SMIRP Barnett 2002
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Transcript of SMIRP Barnett 2002
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SMIRP
Jean-Claude [email protected]
Drexel University
Barnett International Conference on Laboratory Notebooks
08/14/2002
Effective use of a self-evolving database for information capture and retrieval in an R&D
environment
http://smirp.drexel.edu
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LIMS CENS
Single Instrument Automation
Laboratory Information Management Systems
Collaborative Electronic Notebook Systems
Human /Autonomous Agent Hybrid Systems
Human ManagedFully AutonomousScientific Research Systems
TODAY
SMIRP bridge
The Evolution of Automation in Scientific Research
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HumanAgent
AutonomousAgent
SMIRP
Automation SWAT team
(Bot)
Browser
Excel
The SMIRP model for a hybrid Human/Autonomous Agent System
Anthropomimetic Design
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Approaches to Collaborative Electronic Notebooks
rigid
SMIRPcompromise:
Rigid information representationFlexible linking of modules
flexible
•Structured•Generally
domainspecific
•Adaptable•Unstructured
http://smirp.drexel.edu
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Add informationto database
Retrieveinformation
Modify database structure
Functional Requirements of a collaborative electronic notebook
SMIRPRequest
structuralmodification
http://smirp.drexel.edu
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Two approaches to the development of databases
Communicateanticipated
need
Designdatabase structure
Let database structureevolve
through useSMIRP
http://smirp.drexel.edu
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Fundamental Information Representation in SMIRP
Module 1 Module 2
Parameter 1
Parameter 2
Parameter 4
Parameter 5
instance
Record 1
instance
Record 2
http://smirp.drexel.edu
(People)
(Name)
(Employee of)
(Company)
(Name)
Parameter 3(email)
(Address)
Bill Gates Microsoft
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Case-study: Evolution of SMIRP structure in a chemistry laboratory
Location Drexel University
Department of Chemistry
Users faculty, undergraduate students, graduatestudents, librarians and other university personnel
Period Feb 1999 – April 2001, with a detailed focus on
last 7 months (Sept 2000-April 2001)
Total accounts (last 7 months) 78
Active Accounts (added records) 50
Administrators (changed database structure)
9
http://smirp.drexel.edu
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HumanResource
Management 13%
Maintenance1%
Knowledge Processing
72%
Most Active Module Categories (9/00 – 4/01)
Labwork14%
118 modules 1/3 account for 98% of activity
http://smirp.drexel.edu
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Most Active Knowledge Processing Modules
Journal 9%
Knowledge Filter 3%
ReformatReference requests
20%FindReference
66%
PublisherDocument ProductionReference ProcessingParameter CorrelationData source filesExperimental Conclusion GenerationKnowledge consolidation
http://smirp.drexel.edu
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Most Active Laboratory Modules
Preparation of Silver rods for SCBETEM Micrographs Of Pd on CSCBE on membranesHydrogenation of Crotonaldehyde using Pd CatalystsReduction of Methylene blue by Pd Metal Particles in a Field
Electrodeposition of Pd on Graphite
29%
Protocol Prototyping25%
Pd onto Carbon Nanofibers
17%
Electroless plating on Membranes
9%
Synthesis of Pd catalysts by Bipolar electrochemistry
5%
TEM Micrographs Of Pd on C
3%
Pd particle size analysis using TEM
3%
http://smirp.drexel.edu
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Recruitment events 2%
ProjectManager
5%Errors5%
Productivity Tracking
14%
People 28%
Workstudy hours reporting
46%
Most Active Human Resource Management Modules
http://smirp.drexel.edu
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Most Active Maintenance Modules
SMIRPProblems
22%
Orders 19%
Invoice (TEM/SEM and other instrument charges)
19%
Laboratorymaterials
16%
Vendor15%
Orderforms9%
http://smirp.drexel.edu
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Activity Analysis by Category over Time
20
00
-10
-3
20
00
-10
-17
20
00
-10
-30
20
00
-11
-12
20
00
-11
-25
20
00
-12
-8
20
00
-12
-21
20
01
-1-3
20
01
-1-1
6
20
01
-1-3
0
20
01
-2-1
2
20
01
-2-2
5
20
01
-3-1
0
20
01
-3-2
3
20
01
-4-5
20
01
-4-1
8
Maintenance
Human Resource Management
Laboratory Work
Knowledge Processing0
1000
2000
3000
4000
5000
6000
7000
8000
http://smirp.drexel.edu
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For agents to make a decision to:
ACT NOT ACT
Generally for quality controlExpected information: Retrieve details and execute from a menu of predefined tasks
Unexpected information: Redesign tasks
This could be absence of information:“No News is Good News”
WHY retrieve information?
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Active
Passive
Negative (implied)
Pre-emptive
I want to know something NOW
Keep me updated regularly with new information
No news is good news
Tell me things I SHOULDwant to know but have not asked for
Burden on Agent
Highest
Lowest
Are your closest familymembers alive?
A competitor has initiated research in my market space
New experiments in a particular project
Obtaining a phone number
Description ExampleMode
HOW Agents Retrieve Information
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Active
Browser
Excel
Interface
Information Filter
TimeKeyword User ContextSimilarity
Passive
Operation
SMIRP Information Retrieval Matrix
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Keyword Search Results: example “nanotube”Active Information Retrieval : keywords
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From Keyword to Article
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From Keyword to Knowledge Filter
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From Keyword to Orders
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From Keyword to Protocol Prototyping
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Active Information Retrieval : Time Filtered
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Active Information Retrieval: User and Operation Filtered Search
Autonomous AgentMonitoring
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Active Information Retrieval: Similarity Based
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Active Information Retrieval: Context Based
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Passive Information Retrieval: Email Alerts
Space Level Module Level
All Activity
New EntriesWhen link to article has been foundMonitor progress of software development
Keep track of which software version users have downloadedMonitor which experiments are being investigated
Keep track of special users:Job applicantsFormer usersCollaborators
Updates on report or article being written
(general) (specific)
New activity related to keywords
Quality control of autonomous agent activity
Quality Control of workflows
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Module-Level Alerts: Creation of an alert for new urls to articles
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Module Level Alerts: Creation of an alert for new urls to articles
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Space Level Alerts: example of keyword filtering
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Seamless Integration of Human and Autonomous Agents in Workflows
Real-Time Workflow Designs
Automated
Human(default)
State A State B
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Workflow for Extraction of Article information and url
Queries Web and extracts information
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AutonomousAgent
Successful Processing
Citation to be Processed
Portal Not Found
Citation Invalid
Information Missing
HumanAgent Handles exceptions
Human/Autonomous Agent Coordination in Workflow
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Pre-emptive information retrieval
Report experimental results
Read experimental results
Generate Search Strings
Read search strings
Report on search results
Alerted to new documents of potential interest
Parsebot Googlebot
Finding documents that should be of interest to current work
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Pre-emptive information retrieval
Finding documents that should be of interest to current work
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Pre-emptive information retrieval
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Pre-emptive information retrieval
Finding documents that should be of interest to current work
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Leveraging and Extending Bot Implementation
Citation bot in other laboratory research and teaching spaces
In online class SMIRPspace: Plagiobot System
Automatic Content Summarization Tools
Analysis/verification of experimental data analysis
Conversion from Passive to Negative Information Mode: Bot Monitoring of other Bots
Monitoring of competitor/collaborator activity (patents/papers)
Automatic Keyword Generation from most frequently used or read words
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Conclusions
This is still a “Human World”
SMIRP can serve as a framework to allow Human and Autonomous Agents to operate freely within a Laboratory Research Collaborative Space
Automation within workflows can be accelerated by creating Autonomous Agents that are more Human-like in how they retrieve and store information
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Acknowledgements
Benjamin SamuelSundar Babu
Raj HooliKetan Patel
Mohammad Haghkar
NSF CAREER CHE-9875855CIA
http://smirp.drexel.edu