WARREDOC International Winter School on Data Rich Hydrology 2019

The "Data Rich Hydrology" Winter School 2019 took place in beautiful Colombella, Perugia (Italy). It was jointly organised by the Water Resources Research and Documentation Center (WARREDOC) and UNESCO World Water Assessment Program (WWAP). The WARREDOC was established at the Università per Stranieri di Perugia (UNISTRAPG) since 1985 - developing research, advanced training and scientific communication in the field of water, environment and disaster risk management.

http://warredoc.unistrapg.it/en/events/2019-winter-school/

The days were organised into a serious of lectures and lab sessions and food and accommodation were provided all at the location of the Villa Colombella, that was an extraordinary experience. We were completely immersed in this place students and lecturers altogether.

The program encompassed mainly lectures of absolute high scientific standard and well presented by the experienced and well-known lecturers.

- The Era of Data Rich Hydrology, 1st keynote lecture, by Prof. Rafael L. Bras

Prof. Bras is one of the forefathers of hydrology (Google Scholar). He gave us a history lesson of conceptual, numerical and later computational hydrology and modelling of catchments. He concluded with the outlook of what we as young hydrologists should keep striving towards to improve understanding and modelling of the hydrological cycle.

- The WWDR and SDG 6 Synthesis Report, 2nd keynote lecture, by Prof. Stefan Uhlenbrook, also head of UNESCO WWAP

- Remote sensing and data assimilation in hydrology by Prof. Fabio Castelli

- Hydrologic modelling in a data rich world by Prof. Prof Riccardo Rigon

- Citizen science and big data in hydrology by Prof. Fernando Nardi

- Beyond traditional extreme value theory: lessons learned from rainfall and hurricane intensity by Prof. Marco Marani

More topics got covered by further renowned professors, researchers and practitioners in hydrological and hydraulic modelling:

- Groundwater hydrology and hydrological process mechanics
- The water-food-energy nexus
- Modelling scaling properties of precipitation fields
- Hydrologic measurements and novel observation technologies
- Drones in Hydrology (lecture & hands on)
- Hydrological risk assessment: Return period and probability of failure
- Advances in the space-time analysis of rainfall extremes
- Data poor vs. data rich cases for flood hazard (lecture & hands on)
- Distributed Data quality and urban flood modelling uncertainty
- Stream flow measurements: ground and satellite observations
- Remote sensing data and tools to foster inland water monitoring and flood modeling

I also had the pleasure to get interviewed by research fellow and PhD student Francisco Pena, who does a radio show on Disaster Risk Reduction. We had a great chat about our ideas and views on the topics and lectures during this Winter School on Hydrology and did some brainstorming:

http://www.radiophonica.com/podcast/13941 (link to the radio show)

If you like to check out Francisco's pages: https://www.linkedin.com/in/franciscope%C3%B1a/ (LinkedIn) and and https://twitter.com/FebronioPena (Twitter)

Considerations for Data Management Plans in Research

It's grant writing time again. Actually, it's somehow always grant writing time. But even if you are currently a team member in a publicly funded research programme, you might want to consider your data management.
A recent editorial of the Nature journal had it as prime topic: "Everyone needs a data-management plan". They sound dull, but data-management plans are essential. Funders must explain why, and the ones who want to get funded, need to explain how:

https://www.nature.com/articles/d41586-018-03065-z

Keeping your research data freely available is crucial for open science — and your funding could depend on it. A related companion article describes simple steps, "Data management made simple":

https://www.nature.com/articles/d41586-018-03071-1

Robert-Jan Smits, the EU's outgoing director-general for research, science and innovation, recently been appointed the EU's special envoy on open access, tasked with helping make all publicly funded research in Europe freely available by 2020, says that this should consequently also include the data.

https://horizon-magazine.eu/article/open-access-scientific-publications-must-become-reality-2020-robert-jan-smits_en.html

Imagine if all the billions we are now putting into these expensive subscription journals could be put into research. There are already a good variety of open access repositories like Zenodo, OpenAire etc.

How to make research data publicly available and how to plan for and address it in your Data Management Plan:


EU FAIR DATA PRINCIPLES

https://eudat.eu/events/webinar/joint-eudat-openaire-webinar-%E2%80%9Chow-to-write-a-data-management-plan%E2%80%9D

1. Making data findable

Several datasets may be included. This should consider the dataset reference and name; origin and expected size of the data generated/collected; data types and formats, metadata, persistent and unique identifiers e.g., DOI

- catalogues, data citing etc

2. Making data openly accessible

This should consider which data will be made openly available and if some datasets remain closed, the reasons for not giving access; where the data and associated metadata, documentation and code are deposited (repository?); how the data can be accessed (are relevant software tools/methods provided?)

- https://www.re3data.org/

- https://www.openaire.eu/opendatapilot-repository

The Registry of Research Data Repositories provides a useful listing of repositories that you can search to find a place of deposit.

3. Making data interoperable

The Research Data Alliance provides a Metadata Standards Directory that can be searched for disciplinespecific
standards and associated tools.

- http://rd-alliance.github.io/metadata-directory/standards/

Which standard or field-specific data and metadata vocabularies and methods will be used


4. Increase data reuse

Consider what data will remain re-usable and for how long, is embargo foreseen; how the data is licensed;  data quality assurance procedures

- http://www.dcc.ac.uk/resources/how-guides/five-steps-decide-what-data-keep

More aspects:

- Allocation of resources and data security

- Note that costs related to open access to research data are eligible as part of the Horizon 2020 grant (if compliant with the Grant Agreement conditions).

Consider the estimated costs for making the project data open access and potential value of long-term data preservation; procedures for data backup and recovery; transfer of sensitive data and secure storage in repositories for long term preservation and curation

Ethical aspects

Consider whether there are any ethical or legal issues than can have an impact on data sharing. For

example, is informed consent for data sharing and long term preservation included in questionnaires

dealing with personal data?

Last but not least, don't forget to refer to other national/funder/sectorial/departmental procedures for data management that you are using / supposed to be using (if any)

DMPOnline is an online tool that can help you building your Data Management Plan. DMPonline is based on the open source DMPRoadmap codebase, which is jointly developed by the Digital Curation Centre (DCC) and the University of California Curation Center (UC3). The DCC & UC3 work closely with research funders and universities to produce a tool that generates active DMPs and caters for the whole lifecycle of a project, from bid-preparation stage through to completion.

https://dmponline.dcc.ac.uk