# [Volute] r4900 - trunk/projects/time-domain/time-series/note

Volute commit messages volutecommits at g-vo.org
Tue Apr 10 11:37:15 CEST 2018

Author: nebot
Date: Tue Apr 10 11:37:15 2018
New Revision: 4900

Log:
Modid-10April2018

Modified:

==============================================================================
--- trunk/projects/time-domain/time-series/note/time-metadata.tex	Tue Apr 10 11:05:22 2018	(r4899)
+++ trunk/projects/time-domain/time-series/note/time-metadata.tex	Tue Apr 10 11:37:15 2018	(r4900)
@@ -39,7 +39,11 @@
\textbf{Note:} $^1$For SSO or moving objects coordinates might not be enough or relevant.
\end{table}

-In many cases time series data is composed of only three colums: time, magnitude (or flux) and error in the magnitude (or in the flux). For this data to be fully exploitable and reusable (interoperable) it has to be properly documented. In this specific case the minimum information that needs to be provided is: the object coordinates (or name), the filter in which the observations have been carried out, and the time frame and offset (if applicable).
+In many cases time series data is composed of only three colums:
+\begin{center}
+time, magnitude, magnitude error
+\end{center}
+For this data to be fully exploitable and reusable (interoperable) it has to be properly documented. In this specific case the minimum information that needs to be provided is: the object coordinates (or name), the filter in which the observations have been carried out, and the time frame and offset (if applicable).

\subsection{Science use cases}
\label{sect:usecases}
@@ -75,7 +79,7 @@
To answer the first question a user needs to be sure that dates are comparable, that is time has to be brought into a common time frame. To answer the second question we need to keep track of the minimum and maximum time spam. We aim in a first step to answer these fundamental questions and, later on we will move to answer the specific science cases, which focus of the nature of the Time Series data, giving priority to lightcurves which represent the mayority of the cases, while having in mind a wider approach.

\subsection{Using a common time frame}
-To compare datasets from different missions or archives a common representation of time is needed. In order to do so we propose to map time into a pivot format. Following \cite{rots2015} we propose a set of minimum metadata to be added for serializations of Time Series (see Table~\ref{tab:metadata}).
+To compare datasets from different missions or archives a common representation of time is needed. In order to do so we propose to map time into a pivot format. Following \cite{rots2015} and \cite{std:STC} we propose a set of minimum metadata to be added for serializations of Time Series (see Table~\ref{tab:metadata}).

\begin{table}
\begin{center}
@@ -102,7 +106,7 @@
We also give some values that can be used as default in the case that some information is not known and impossible to recover. We minimize the impact of doing this by adding a systematic error to time when those values are unkown.

\subsection{Extension of ObsCore based on EPNCore}
-Some of the fields described for Time Series data have already been explecitely defined and used in the context of data discovery using ObsCore \cite{xx}, and the remaining ones have been defined in the context of EPNcore \cite{xx}. In Table~\ref{tab:obs_epn} we show the equivalence between the fields we define here and those by ObsCore and EPNcore.
+Some of the fields described for Time Series data have already been explecitely defined and used in the context of data discovery using ObsCore \cite{std:OBSCORE}, and the remaining ones have been defined in the context of EPNcore \cite{xx}. In Table~\ref{tab:obs_epn} we show the equivalence between the fields we define here and those by ObsCore and EPNcore.

\begin{table}[h!]
\begin{center}