8/4/2019 An environmental model repository: Case studies applied to Sierra Nevada LTER site

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K

EPLER

An environmental model repository: Case studies applied

to Sierra Nevada LTER site.Prez-Prez, R.; Benito, B.M.; Bonet-Garca, F.J.; Prez-Luque, A.J.iEcolab - Laboratorio de Ecologa. Centro Andaluz de Medio Ambiente. Universidad de Granada. SPAIN. ramon@ugr.es

MODISpixel

Juniper

cuadrat

Meteo

station

Municipality

in each of these

spatial entities

monitoring methods

are applied to

obtain

Real world

Raw

data

that are stored

in relational

databases,

obtaining

Queryable

information

Nosystematicanalyses,

that create

Reports,

slides,

videos, etc.

A scientific

workflow

management

system

that

creates

Pressure,

response

and state

indicators

Systematic

analyses

run through

that is converted

into useful

knowledge

through two

different routes

that is properly

documented using two

international

metadata standards

Ecologicalmetadatalanguage(EML) Inspire

directive

(ISO 19115)

Data

Knowledge

WisdomInfo

rmation

LinariaInformation System

Objectives

Development a system that we allow set themetadata for environmental models.

Delegate the execution of a workflow that implementan environmental model.

Use the raw data of an Information System. Feedback of results on environmental model to

Information System.

General

Descriptio

n

ParametersData

conexion Steps

OutputData

Metadata

on modelsKepler

A scientific workflowmanagement

500m500m

1

77980

cell_id; maximum_snow_extent; eight_day_snow_cover1; 0:missing_data; 00100011;

25: no_snow; (snow on first,200: snow; second and

sixth day)

STEP 1: generate csv (tar.gz) with data for earch cell

Web Services

Raw data handling to generate both information andknowledge is a frequent process in the LTER-sites.

We call a model to the steps required to transform

raw data.

ModeleR, is a model repository accessible from the

web, which enables the user to design, document,

manage, and execute environmental models:

Metadata about the different steps to transform thedata.

Manage the workflows of Kerpler for automatizethe proccess.

1. Introduction and Objectives

Cell_id; date; maximum_snow_extent

Spacial entity; set of cell_id

EML

STEP 2: Aggregate raw data to obtain differens indicators

entity_id; year; durationentity_id; year; start; end

CSV

SnowpackstatusinSierraNevada

OAPN

Autonomous Organismof National Parks

Rediam

Environmental Information

Network of Andalusia

8

daily every month

It processed each email and different formatsare converted to only format

Variable_id; description; code

estation_id; estation_codeEML

CSV "2011-09-21 06:10:00",3996,"PSN01",12.22,80.1,0.048"2011-09-21 06:20:00",3997,"PSN01",12.63,81.8,0.519

KEPLER

Raw

datacomingfrommeteo

rological

stationslocatedinSierraN

evada

Meteorological Stations