iot observatory
TRANSCRIPT
IoT Observatory: Infrastructure & Technical ChallengesUniversity of Southampton
IoT Observatory
Visualisations
Historical
DcatApps Metadata
Datasets/Streams
EfficientTranslation
Schema.org
Real-time
Analytics
People/Communities
C4: Support
Analytics
C3: Diverse Stakeholders
C1: Data Discovery &
Heterogeneity
C2: DataPrivacy &
AccessEngagement
4Cs – Four Challenges for IoT Observatory
• Inspired by the Web Observatory initiative of Web Science Trust1
1. http://www.webscience.org
C1: Data Discovery
• At present: Centralized search across Observatory sites • http://search.webobservatory.org/ • Using metadata (schema.org) and datasets • IoT datasets description – Hypercat
• Moving towards: Distributed search reaching lightweight computers/base stations
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C2/C3: Data Privacy & Diverse Stakeholders
• Adopting reverse proxy and URL obfuscating technologies to protect private and sensitive data
• Data Publisher controls – location, visibility & access of datasets
C2/C3: Access Control & Diverse Stakeholders
1. Present IoT Observatory - distinguishes b/w metadata and content
2. Working towards – Easy-to-use Web interface for Access Control
• Granularity - IoT datasets, meta-data, aggregations & correlations
• Entities- Data owner(s), publisher(s), device(s)
• Data owners/Publishers – able to evaluate trade-offs, permit & restrict data
processing/usage– Implement data sharing negotiations with the stakeholders
06-11-2016 SOCM Workshop 2016 6
Dataset 1 Dataset 2 Dataset 3
Data Harmonization
Spatio-temporal filter(s) Aggregation(s) Visualization(s)
App 1 App 2 App 3
Distributed Datastores
Applications
Observlet Inventory
Madaan, Aastha et al. “Observlets: Empowering Analytical Observations on Web Observatory.”, SOCM’16, WWW (2016).
• Fine granularity data processing control
C2/C3: Access Control & Diverse Stakeholders (1)
C4: Support for Analytics
● Built-in smart API for building data-driven applications
