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Agents and Social Networks Environments for Digital Preservation
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Agents and Social Networks Environments for Digital
PreservationProf. Peplluis de la Rosa
Albert TriasEASY INNOVA @ UdG
Nov 2007 – Oct 2010
10/05/2013 1
PROTAGE Consortium PReservation Organizations using Tools in AGent
Environments National Archives of Sweden
Luleå University of Technology (Sweden)
National Archives of Estonia
Fraunhofer Gesellschaft zur Förderungder angewandten Forschung e.V. (Germany)
University of Bradford (U. K.)
EASY Innova @ UdG (Spain)
Giunti Labs S.r.l. (Italy)
Digital Preservation?
10/05/2013 3
Tones of personal data!
DATA DELUGE (Fran Berman)
Opportunities
Digital Preservation is a social duty;
not only institutions but individuals
10/05/2013 5
Digital data paradigm shift
180 Exabytes
1600 Exabytes
9X Growth95%
Unstructured
70% Created by Individuals Enterprises responsible for 85% of this new data(Security, privacy, reliability, compliance)
The Digital Data Paradigm Shift2011 New Digital Data
(25% Created, 75% Replicated)
2007 New Digital Data(Created, Captured, Replicated)
10/05/2013 7
67% of DP expert users % think that the Digital Preservation solutions they have today are not good enough, or are insufficient (43%) or scarce (23%). So they look for new DP solutions
DP is socialFragmented DP
Knowledge• 67% of expert users look
for solutions provided by other institutions.
• 90% of them consult trusted colleagues.
• 83% consult final users
Frequent Knowledge Exchanges
• 83% of expert users share their knowledge
• 77% search through the web for solutions
• 60% visit DP web sites• 20% contribute to the
web sites
10/05/2013 8
community of DP experts are in favour of DP knowledge exchanges with colleagues and other institutions, and they are equally happy to do it with individual users
DP Price• Distribution chanel of DP: there is slight preference for
being bundled with storage services (77%) rather than being bundled with antivirus tools (63%). The key issue is that PROTAGE will attract DP knowledge exchange among expert users through Internet though it will also distribute the DP knowledge and solutions to individual users via storage software and antivirus tool bundles. The expert users (64%) claim they would accept to pay 10% of the price of the storage service, being the estimated price of 15% of the storage service and 13% of the antivirus service.
10/05/2013 9
DP Opportunities
• DP Consultancy• Indexing: deep web• Social search
Peer DP services like• ”keeping your copies
as you keep mine”• Crossed services
before preservation (i.e., enhancing content)
10/05/2013 10
Users show a slight preference for DP being bundled with storage services (77%) rather than being bundled with antivirus tools (63%). Expert users (64%) claim they would accept to pay 10% of the price of the storage service, being the estimated price of 15% of the storage service and 13% of the antivirus service.
PROTAGE–intelligent agents
• Social search is implemented
• Experts and final users share DP solutions
• Lists of trust guide the social search
It might seem the Facebook of DP
• Agents automate the social search for DP solutions in terms of actions plans and migration support
• Agents proactively schedule the preservation tasks
Agents are a type of peer services
10/05/2013 11
First time a DP effort that targets not only memory institutions
The prototype = IT Innovation
Agent technology can be applied to DP
Agent technology can simplify DP for many users and groups …
PROTAGE = Intelligent AgentsWHY AGENTS?
1210/05/2013
PROTAGE = Intelligent AgentsWHY AGENTS?
13
•Agents:• Are reactive: react after receiving a question.• Are social: capability to communicate to
others.• Are proactive: take initiative.• Are autonomous: ability to work
independently.• Agents enable the construction of information
systems from multiple heterogeneous sources [Dignum 2005]
10/05/2013
How Agents do Social Search?
14
When a User is searching for a DP Plan, the query is sent to her Searcher Agent.
The Searcher Agent:• Search in the local Knowledge Base• Search in Institution Repositories Knowledge Base• Asks friends’ agents (send and forward message)• Filter Results:
• Only DP Plans well rated by friends• Only DP which are owned by users of with some features.• Hybrid
• Can show the question to its user.• The effort of a search depends on the trust it has to the sender.
10/05/2013
Search Example
15
ActionPlan Eloy Albert Alex Access-Point
Image conversion (3versions) X X X
Tech medatada extraction X X X
Local AV Check X X
Local AV Clean X X
Remote AV Check X X
Remote AV Clean X X
Generic Image Conversion (certified) X
Calc MD5 X
1. Alex searches the keyword “AV”.in the “Application local DB” No result is found.
Alex’s SA Eloy’s SA Albert’s SA
AV
Local DB
10/05/2013
Search Example
15
ActionPlan Eloy Albert Alex Access-Point
Image conversion (3versions) X X X
Tech medatada extraction X X X
Local AV Check X X
Local AV Clean X X
Remote AV Check X X
Remote AV Clean X X
Generic Image Conversion (certified) X
Calc MD5 X
1. Alex searches the keyword “AV” in the“Application local DB” No result is found.
2. Alex’s Agent searches for a certified actionplaninto the Access Point (institutional point of view,with certified plans). No result is found again.
Alex’s SA Eloy’s SA Albert’s SA
AV
Access Point DB
10/05/2013
Search Example
15
ActionPlan Eloy Albert Alex Access-Point
Image conversion (3versions) X X X
Tech medatada extraction X X X
Local AV Check X X
Local AV Clean X X
Remote AV Check X X
Remote AV Clean X X
Generic Image Conversion (certified) X
Calc MD5 X
1. Alex searches the keyword “AV” in the“Application local DB” No result is found.
2. Alex’s Agent searches for a certified actionplaninto the Access Point (institutional point ofview, with certified plans). No result is foundagain.
3. The Agent asks its friend Eloy (distance = 1).
Alex’s SA Eloy’s SA Albert’s SA
AV
10/05/2013
Search Example
15
ActionPlan Eloy Albert Alex Access-Point
Image conversion (3versions) X X X
Tech medatada extraction X X X
Local AV Check X X
Local AV Clean X X
Remote AV Check X X
Remote AV Clean X X
Generic Image Conversion (certified) X
Calc MD5 X
1. Alex searches the keyword “AV” in the“Application local DB” No result is found.
2. Alex’s Agent searches for a certified actionplaninto the Access Point (institutional point of view,with certified plans). No result is found again.
3. The Agent asks its friend Eloy (distance = 1).4. Eloy’s agent checks whether 4 matching plans
are good for Alex (trust-guided decision). Twoplans (collection and author) do not match; theirfulfilment F = .35 is lower than the QoS of .50(the Quality of Service threshold).
5. On the other hand, two trusted plans match(fulfilment F=1.00 as author and collectionmatch higher than .50 of the QoS). Eloy’sAgent sends these 2 actionplans to Alex. Local DB
Alex’s SA Eloy’s SA Albert’s SA
AV
2 resultsfound
10/05/2013
Search Example
15
ActionPlan Eloy Albert Alex Access-Point
Image conversion (3versions) X X X
Tech medatada extraction X X X
Local AV Check X X
Local AV Clean X X
Remote AV Check X X
Remote AV Clean X X
Generic Image Conversion (certified) X
Calc MD5 X
1. Alex searches the keyword “AV” in the“Application local DB” No result is found.
2. Alex’s Agent searches for a certified actionplaninto the Access Point (institutional point ofview, with certified plans). No result is foundagain.
3. The Agent asks its friend Eloy (distance = 1).4. Eloy’s agent checks whether 4 matching plans
are good for Alex (trust-guided decision). Twoplans (collection and author) do not match; theirfulfilment F = .35 is lower than the QoS of .50(the Quality of Service threshold).
5. On the other hand, two trusted plans match(fulfilment F=1.00 as author and collectionmatch higher than .50 of the QoS). Eloy’sAgent sends these 2 actionplans to Alex.
6. Alex’s Agent receives the actionplans fromEloy’s agent and ranks them for Alex.
7. The plans are added to Alex’s actionplancollection and are tagged “Eloy” as provider andauthor. Alex Eloy Albert
Local DBAdd and Ratenew plans
10/05/2013
Search Example
15
ActionPlan Eloy Albert Alex Access-Point
Image conversion (3versions) X X X
Tech medatada extraction X X X
Local AV Check X X
Local AV Clean X X
Remote AV Check X X
Remote AV Clean X X
Generic Image Conversion (certified) X
Calc MD5 X
4. If Eloy’s Agent did not found an Action Plan, then:1. Eloy’s Agent will show to Eloy the
question2. Eloy’s Agent will forward the question to
Albert’s Agent.
Alex Eloy Albert
10/05/2013
AVAV
PROTAGE Client Application
Collection andUser Profiles
SearcherAgent
SearcherAgent
Actions and Action Plans
Memory institution
Actions andAction Plans
SearcherAgent
PROTAGE Client Application
Actions and Action Plans
WS
WS
Execution agent
WS
WS
WS
WS
WS
WSWS
WS
WS
WS
WS
WS
WS
GatewayAgent
InstitutionalAgent
Memory institutionInstitutionalAgent
MigrationAgent
PlanetsCoreRegistry,Blogs, Forums
External knowledge bases
HarvestingAgent
1619.01.2011
What we learned: the DP relevance
• Novel approach, that way never seen before (both the approach and the prototypic solution)
• Adequate services (tools) offered for organizational and individual users alike
• Certain degree of “intelligence” shown by the solution• Step forward in bringing software agent technology
into DP domain (not yet reached the end of that road)• Personalization of user access to solution (profile,
preferences, own resources)• No prerequisite for expertise in DP before using the
solution (depends on complexity of action plans)
1719.01.2011
Future work (PROTAGE++)
1. The pro-activity of the solution is essential even if a “one-size-fits-all” solution is not expected to exist.
2. There is a need for expanding the potential of “digital preservation intelligence” embedded into the agents.
3. The system should be able to incorporate and analyze user’s collections. This adds to the aspect of personalization.
4. The system should make sure that it is able to efficiently point at particular problems in the domain, to problematic overall areas, and to specific potential risks.
5. The users need more help in formulating questions for searching for existing action plans.
6. A solution dedicated to “ordinary” private users with little or no experience in digital preservation requires the provision of a user-adapted graphical user interface with more predefined customizations but it pays off.
7. The solution must provide specific features for memory institutions allowing them to integrate the agent based technology into their daily procedures.
1819.01.2011
Main Achievements of the Project
(2) AUTOMATION- Execution of DP
tools (locally and as web services).
- Technology watch function (through
monitoring agents).
(4) TRUST MODEL- Trustable access to trusted information on
DP.
(5) AWARENESS- An understanding of others’ activities that bring context to ones
own activities
(1) AGENTS- Agent ecosystem as a design
concept for DP tools.
- Provide context-sensitive access to DP information from trusted knowledge
bases.
(3) KNOWLEDGE MANAGEMENT
- Reduces the knowledge gap between MIs and other users
- Provides new means for MIs to reach their ”clients”
- Reach more user groups.
- Practical means for sharing DP information through social networks and crowd-sourcing
MI = memory institutionsDP = digital preservation
PROTAGE
1919.01.2011
Future Technology Challenges
User adapted GUIs Specific features for memory institutions
Expand the intelligence potential –
Pro-active solution Analyze users´collections
Point at problem areas/risks
Help formulating questions
Identify other domains
2019.01.2011
