#  1\. Executive Summary

The objective of this data management plan (DMP) is to detail the plan for
management of data generated and collected within the MONOCLE project. The DMP
describes the data management life cycle for all datasets collected, processed
and/or generated by the project. It covers

  * what data will be collected, processed or generated 

  

  * how the data will be handled during and after the project 

  

  * who is considered as an owner of a data set and who it is shared with 

  

  * how the sharing of the data within and outside the project is organised 

  

  * what formats, meta data and standards the data will adhere to 

  

  * how data will be curated and preserved 

  

MONOCLE data will consist of a diverse range of types and formats and
standardization of the data and data flows is one of the main project
objectives.

#  2\. Scope

This document, The Data Management Plan, is intended for internal and external
use, describing the mechanisms that MONOCLE will put in place to ensure all
public data follow the FAIR (Findable, Accessible, Interoperable, Re-usable)
data management principles. This is a living document, updated periodically to
reflect new data sets made available through MONOCLE. The current document
presents the status and planning at month six of the four-year project.

Streamlining data access and interoperability from the sensor to the user is
one of the main aspects of the MONOCLE project. Therefore, a number of related
reports which detail the methodologies developed in the project will be of
interest. At present, D5.2 outlines the data infrastructure and standards that
will be implemented in the project. D5.4 will describe the final
implementation of the data flow between MONOCLE subsystems.

#  3\. Introduction

The aim of MONOCLE is to implement enabling technologies for the deployment,
management and maintenance of sensors and sensor networks. Sound data
management is pivotal for fully realising the benefits of MONOCLE. Well
curated data will stimulate and ensure smooth collaboration between the
project partners and will allow the users to easily evaluate and put to use
the data received from the project. For dissemination and exploitation, open
access to data generated in the project will help to underpin the credibility
and stimulate uptake of MONOCLE results.

The MONOCLE project will follow the FAIR (Findable, Accessible, Interoperable,
Re-usable) data paradigm and this is reflected in the data management plan.
Data will be **F** indable through the various user applications that
interface to the data services provided by the MONOCLE back-end. A web based
geographic information system (GIS) will be publicly available with a data
search feature acting on parameter, spatial and temporal coverage or data
originator fields. Appropriate datasets will also be registered in public
archives such as ZENODO and GEOSS, this will enhance their ability to be found
and **R** e-used, even if the MONOCLE back-end should cease to operate. The
use of data services designed for system inter-operability will guarantee that
all open data within the project are widely **A** ccessible now and in future.
The user applications (web based and in the form of source code) will also
improve **A** ccessibility with focused information available, including
through intuitive tools. **I** nteroperability is also made possible through
the use of common data formats and standardised data services. For instance,
it would not matter what format the original data are stored in when requested
via a Sensor Observation Service as the response is documented and
standardised.

The DMP will be updated as a “live” document during the lifetime of the
project, with four scheduled release dates. Document D5.2 “System architecture
and standards report”, accompanies the first release of the DMP and describes
data sources and interfaces in additional detail.

#  4\. Data summary

##  Data purpose and utility

Observation of global coastal and inland water bodies with ocean-colour
satellite sensors has reached full operational potential through the latest
satellite missions in the Copernicus programme. The global societal demand for
water quality information through downstream EO services is increasing and
expanding into domains of public health, agriculture, aquaculture, energy and
food safety, drinking water, conservation of ecosystems and biodiversity
conservation, navigation and recreational use of water resources. Inland and
transitional water bodies, however, represent a staggering range of optical
and environmental diversity. A dedicated concept for EO-supporting in situ
services for optically complex waters is necessitated by the limited ability
of present in situ activities to add additional value to operational EO
missions.

To improve in situ components of the GEOSS and Copernicus services in
optically complex waters, MONOCLE will introduce new sensor technological
development across a range of innovative platforms. MONOCLE will combine high-
end reference sensors in a spatially sparse configuration with a
complementary, higher density, network of low cost sensors for smartphones and
unmanned aerial vehicles (UAV or drones).

The full MONOCLE sensor suite and the data gathered and processed with MONOCLE
sensors and processing means will serve the EO research communities for water
and atmosphere with a rapidly replenishing volume of reference observation
data, reducing both local-regional (improved atmospheric correction) and
global (improved algorithms) observation uncertainty. The MONOCLE integrated
observation service concept, particularly when integrated with EO services,
significantly lowers the technology and computing requirement for innovators
in environmental observation in general, and water quality management in
particular. This reduction is critical for uptake and engagement in developing
regions. By making both data and supporting software openly available the
project will boost innovation with app developers, environmental consultants,
data analysts and visualisation artists worldwide.

The open data strategy of MONOCLE plays a central role in opening
opportunities to the EO sector, not merely in Europe but also in supporting
downstream users and regional information providers in data-poor regions,
particularly developing countries. For the latter, MONOCLE will lower the
threshold for computational and technological capacity to actively contribute
to the global observation system

##  Data Types

MONOCLE will collect a wealth of data on water quality from multiple sources
that can be categorised as one of:

  * In-situ data, either: 

  

o Data collected by non-expert participants (e.g. citizen scientists) o Data
from automated instruments (e.g. on buoys, ships) o Data from manually
operated instruments (e.g. hand-held sensors, piloted aircraft)

  * Satellite data of inland, transitional and coastal water bodies 

  

  * Image data collected with Remotely Piloted Aircraft Systems (RPAS) 

  

  * Pre-existing data, accessed in (external) databases or directly contributed by stakeholders  Research results and derived data sets 

  

Each of these data sources has specific characteristics and challenges which
are summarised below:

###  Citizen generated data

MONOCLE will engage with groups of volunteers in citizen science campaigns
where the citizen scientists collect water quality data and submit these to
the MONOCLE system via a mobile app. A number of different parameters will be
collected by the citizen scientists, either ad-hoc or during larger campaigns.
Such campaigns can deliver a large amount of data in a fixed time period, but
are more difficult to plan as motivation of the volunteers is pivotal. A
fundamental principle of MONOCLE data management is that the apps used to
collect data will also have access to stored results, providing immediate
feedback where possible.

Citizen participation requires additional ethical considerations, which are
discussed further below.

Citizen observations are presently foreseen to be collected through the
Earthwatch Freshwater Watch app and the iSPEX app (under development). Data
exchange formats are still being decided upon, but will likely follow concepts
of interoperability using Web Feature Services (WFS) and Sensor Observation
Services (SOS), with the MONOCLE back-end communicating with the respective
data stores of iSPEX and Earthwatch. Hence, no ‘raw’ data format is currently
considered here.

The global Freshwater Watch dataset currently contains > 20,000 datasets,
where each contributor is represented as a separate dataset. For iSPEX, the
main mode of operation is foreseen to be in dedicated campaigns. Data volumes
associated with the FreshWater Watch are modest as these take the form of
forms and occasionally photos, likely to remain in the order of Gigabytes or
less. The iSPEX collects a range of smartphone camera photos, likely to range
in the order of Gigabytes. Data storage at this magnitude is not currently
seen as an issue.

###  Automated data collection

A variety of automated sensors will be deployed by project partners such as
radiometers, fluorometers and absorption meters. The sensors can be deployed
at fixed positions (e.g. on buoys, poles or jetties) or on moving platforms
(ships, RPAS). Data will in general be collected at high frequency and
immediately transmitted to the MONOCLE system. However, if deployed in remote
locations, the sensors can also collect data less frequently, and store
measurements if they are not online. Data acquisition, processing and
transmission should all be automated with these sensors as should be quality
control mechanisms. The aim of MONOCLE is to provide these sensors with
interactive interfaces so that measurements can be triggered, sensors turned
on and off or calibrations performed remotely.

During and / or following data collection, most of the optical sensors require
data processing, calibration and quality control. The intention is for these
processes to be highly automated, with suspect data flagged as not recommended
for use and to be inspected by the data creator / curator.

Where existing data stores are considered and an application programming
interface (API) is not already in place, one will be created. The SOS
interface will be preferred in the development of new communication interfaces
from individual sensors. In addition, an SOS compliant data wrapper will be
made available for legacy sensors.

Automated high-frequency data collection for the MONOCLE sensors is estimated
in the order of tens of megabytes per observation day. Transfer, storage, and
dissemination of these volumes is not currently seen as an operational issue.

###  Manual data collection

The project will collect data in field situations using handheld and manually
operated instruments. This includes new sensors intended for short-term
deployment, and high-end reference sensors operated only during validation
campaigns, following described protocols. In all cases, the measurement
records will be referenced by geo-location and UTC time-stamp and the
measurement protocol which was used. These measurements are subject to further
quality assurance (protocols) and quality control by the operators.

Manual data collection during field campaigns is estimated to deliver in the
order of several gigabytes of data per campaign. Transfer, storage, and
dissemination of these volumes is not currently seen as an operational issue.

###  Earth observation data

While the focus of MONOCLE is on providing a network of in situ observation to
support Earth observation of optical water quality, for demonstration of the
use and benefits of the MONOCLE services for Earth Observation services,
satellite-derived data will be produced within the project. For dedicated case
studies, high resolution (Sentinel-2 MSI) and medium resolution (Sentinel-3
OLCI) data will be acquired and processed into water quality information
products making use of MONOCLE in situ data for calibration and validation.

Data storage needs for EO data for the selected MONOCLE regional use cases
(Lake Balaton, Scottish Lochs, Danube Delta, Lake Tanganyika, and several
smaller sites) is in the order of hundreds of gigabytes of data per year,
which has been costed in the project budget.

###  Image data collected with Remotely Piloted Aircraft Systems (RPAS)

The purpose of data collection with RPAS is to construct mosaic maps of
waterbodies from which water quality parameters can be derived. The RPAS
systems may also serve as direct reference to satellite data, with the added
advantage of detailing fine spatial features which can explain aberrations in
processed satellite data, where fine features are not directly visible due to
a large pixel size. The raw image data are too large (and not useful) to be
disseminated beyond the data processing centres, where they are archived on
suitable storage media (e.g. tape drives). Processed parameter-specific maps
will be disseminated through the MONOCLE data back-end using machine
interfaces (WCS).

Storage and archiving needs associated with the image data are in the order of
terabytes of data and budgeted for in the project.

###  Pre-existing data

Pre-existing in situ datasets will consist of collections of optical and
biogeochemical measurements contributed by various stakeholders, either as
independent data sets where MONOCLE is given a licence to use and distribute
these, or as part of curated data bases (e.g. LIMNADES for inland water).
Access constraints will be recorded and maintained as part of the registration
of the data set in the MONOCLE back end.

Pre-existing data will also take the form of large scale satellite data
archives downloaded from space agencies (ESA and NASA), which are then used
for further processing to a usable format, in turn integrated with data from
MONOCLE sensors.

###  Research results and derived data sets

In the process of research and development, outputs will be generated in the
form of publications, presentations, tables and datasets, survey results. Such
results will be stored in the project management portal for access within the
project consortium, the size not likely to exceed 100Mb per item. Public
reports will be available also through the website. Public deliverables will
be available through the website and OpenAire. The methodology is detailed in
D9.3 “Open data repositories”.

The open access requirement for H2020 publications will be honoured through
either the green or gold open access route. Each project partner is
responsible for delivering publications through their chosen open access route
– open access publication fees are an eligible project cost. In addition,
these papers will be included in the Zenodo/OpenAire repository that has been
set up for MONOCLE.

#  5 FAIR data principles

All MONOCLE research data will be curated according to the 'FAIR' principle,
i.e. Findable, Accessible,

Interoperable and Re-usable. In the following, a short overview is given of
the building blocks to

reach this goal. It should be noted that due to the ongoing development of the
system, further detail will be provided in future releases of this document.
The following are guiding principles.

Details on each data set will be kept in a central data register, discussed
further below.

##  General data documentation and guidance

Any documentation such as measurement protocols, system descriptions and use
cases will be linked within the data register and a copy will be kept in the
MONOCLE back-end, where possible. Users of the MONOCLE front-end will be able
to access these documents when accessing a corresponding data set.

Where data sets are ‘frozen’ to create a snapshot of available data at a given
point in time, these datasets will be versioned and uploaded to public
repositories providing a digital object identifier.

By default, all data generated in MONOCLE will be openly available (see Data
Access, below), with the exception of unprocessed, uncalibrated data if these
have no value to the user. Such data will nevertheless be stored and curated.
Data contributed from external sources are the exception to this rule. In such
cases, data ownership and licensing will govern whether dissemination beyond
MONOCLE is possible.

##  Metadata

Initially the metadata profile ISO 19115 will be used to describe datasets
that are made available. As a common ontology the CF conventions
(cfconventions.org) will be followed or extended. These metadata conventions
ensure that data are identifiable, usually as part of (live) data streams,
using appropriate search terms and key words.

Additional metadata requirements to enable MONOCLE data interoperability
developments are described in D5.2 “System architecture and standards report”.
These requirements concern data ownership, licensing, access restrictions
(embargo periods), as well as geospatial parameters. The definition of the
minimum and recommended metadata for MONOCLE data sets will be refined during
the implementation of MONOCLE WP5.

A guiding principle for MONOCLE sensors and platforms is that metadata are
injected into the data flow at the point of measurement, either at the sensor
or using a dedicated sensor interface.

##  Data Access, Interoperability and respecting Intellectual Property

Processed data intended for public access and not subject to ethics
limitations will be made available through the Open Geospatial Consortium
(OGC) Sensor Observation Service (SOS), Web Feature Service (WFS) and Web
Coverage Service  1  (WCS) standards initially with other standard and bespoke
data interfaces being added as required. MONOCLE aims to apply these standards
to communication between sensors, sensors and data hubs, the MONOCLE data
back-end, front-end and user applications. Details can be found in D5.2
“System architecture and standards report”.

Data generated as part of MONOCLE will be free of cost. Data access
restrictions and intellectual property rights will, however, remain as set by
the dataset creator/owner where applicable. Unless specified, all data will be
treated as FAIR open data. In practise, the following data access levels are
foreseen:

  * open access, not requiring registration, providing access to data identified as open without license restrictions 

  

  * limited access, requiring registration, providing access to open data as well as data sets with a limited license for use (e.g. non-commercial, accrediting ownership, delayed release etc). 

  

  * restricted access, requiring registration, providing access to data owned by the user and any data sets this specific user has been granted access to. 

  

Any software tools that are required to access and, to a limited extent, make
use of the data, which are developed during MONOCLE, will be available free of
cost through software repositories such as those already set up on Zenodo and
Github (see D9.3 “Open data repositories”, for details). Essential software
tools required to make use of the data have not been defined at this point.

##  Data Sharing and Reuse

All data accessible through the MONOCLE backend data services (Sensor
Observation Service, Web Feature Service, Web Coverage Service) will be
publicly findable, with accessibility rules based on ownership and licensing
defined drawn from the metadata and data register. Any data producer that
requires data to be delayed in its release will carry that information such
that it can be securely stored and released only when appropriate. In many use
cases, however, it will be beneficial to the user to know that embargoed data
exist. Such data embargoes will feature in the extended metadata and the data
register and can take the following shapes:

  * restricted data that are identifiable by measurement parameter, and as collected within a given geographical range and time period 

  

  * restricted data identifiable as above but including exact time and location of observation 

  

  * restricted data identifiable as above, but including information about the data owner 

  

##  Data Preservation and Archiving

Data will be kept available for a minimum of three years after the end of
MONOCLE. Beyond this period, e.g. if the service should no longer be deemed
useful or sustainable, data will be archived at a secure open access location,
insofar as data licensing permits. The project intends to create links between
MONOCLE data service and large-scale public data archives (e.g. GEOSS) for
long-term accessibility.

Requests to remove a data set from the MONOCLE services can be submitted to
the Coordinator and will be handled in a manner equivalent to the GDPR for
personal data.

Within the project, Work Package 8 is dedicated to planning for long-term
sustainability and evolution of MONOCLE from a service concept into an
operational in situ service. Each of the development and innovation activities
have set deliverables that will be conditioned by the identified end users and
stakeholders through early stage trend and gap analysis. The input from the
sensor manufacturing industry (beyond those well represented in the
consortium), by primary in situ data producers (e.g. environment agencies), or
primary data consumers (e.g. EO service developers) will provide both a
cornerstone and vision for development. Commercial sensor and service
development will be explored to support a 180 degree market perspective for
MONOCLE system components and branding as a whole, exploring manufacturing
chains and economies of scale, IP licensing, and patent searches, where
applicable. Public-private partnerships and corporate sponsorships (providing
green credentials) to sustain citizen observatories and management of ‘super
sites’ will be considered in this work, delivered as an evolving exploitation
plan.

##  Data Register

The data register will be maintained as a “live” document; a snapshot will be
created for each DMP release. A template is included in the Appendix.

The data register is based upon information and restrictions supplied by the
upstream data provider matched to Horizon 2020 guidelines as below (in
_italics)_ :

  * _**Data set reference and name** _

  

_Identifier for the data set to be produced._

  * _**Data set description** _

  

_Descriptions of the data that will be generated or collected, its origin (in
case it is collected), nature and scale and to whom it could be useful, and
whether it underpins a scientific publication. Information on the existence
(or not) of similar data and the possibilities for integration and reuse._

  * _Standards and metadata_

  

_Reference to existing suitable standards of the discipline. If these do not
exist, an outline on how and what metadata will be created._

  * _Data sharing_

  

_Description of how data will be shared, including access procedures, embargo
periods (if any), outlines of technical mechanisms for dissemination and
necessary software and other tools for enabling re-use, and definition of
whether access will be widely open or restricted to specific groups.
Identification of the repository where data will be stored, if already
existing and identified, indicating in particular the type of repository
(institutional, standard repository for the discipline, etc.). In case the
dataset cannot be shared, the reasons for this should be mentioned (e.g.
ethical, rules of personal data, intellectual property, commercial, privacy-
related, securityrelated)._

  * _**Archiving and preservation (including storage and backup)** _

  

_Description of the procedures that will be put in place for long-term
preservation of the data. Indication of how long the data should be preserved,
what is its approximated end volume, what the associated costs are and how
these are planned to be covered._

#  6 Allocation of resources

The MONOCLE infrastructure has been designed as an open infrastructure from
the start, therefore the effort and cost of making the data FAIR is part of
the overall MONOCLE budget. It is the responsibility of each sensor provider
within the project to ensure that their sensors adhere to the agreed
standards, with support provided through Work Package 5 which is dedicated to
data interoperability and accessibility. The development and maintenance of
the MONOCLE backend are the responsibility of PML, who will continue to
maintain access for at least three years beyond the end of the project.

#  7 Data security

To safeguard original data, backups will be made at the site where they are
hosted. The nature of the MONOCLE data back-end is such that copies can be
stored there, but this is not a requirement – it is designed to function both
as a centralized and distributed data system.

Copies of data will, in general, not be backed-up at the MONOCLE back-end
provided that they can be retrieved again from the source. The same applies to
the use of Earth Observation and auxiliary data. Loss of such data would
potentially cause delays due to the need to download them again from the
source, but this will not be much different than restoring the data from tape
backups.

A number of data repositories have been set up to safeguard specific project
outputs, such as software, publications, sensitive data and frozen versions of
sensor data. These will be accompanied by DOIs and are described in more
detail in the document accompanying D9.3 “Open Data

Repositories”.

#  8 Ethical aspects

Ethical aspects are mainly relevant for data gathered through citizen science
initiatives. These data will be treated according to the ethics procedures
laid out in D10.1, in summary these procedures cover the following aspects:

  * Details on the procedures and criteria used to identify/recruit research participants  Details on the informed consent procedures for the participation of humans. 

  

  * Templates of the informed consent forms 

  

  * Information sheets provided to participants 

  

  * Procedures regarding the recording of imagery where humans are identifiable 

  

#  Appendix

##  Data Register Template  
  
<table>  
<tr>  
<th>

**Project**

</th>  
<th>

MONOCLE H2020 (grant 776480)

</th>  
<th>

**Start / Duration**

</th>  
<th>

1 February 2018/ 48 Months

</th> </tr>  
<tr>  
<td>

**Dissemination**

</td>  
<td>

PUBLIC

</td>  
<td>

**Nature**

</td>  
<td>

**ORDP**

</td> </tr>  
<tr>  
<td>

**Date**

</td>  
<td>

1 Aug 2018

</td>  
<td>

**Version**

</td>  
<td>

**1.0**

</td> </tr> </table>

The example shows the information collected through the data register.
Included are descriptions of the fields and an example covering Earth
observation data.  
  
<table>  
<tr>  
<th>

**Organisation**

</th>  
<th>

**Dataset reference & **

**Name**

</th>  
<th>

</th>  
<th>

**Dataset description/outline**

</th>  
<th>

**Standards & metadata **

</th> </tr>  
<tr>  
<td>

_**Name of organisation providing the data.** **Also reference any other
ownership, i.e. if you have bought commercial data and you have rights to use
but must attribute etc** _

</td>  
<td>

_A reference label. Should be unique when combined with your organisation
name._

</td>  
<td>

_Simple description of the dataset, try to include as much information as
possible on_

</td>  
<td>

_Spatial Resolution & extent Temporal resolution and extent _

</td>  
<td>

_any standardised metadata that accompanies the dataset_

</td> </tr>  
<tr>  
<td>

**PML**

based on satellite data from ESA and

NASA

</td>  
<td>

CCI_reference_chlor_a

</td>  
<td>

ESA OC-CCI archive consisting of global 4 x 4km ocean colour data.

Consisting of individual RRS bands and derived chlor_a, the dataset has per
pixel bias and rmsd uncertainty

</td>  
<td>

resolution: 4km 1997-09-04T00:00:00.000Z extent: -180,-90,180,90 to

2017-10-01T00:00:00.000Z

</td>  
<td>

Files contain CF compliant metadata but currently no xml/ISO 19115 metadata
exist

</td> </tr> </table>

Page **14** of **15**  
  
<table>  
<tr>  
<th>

**Project**

</th>  
<th>

MONOCLE H2020 (grant 776480)

</th>  
<th>

**Start / Duration**

</th>  
<th>

1 February 2018/ 48 Months

</th> </tr>  
<tr>  
<td>

**Dissemination**

</td>  
<td>

PUBLIC

</td>  
<td>

**Nature**

</td>  
<td>

**ORDP**

</td> </tr>  
<tr>  
<td>

**Date**

</td>  
<td>

1 Aug 2018

</td>  
<td>

**Version**

</td>  
<td>

**1.0**

</td> </tr> </table>  
<table>  
<tr>  
<th>

**How will data be shared**

</th>  
<th>

**software/protocol required for sharing**

</th>  
<th>

**data access policy**

**(open/locked/partial - give details, e.g. embargo time)**

</th>  
<th>

**stored in MONOCLE**

**Backend (yes/no - if no please say why/where it will be stored**

</th> </tr>  
<tr>  
<td>

_**list data services or custom websites** _

</td>  
<td>

_list the protocols available for data access_

</td>  
<td>

_data policy, such as groups that can use, whether it is only accessible to
project partners or whether there is a time based embargo_

</td>  
<td>

_whether the data will be stored in the MONOCLE back end or not. If not,
describe how data will be stored._

</td> </tr>  
<tr>  
<td>

WMS:

**_https://vortices.npm.ac.uk/thredds/wms/CCI_ALL-v3.1MONTHLY?service=WMS
&version=1.3.0&request=GetCapab _ ** **_ilities_ **

**WCS** :

**_https://vortices.npm.ac.uk/thredds/wcs/CCI_ALL-v3.1MONTHLY?service=WCS
&version=1.1.0&request=GetCapabil _ ** **_ities_ **

</td>  
<td>

OGC WCS OGC WMS

</td>  
<td>

Fully open data

</td>  
<td>

No

Archive will be proxied through the backend using the WMS/WCS links provided

</td> </tr> </table>

Page **15** of **15**