2019

Courses tagged with "2019"

Ocean Currents Data Quality Control and Analysis Methods

Category: 2019
The course provides students with both background reading assignments that cover the main course topics and hands-on exercises that explore the essential elements of ocean currents data quality control and analysis methods. The course assists participants in developing specific technical skills and methods for usingocean currents data.
  • Course Editor / Instructor: Greg Reed
  • Course Editor / Instructor: Charles Sun

Sistemas de Carbonatos: Documentación de conjuntos de datos, su análisis y visualización geográfica, en el marco del Objetivo de Desarrollo Sostenible 14.3 para minimizar los impactos de acidificación de los océanos

Category: 2019

El curso proporcionará las herramientas necesarias para evaluar la calidad de los datos QA/QC que permitan seleccionar sólo aquellos que cumplan con la calidad requerida para el indicador ODS 14.3.1. Aplicar las mejores prácticas para estandarizar y organizar los datos de acuerdo a la metodología 14.3.1. Identificar cuales son las herramientas de análisis más apropiadas  y utilizarlas adecuadamente. Por último los participantes aprenderán a visualizar los resultados de los análisis de manera que sean entendibles para públicos no especializados, incrementando las capacidades en los países para reportar el indicador.
  • Course Editor / Instructor: CESAR AUGUSTO BERNAL
  • Course Editor / Instructor: Angela Lopez

Project funding and management

Category: 2019

Research Design, Data Management & Data Communication in Marine Sciences



  • Course Editor / Instructor: Luiza Campos
  • Course Editor / Instructor: Rosa Maria Cañedo Apolaya
  • Course Editor / Instructor: Tim Deprez
  • Course Editor / Instructor: Marleen Roelofs
  • Course Editor / Instructor: Tim tkint
  • Course Editor / Instructor: Shanna Vanblaere

Regional Marine Observation and Quality Control

Category: 2019

This course provides an overview of regional/international marine observation, application and quality control of CTDs (Conductivity, Temperature, and Depth) and their measurements. It will provide an opportunity for participants to exchange the research progress on regional marine observation, and to learn the quality control procedures of CTDs to improve the in-situ oceanographic measurements.
  • Course Editor / Instructor: Jun Wang

Remote Sensing of Coral Reefs

Category: 2019
The course provides an introduction to the capabilities of the Remote Sensing for the coral reefs mapping. This includes practices in processing of high spatial resolution remotely sensed data for mapping the nearshore coral reef communities. After the workshop, the trainees will be able to select the most appropriate satellite data in case, and to conduct required image processes on satellite image, as well as to produce final coral maps in GIS software.
  • Course Editor / Instructor: Abdolvahab Maghsoudlou

Science Communication

Category: 2019

Research Design, Data Management & Data Communication in Marine Sciences


Module 6
  • Course Editor / Instructor: Luiza Campos
  • Course Editor / Instructor: Rosa Maria Cañedo Apolaya
  • Course Editor / Instructor: Tim Deprez
  • Course Editor / Instructor: Marleen Roelofs
  • Course Editor / Instructor: Tim tkint
  • Course Editor / Instructor: Shanna Vanblaere

Scientific Communication

Category: 2019
Marine scientist are usually evaluated by their scientific communication productivity. It is fundamental for getting PhDs, grants, projects and jobs.  Scientific Communication is the output that normally leads to a formal publication of the results, findings, observations and views arising from a scientist’s research project. Most often, the official results are published in the form of printed materials, such as academic journals. Verbal communication channels, such as personal contacts with colleagues and teachers, seminars, workshops, lectures, and conferences, are also vital to the exchange of information among scientists. These types of communications work toward the advancement of the various scientific disciplines. In this Module we address those formal channels of communication…
  • Course Editor / Instructor: Luiza Campos
  • Course Editor / Instructor: Rosa Maria Cañedo Apolaya
  • Course Editor / Instructor: Tim Deprez
  • Course Editor / Instructor: Marleen Roelofs
  • Course Editor / Instructor: Tim tkint
  • Course Editor / Instructor: Shanna Vanblaere

SeaDataCloud: 2nd Training Workshop

Category: 2019

The 2019 SeaDataCloud training session addresses the whole range of new developments recently made to improve the efficiency of the infrastructure and of the services it offers. Some topics are relevant for the technicians taking care of the availability of the data through the network. Some others will be more relevant to data managers and data analysts, for example in the perspective of a better quality control of the data we provide to our customers or in the process of making data products.

Tecnologías de Información (SIG) aplicado al medio Marino y Costero (ArcGIS)

Category: 2019

El curso ofrece una introducción para los gestores de datos marinos aplicando el Sistema de Información Geográfica (SIG) en el medio marino utilizando el software ArcGIS. Esto incluye la adquisición, procesamiento, análisis e interpretación de los datos y en la creación de productos para apoyar los programas marinos y costeros.
  • Course Editor / Instructor: Julian Pizarro

Ocean Primary Productivity

Learning outcomes By the end of this course, You will know the basics of ocean primary productivity. You will be able to explain which processes are involved in primary productivity, how it is measured and why it is important. You will learn different methods of ocean observing including in situ and remote sensing and how these observations can be used. You will gain knowledge of the advantages of open data and know where to find ocean data through the Australian Ocean Data Network or other databases and how to access these datasets. You will gain experience on how to analyse and interpret the data with options given on coding languages to achieve this. The data laboratories are developed in Matlab and either in R or Python, or both. Engagement This is a self-paced online course. Activiti…
  • Course Editor / Instructor: Eduardo Klein
  • Course Editor / Instructor: Ana Lara Lopez