The document proposes an event-centric provenance model for digital libraries. It describes provenance as information about the source, derivation, and history of an object. Many existing provenance models make different assumptions. The proposed model captures provenance as a series of events that occur to reference objects. Each event has attributes like type, description, time, and agent. The model is non-invasive and flexible. It will be validated and implemented in digital library applications and infrastructures.

1. Introduction
An Event-Centric Model
Summary
An Event-Centric Provenance Model for Digital
Libraries
C. Tang D. Castelli L. Candela P. Manghi
P. Pagano C. Thanos
Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” – CNR, Pisa - Italy
name.surname@isti.cnr.it
6th Italian Research Conference on Digital Libraries
Padua, Italy, 28-29 January 2010
C. Tang et al. An Event-Centric Provenance Model

2. Introduction
An Event-Centric Model
Summary
Outline
1 Introduction
Motivations
2 An Event-Centric Model
The Constituents
Exploiting the Model
C. Tang et al. An Event-Centric Provenance Model

3. Introduction
An Event-Centric Model Motivations
Summary
What is Provenance?
Some pseudo-definitions:
“a summary of the history and context of the data”
“the parts of the input that influenced (or that explain) a
part of the output”
“the part of the input that shows where a part of the output
came from”
“a causal graph that shows how a result was computed”
C. Tang et al. An Event-Centric Provenance Model

4. Introduction
An Event-Centric Model Motivations
Summary
What is Provenance?
Provenance is thus information about
source, derivation, influences, history
. . . of an object
program result, database query
In e-Science (thus in DLs), it is essential for
efficiency, reproducibility, accountability, explanation, data
cleaning, certifying scientific value of data
C. Tang et al. An Event-Centric Provenance Model

5. Introduction
An Event-Centric Model Motivations
Summary
What is the Problem?
Many models are being developed
Where-provenance, links output parts to equal input parts
Why-provenance, explains “why” some data appears in the
result
How-provenance, explains “how” a result was calculated
Workflow, describes result of a parallel/distributed program
. . . using different assumptions, e.g. system scope, program,
granularity
Our goal: develop a “non invasive” and “open” model
supporting “provenance generation”
C. Tang et al. An Event-Centric Provenance Model

6. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Idea
Add a layer dedicated to capture provenance-oriented data
Reference Objects
Information Objects
Events
C. Tang et al. An Event-Centric Provenance Model

7. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Event is a happening having an effect on a Reference Object
<happenedTo> an Object
C. Tang et al. An Event-Centric Provenance Model

8. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Each Event has a Type for filtering purposes
C. Tang et al. An Event-Centric Provenance Model

9. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Description captures the “how” of the Event
C. Tang et al. An Event-Centric Provenance Model

10. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Place captures the “where” of the Event
C. Tang et al. An Event-Centric Provenance Model

11. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Time captures the “when” of the Event
C. Tang et al. An Event-Centric Provenance Model

12. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
The Agent controls the Event
C. Tang et al. An Event-Centric Provenance Model

13. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Rationale captures the “why” of the Event
C. Tang et al. An Event-Centric Provenance Model

14. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
The Parameter is any additional information
C. Tang et al. An Event-Centric Provenance Model

15. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The Model
Don’t reinvent the wheel!!!
C. Tang et al. An Event-Centric Provenance Model

16. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
Computing the provenance
4 1
5
3 2
C. Tang et al. An Event-Centric Provenance Model

17. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The granularity issue
High flexibility by relying on the Information Object relationships
Reference Objects
part-of
Information Objects
Events
C. Tang et al. An Event-Centric Provenance Model

18. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
The AquaMaps scenario
AquaMaps is one of the VRE supported by the D4Science
e-Infrastructure
Aggregate data on species from multiple and evolving data
sources (e.g. OBIS, GBIF)
Curate aggregated data
Generate species distribution and biodiversity prediction
maps
C. Tang et al. An Event-Centric Provenance Model

19. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
Example 1
Find the events occurred to the Salmon object
C. Tang et al. An Event-Centric Provenance Model

20. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
Example 2
Find the contributors to the Salmon object
C. Tang et al. An Event-Centric Provenance Model

21. Introduction
The Constituents
An Event-Centric Model
Exploiting the Model
Summary
Example 3
How to explain the existence of the Salmon object
C. Tang et al. An Event-Centric Provenance Model

22. Introduction
An Event-Centric Model
Summary
Summary
Provenance is an essential feature in Digital Libraries and
eScience scenarios
Many provenance models are being developed using
different assumptions
A DL oriented provenance model that is event-based,
“open” and “non invasive”
Future steps
validation and consolidation of the model in the context of
new DLs application scenarios
implementation of a infrastructural service realising the
model in the D4Science infrastructure
C. Tang et al. An Event-Centric Provenance Model

23. Introduction
An Event-Centric Model
Summary
Summary
Provenance is an essential feature in Digital Libraries and
eScience scenarios
Many provenance models are being developed using
different assumptions
A DL oriented provenance model that is event-based,
“open” and “non invasive”
Future steps
validation and consolidation of the model in the context of
new DLs application scenarios
implementation of a infrastructural service realising the
model in the D4Science infrastructure
http://www.d4science.eu
http://www.dlorg.eu
C. Tang et al. An Event-Centric Provenance Model