research for Disaster Management
Chair: Calton Pu (Georgia Tech, USA)
– Session Introduction/overview
– Position talks from participants
* John Wilson (University of Southern California, USA)
“The Challenges and Opportunities Accompanying Geospatial Big Data”
* Gurdip Singh (Kansas State University and NSF, USA)
“Perspectives on Smart and Connected Communities and Cyber-Physical Systems”
* Jianwei Yin (Zhejiang University, China)
“Security Channel for Enterprise Big Data Platform to Deliver Public Service”
* Teruo Higashino (Osaka University, Japan)
“Crowd Sensing from Heterogeneous Sensors for Disaster Mitigation”
– Discussion, Brainstorming Issues and Challenges
12:00-13:30 Lunch
13:30-18:00 Excursion to Kamakura
19:00-21:30 Banquet Dinner
21:30- Free Time

Day 4 (Thursday, 31st March)

07:30-09:00 Breakfast
09:00-12:00 Closing Session
– Idea marketplace and future collaborations
– Final organizer presentation and wrap up
12:00-13:30 Lunch



Sanjay Madria, Missouri University of Science and Technology, USA
Takahiro Hara, University of Osaka, Japan
Cyrus Shahabi, University of Southern California, USA
Calton Pu, Georgia Tech, USA
Yoshihide Sekimoto, University of Tokyo, Japan
Hiroki Ishizuka, KDDI R&D Labora-tories, Inc., Japan
Teruo Higashino, Osaka University, Japan
Hideki Hayashi, Hitachi, Ltd., Japan
Seon Ho Kim, University of Southern California, USA
Stephen Jones, The MITRE Corporation, USA
John Wilson, University of Southern California, USA
Matthias Renz, George Mason University, USA
Kyoungsook Kim, AIST, Japan
Asanobu Kitamoto, National Institute of Informatics, Japan
Gurdip Singh, Kansas State University and NSF, USA
Jianwei Yin, Zhejiang University, China
Kuo-yi Lin, Asia University, Taiwan
Yasushi Sakurai, Kumamoto University, Japan
Helmut Prendinger, National Institute of Informatics, Japan
Nalini Venkatasubramanian, University of California-Irvine, USA

Access to Shonan Village Center

For access to Shonan Village Center, please refer to the web page on the NII Shonan Meeting Web site:

Access to Shonan Village Center


Mar. 30th, 2016

13:30    Depart at the Village Center by bus

14:10    Arrive at Kotokuin Temple

Meet the Great Buddha Statue

14:40    Leave the temple by walk

14:55    Visit Hasedera temple

Meet the Statue of Goddess of mercy

16:00    Leave the temple by bus

16:20    Arrive at the Hachiman-gu Shrine

Visit Hachiman-gu Shrine

18:00    Leave for the restaurant by bus

18:15    Banquet at Japanese style restaurant “Minemoto”

20:15    Leave for the Village Center by bus

20:45    Arrive at Hotel

Guided by Kanagawa Systematized Goodwill Guide Club


Kamakura History

-The Samurai Capital-

Yoritomo Minamoto, the warlord who prevailed in the (mass) civil war at the end of the Heian period, destroyed the power of the Hei family, the ruling dynastic power of the day.

He became the Seiitai shogun and initiated the Kamakura Shogunate. The Samurai administration strengthened its foundations from those years onward and stayed in control until the middle of the 19th century. Minamoto organized the Shogunate institutions and started Kamakura’s town planning and construction was mostly complete, the Shogunate entered its golden age.

Kamakura became the capital in every respect-politically, militarily, diplomatically, and culturally. Trade with ancient China became active and Zen Buddhism, statues of Buddha, lacquerware, etc. were assimilated. Today still, after long centuries, Kamakura retails the prosperity and brilliance of its of culture in the golden age.

kamakura1 kamakura2

Hasedera Temple