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None of these proposals have come to completion due to the complexity of the task.
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None of these proposals has come to completion due to the complexity of the task.
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The source DM issue resurfaced at the spring 2018 Interop in Victoria during an hands-on session
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focusing on the tools available to work with VO data models and especially with VO-DML.
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The goal of this session was to annotate data from different origins in order to make them
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interoperable with each other.
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The main concern expressed during this session was not much related to the tools themselves
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but indeed to the lack of models for sources.
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The goal of this session was to annotate astronomical data from different origins in order to make them
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interoperable with each other. The main concern expressed during this session was not much related to the tools themselves but indeed to the lack of models representing sources.
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This is a paradox in the VO world: source data which represent the basic building
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blocks of astronomers' work, is not modelled.
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This paradox can be explained by the fact that the observation of source objects is multi-faceted.
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In a general way, the way features for source data are described and organised depends on
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In a general way, the way features for source data are described and organized depends on
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the targeted science case.
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Principal investigators and archive designers set up the data profile and structure it according
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to this goal which varies from one project to another.
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Therefore this diversity cannot be served by a single static data model describing a source
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item for all possible cases.
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Having a global source model would lead to a very complex solution not usable in practice.
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Having a global all-purpose source model would lead to a very complex solution not usable in practice.
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This standard proposes to overcome this paradox and presents a template model gathering independent
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In contrast this specification proposes to overcome this paradox and presents a template model gathering independent
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components from VO existing models embedded on demand in a container.
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MANGO is not designed to describe what a source is but to help clients to discover and to understand
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the quantities available for a particular source instance.
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VOtable data mapped on MANGO with Mivot (2023ivoa.spec.0620M) annotations can be consumed quantity
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par quantity instead of column per column.
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The way complex quantities are built is described by MANGO but no longer by the clients.
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the features (i.e quantities) available for a particular source instance.
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VOTable data mapped on MANGO with MIVOT (2023ivoa.spec.0620M) annotations can be consumed on a feature basis
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instead of column per column.
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The way complex quantities are built is described by MANGO but no longer by the client applications.
\caption{Architecture diagram showing the MANGO DM and its relations to other IVOA specifications}
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\label{fig:archdiag}
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\end{figure}
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Fig.~\ref{fig:archdiag} shows the role this document plays within the
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IVOA architecture \citep{2010ivoa.rept.1123A}.
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IVOA architecture \citep{2010ivoa.rept.1123A}. This model reuses existing data models like Measure and Coords, and PhotDM. Implementations can use the TAP protocol and distribute data model instances in VOTable.
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UCD, VOUnits and Vocabularies are also re-used.
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\section{Representing observed astronomical objects : Use Cases and Requirements}
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