e-Infrastructures for Astronomy:
an integrated view
F. Pasian (1,2), G. Longo(3)(1) INAF – Information System Unit, (2) INAF – Osservatorio Astronomico di Trieste, (3) Università di Napoli “Federico II”

As in the case of other disciplines, the capability of performing “Big Science” in astrophysics requires the availability of large facilities.
Computational resources (e.g. HPC) are important, but are far from being enough for the community: as a matter of fact, the whole set of einfrastructures (network, computing nodes, data repositories, applications) need to work in an interoperable way. This implies the development ofcommon (or at least compatible) user interfaces to computing resources, transparent access to observations and numerical simulations through theVirtual Observatory, integrated data processing pipelines, data mining and semantic web applications. Achieving this interoperability goal is a must
to build a real ``Knowledge Infrastructure" in the astrophysical domain. Also, the emergence of new professional profiles (e.g. the “astroinformatician”) is necessary to allow defining and implementing properly this conceptual schema.

TheoryNumerical simulations
Data reductionData Analysis...
applications havedifferentrequirements, butshare the same
infrastructure

Computing

DATA

Applications

NetworkIn order to cope with the rapid increase in production and use of scientific information a high-quality and reliable repository infrastructureis essential. The emergence of “big data science” has a global dimension, as it reflects the increasing value of raw observational andexperimental data not only in astronomy, but in virtually all fields of science.
The Virtual Observatory (VObs) has helped a lot in conveying the concept that data need to be shared to allow scientific advance in ourfield. But, besides raw and processed data, also publications, technical reports and white papers, software artifacts, numericalsimulations, etc. all need to be taken in consideration. The VObs, within its IVOA ‘standards’ body, has recently made lots of progress inthe direction of characterising 'scientific information' in a simple way. But this is confined to a limited set of data products and needs tobe properly expanded.

Networke-Infrastructure

DataAlthough astronomy is at the forefront of the digital data landscape, it is estimated that only a limited part of its research output ismanaged in digital repositories. Therefore, a new strategy for the management of scientific information and associated policies needs tobe developed. This has to be done with the support of key research stakeholders as well as academic institutions and libraries.
But of course electronic access to data resources has costs involved (e.g. hardware, high-speed internet access, staff for maintenance),
and most of these costs are left to the information providers.

To offer scientists a useful service, all of the components of the informaticsinfrastructure need to be thought as integrated, or at least fullyinteroperable. In other words, the various infrastructure components(applications, computing, data) should interact seamlessly exchanging
information, and be based on a strong underlying network component.

Is developing domain-specific data repositories something still affordable in a period of economic recession? Or is it more cost-effective
to develop a data infrastructure jointly with other disciplines, and implement on top of such a common infrastructure the domain-specificlayer for data access (i.e. a VObs-enabled user interface)?

COMPUTINGAPPLICATIONS

To perform their research, astrophysicists heavily use a wide range of facilities: computing and storage capacities,
archives plus, of course, the research networks. Astronomical institutions in all countries participate actively in theinternational initiatives in the field, and usually participate in defining national development policies together withthe other disciplines.
CEApplications are the key of astronomical computer-aided research. Scientists develop codesof their own to perform personal research. To be integrated with other ‘standard’ dataprocessing codes, such development has to embedded in a data processing environment.

Considering first the computing infrastructure, the facilities available to the scientists can be very different: from thelaptop or desktop PC to the HPC center, passing through local clusters and ``the Grid''. From SE
the user perspective,
ideally, all facilities should be seen homogeneously; in reality, they all tend to have different access modes. As aresult, users find obstacles to their ideal exploitation.
In the medium-to-long-term it is important to reach complete interoperation of HPC centres: initially, Tier-2(regional) facilities shall be integrated with the Grid, followed by full integration of local clusters (`Tier 3') and, asfinal goal, achieving inclusion of Tier-0/1 (national and international) within a common scheme. In any case, anecessary step is to achieve as soon as possible the full compatibility between HPC and Grid at least at the User
Interface level.

The OPTICON (Optical-Infrared Co-ordination Network for Astronomy) proposal was fundedby the EU FP7. It contains a network (N9.2) for discussing detailed designs and specifications
for a future environment for data analysis in astronomy.
In a different paradigm, some applications are used as services provided by centres, andusers can run them as black-boxes, without really caring about the computing resources they
are run onto. This has been successfully applied for the production on-demand of numericalsimulations (the BaSTI database), or for statistical analysis and data mining on large data
sets (DAME).
A key issue for the complete exploitation of the potentiality of applications is the developmentof proper scientific gateways allowing seamless access to the codes.

The Grid concept should become far more widespread than currently. The old perception of the Grid re-using theidle cycles of a set of PC's (as was in the SETI@home experiment that originated the Grid concept) is nowadays
completely misleading -- from the computing and storage viewpoints, the Grid has now the possibility of linking
powerful clusters and even HPC hardware, provided it uses the proper middleware and high-throughput
connections..
There is a further point. Up to now, the Grid has mainly delivered computing power, the main issue that its
implementers, mostly involved in large High-Energy Physics experiments (e.g. at CERN in Europe), needed tosolve. Accessing data, and databases using the Grid paradigm is a step still to be improved. Some activities arebeing carried out within EGEE. This is of course a further step in the direction of interoperability.

Knowledge Infrastructure

VObs
appl

The “big science” challenges in astrophysics call for an expansion of the computing infrastructures -- and of networkand data management infrastructures as well. The community is interested in using, and participating in defining,
competitive computing infrastructures so to let its know-how in the field grow. But there is furthermore the desire tointegrate the network, data and computing infrastructures, or at least to let them interoperate.
To fulfill this requirement applications, computing power, data repositories and databases holding metadata or
catalogues should be accessed as a single utility. It needs to have a Virtual Observatory interface, which is morefamiliar to our community.

appl

...

appl

DataComputing.
Networkappl

The different layers of the integrated
ICT infrastructure for astrophysics.
Scientific applications may interact
with the Data Infrastructure, or withthe Computing Infrastructure, or
directly with the Network
Infrastructure (each interacting witheach other). The interoperation ofspecific applications creates a
Knowledge Infrastructure. Thedashed box defines the area where
the Virtual Observatory is expectedto act.}ASTRO-INFORMATICSAs it has been stressed in the report of the 2007 NSF workshop on data repositories “data-driven science is becoming a new scientific paradigm, ranking with theory, experimentation, and computational science”.
Astronomy has become a data-rich science , with data volumes rapidly growing from terabytes into tens (or hundreds) of petabytes. These data sets have posed scalability problems which are causing a strong shift in
the way data are manipulated, reduced and understood. Problems which call for a set of know-hows in algorithms (scalability, parallel codes, etc), infrastructures (GRID, cloud computing, HPC) and access (web servicesand web applications) which do not belong to the traditional astronomical background. So far, these problems have been addressed in an informal way, leaving most of the required special expertise to e-Science, buthave posed the foundations of an increasingly tight integration which will prove crucial in the near future when larger and larger data sets (both simulated and observed) will become available.
We believe that time is mature to promote (as it has already happened in other fields of research such as geo-informatics and bio-informatics) a major new discipline, which can be called Astro-informatics, to beintegrated into Astronomy as a formal sub-discipline within agency funding plans, university research programs, graduate training, and undergraduate education.
In our understanding, Astro-informatics is an essential methodology for data-oriented astronomical research and the future of astronomy depends on it. Astro-informatics includes a set of naturally-related specialties: datamodeling and description, data integration, information visualization, data mining and knowledge extraction, indexing techniques, classification taxonomies, ontology, etc.