1. eCulture Science Gateway – reloaded
Implementation of
eCulture Science Gateway – reloaded
Luca Martinelli
Istituto Centrale per il Catalogo Unico (ICCU)
e-Research Summer Hackfest
RIA 1

2. INDIGO-DataCloud RIA-653549
Outline
The experiment regards the digital library “MuseiD-Italia”, which showcases digital objects and metadata regarding Cultural Heritage in Italy
We are trying to revamp the whole workflow in order to make it better, easier & faster, as well as adding new potential features
This is only the first step – other ICCU projects (larger than this) will also be included in experimentations in the next months
My focus will be on analysing the current workflow, the problems we are facing, and how to possibly integrate INDIGO solutions
INDIGO-DataCloud RIA 2

3. INDIGO-DataCloud RIA-653549
What is MuseiD-Italia
MuseiD-Italia is a digital library devoted to museum. It’s integrated in CulturaItalia, that is the Italian portal of culture
The Digital Library is based on FEDORA Commons
repository accessible via the REST protocol
data sharing is available via OAI-PMH protocol (Open Archive Initiative)‏ for incremental harvesting (especially to CulturaItalia)
6,434 museums descriptions (from the National Registry)
449 digital collection of more than 360 museums (from the partners)
more than 95,000 digital objects (images and videos) in the digital library (from the partners)
INDIGO-DataCloud RIA 3

4. INDIGO-DataCloud RIA-653549
System requirements
Linux server operating system
Database MySQL
Java (JDK version 1.6)
Tomcat servlet container
Fedora Commons (version 3.4)
OAI Provider Service 1.2 (Proai)
Mass storage of adequate capacity in RAID configuration
INDIGO-DataCloud RIA 4

5. INDIGO-DataCloud RIA-653549
System architecture
INDIGO-DataCloud RIA 5

6. Integrating distributed data infrastructures with INDIGO-DataCloud
Users role in MuseiD-Italia: levels of access
End User: any user, authorised by default only for basic browsing
Collections Manager: a registered user from partner institution (validated through federated access), that uploads digital contents to the repository and is responsible for their management
Administrator (ICCU): supervision role which grants collections coherence, managing of user authorizations and that has last-resort powers of rollback
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7. INDIGO-DataCloud RIA-653549
How it works
MuseiD-Italia is interoperable with the National Registry of museums and it import data via FTP
Partners may create their digital collections using free downloadable software
METS GENERATOR: it generates xml METS-mdi records from the packages resulting from the packaging tool
METS VALIDATOR it validates METS-mdi records resulting from the METS generator
The ingestion process is centralized and managed by ICCU
INDIGO-DataCloud RIA 7

8. Integrating distributed data infrastructures with INDIGO-DataCloud
The workflow right now
Digital objects and metadata are collected/digitised by our partners
Content is fed into METS Generator and organised into “METS packages” (in compliance to METS-MDI standard)
Packages are then validated (i.e. METS Validator software checks that XML metadata files are compliant with the METS-MDI standard)
Once validated, packages are sent to ICCU and imported through FTP to our central Fedora-based repository (“METSTeca”)
The Digital Library Administrator links the METS packages to the Museum record imported by the Registry
Periodically, MuseiD data are harvested by CulturaItalia portal through OAI-PMH
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9. Integrating distributed data infrastructures with INDIGO-DataCloud
What are the (most important) problems
The data collection, generation and upload phases are centralised (i.e. they are almost entirely on us)
We need more calculation capacity to manage the elaboration of METS packages and their upload to the Digital Library
The process of correction/modification of descriptive metadata should be further improved
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10. Integrating distributed data infrastructures with INDIGO-DataCloud
Implementation strategy
Data collection phase: we plan to move to a OneData solution, in order to allow our partners to directly upload their content on the platform
We will need to adapt the users’ level-of-access part, also integrating federated access to the platform
Data generation, validation and management phases also will probably be moved on a virtual machine (Ophidia?), which will use the Kepler tool to automate all these processes
[TO BE ANALYSED] Correction/modification of data made easier for institutions
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11. Integrating distributed data infrastructures with INDIGO-DataCloud
Thank you!
Any questions?
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