#  Executive Summary

This deliverable provides an update to the initial version of the CATALYST
Data Management Plan. It comes with the refined version of information with
respect to D7.1 and provides also an update for some of the data sets reported
in D7.1, complemented by data sets coming from simulations and external
sources (other than CATALYST pilot data centres). It also contains additional
information concerning availability, licensing and security of specific data
sets. Data sets are orchestrated with trials defined in D7.3.

This document defines data management procedures and identifies data sets
related to project pilots and specific activities. It describes the data
sources and owners in the CATALYST project, together with corresponding data
security and preservation aspects. Description of the data sharing platform,
to which some of the CATALYST data can be published, is provided. The CATALYST
Data Access Committee, defined within this Data Management Plan, will make
decisions about the use and potential sharing of specific instances of data
sets obtained during the project course. This document reflects the current
state of the project data, and we do not preclude inclusion of other data sets
or changes if such need occurs. The first results containing the use of
specific data set instances will be described in D7.4 due on M26.

This Data Management Plan follows the template provided by the European
Commission in the Participant Portal.

#  Introduction

The CATALYST project takes part in the Open Research Data Pilot. According to
obligations related to the pilot, a final version of the Data Management Plan
(DMP) is provided in this document.

The main role of the CATALYST DMP is to identify, describe, and propose
procedures to manage the data collected and processed by the CATALYST
consortium in order to realize project objectives, which are as follows: ▪
CATALYST will adapt, scale up, validate and deploy an innovative, adaptable
and flexible technological and business framework by leveraging on FP7 GEYSER
and DOLFIN TRL 4/5 results, with the aim to provide DCs with a set of TRL 6/7
enabling solutions and tools, which:

  * Use and trade the wasted DC heat to lower the energy footprint, reduce DC energy costs and create a new DC income source over longer time; 

  

  * Assess resiliency of energy supply and flexibility, against adverse climatic events or abnormal demand, trading off DC assets energy generation/consumption against local/distributed RES, energy storage and efficiency; 

  

  * Deliver energy flexibility services to the surrounding energy (power and heat) grids ecosystems; 

  

  * Exploit migration of traceable ICT-load between federated DCs, matching the IT load demands with time-varying on-site RES surplus availability or where heat generation in needed (follow the energy approach). 

  

  * Implement novel multi-carrier marketplace mechanisms (in the form of MaaS) to support novel ESCO 2.0 like business models and secure/traceable micro-contracts. 

  

▪ The CATALYST framework will be adaptable to a broad variety of DCs
categories, ranging from different DCs types (co-location, enterprise, HPC
DCs), to different geographical location, to different architectures (large
centralized versus fully decentralized micro-DCs) and energy efficiency
orientation.

To realise these objectives the CATALYST project collects information on DC
energy (electricity, heat and cooling) consumption and generation as well as
other resource usage, for example water consumption and IT systems
utilization. Based on this information CATALYST prepared a Data Management
Plan (updated version of the initial DMP) accommodating all necessary measures
for proper data handling. This DMP document defines how data collected or
generated by the CATALYST project is organised, stored and shared.

The aim is to gather data, which is valuable for technological and scientific
evaluation of the project achievements respecting privacy and legislation
(e.g. as mandated by GDPR EU Directive 2016/680 and Regulation 2016/679).
Those project data, which are allowed for open access, will be anonymised (if
needed) and stored in repositories including publishing to well-known open
platforms (OpenAIRE [1]).

##  Intended Audience

The audience of this document are all entities interested in the results of
CATALYST project, especially the delivered data sets. Thus, this document
provides relevant information for DC managers and operators as well as
external stakeholders or researchers who would like to process the data being
the output of CATALYST. Finally, all partners providing and managing the data
in the project should get familiar with the content of this document.

##  Relations to other activities

The work related to this report is correlated with activities undertaken
within other WPs and tasks, especially, the ones that result in data
provision. There is a natural dependency on the activities concerning trials
(WP7). Data sets produced by each of the trials at pilots’ side are the
subject of data management process. Additionally, there is a dependency to WP4
(providing Prediction and optimisation of DC flexibility data), WP5 (providing
Market data) and WP8 (providing Social data).

##  Document overview

This report contains a final Data Management Plans (DMP) of the CATALYST
project. It is an update of the first version of provided in M6. The main
differences include:

  * Other data sets than raw data from pilots, e.g. market or simulation data (in M6 details of such data sets were under discussion) 

  

  * More details on the use of OpenAIRE and Zenodo public repositories 

  

  * Updated data sets from pilots 

  

  * Information on sharing and preservation of specific data sets 

  

The reminder of this report is as follows:

Section 3 contains a general description of data collected and used by the
CATALYST project.

Section 4 describes how these data can be identified, shared and made
interoperable.

Section 5 explains the way of financing the DMP by the project.

Section 6 contains security and ethics considerations along with references to
other regulatory frameworks.

Section 7 introduces a template to describe CATALYST data sets along with
definitions of specific project data sets.

#  Data sources and owners in CATALYST

In this chapter, a general description of data collected and used by the
CATALYST project is introduced. The description includes information about
data sources and owners in CATALYST, basic data characteristics, and data sets
use. More detailed description of data including specific identified data sets
is provided in Section 7.

In CATALYST, data comes from 4 main types of sources:

  * Technical data related to pilots and trials executed in the project 

  

  * Other technical data (not coming from pilots), for example simulation data 

  

  * Market data – data concerning energy market (mostly simulated) 

  

  * Social Data related to people interacting with the project 

  

##  Pilots data sources

Technical data collected and processed within the project will come mostly
from CATALYST pilots. That means data collected both from real data centres
and separated testbeds accompanied by data from surrounding systems such as
renewable energy sources, energy management systems, buildings, etc.

Apart from the data that come directly from project pilots (and partners)
there are also other sources related to potential systems configurations or
markets considered within the project. Those data sets can be either generated
by simulation tools or taken from external source if available.

The purpose of these data sets collection and processing is first of all to
test and verify CATALYST platform and solutions in several different
environments. Data coming from real environments will be used to fill CATALYST
data model and based on it perform optimisations to verify potential gains.
Various data sets will be used to validate the project approach in different
settings. Re-using these data sets will help in improvements of the project
outcomes. Those data sets that can be shared and re-used will allow others to
evaluate requirements and benefits of the CATALYST platform.

The pilots that are the main source (and owners) of data collected and
processed within CATALYST are shortly summarised below. More detailed
description of pilots and corresponding trials is included in D7.3 report:
Trial set-up, test & evaluation methodology.

  * Pilot 1: ENG PSM 

  

The ENG Pilot involves the Pont Saint Martin Green DC located in the mountain
Valle d’Aosta region. It is one of the biggest Italian data centers managing
about 350 customers and hosting about 8 Petabyte of data. The PSM DC,
classified as tier IV, works as colocation DC hosting and providing most of
innovative technology services that can be tailored to current customer
processes and scenarios. In the contest of this Project, the overall DC will
be considered as testbed.

  * Pilot 2: PSNC – HPC 

  

The PSNC pilot consists of 2 parts.

The first, micro data centre laboratory enables execution of trials with a
full control of the whole DC environment and the possibility to measure the
impact on this environment. In PSNC micro data centre laboratory there are 2
racks with ~120 server nodes (some of them being low power micro-servers). The
IT equipment of the micro DC consumes approximately 10kW of power in a maximum
load and is connected to the photovoltaic system, which consists of 80 PV
panels with 20kW peak power. Therefore, it allows performing trials with
different availability/cost of energy.

The second part of the pilot consists of the data coming from the whole main
PSNC data centre and the nearby University campus to study heat re-use
scenarios. PSNC data centre is already equipped with the heat reuse system for
office heating. Within CATALYST, a study on the possibility of the DC wasted
heat re-use by the campus is being performed.

  * Pilot 3: SBP Co-location data center 

  

The SBP pilot consists of several parts. The main ones are colocation data
centre and data centre utility area.

The former one provides information on an energy reuse system, subtracting
waste heat from DC data room hot aisles, transporting heat towards a heating
system in the DC office part, using a VRF system (heat pump system). The pilot
part is based upon calculations on energy efficiency and effectiveness of this
low temperature heating system. The reduction on primary energy use (natural
gas, high temperature heating system, replaced by heat pump power demands) is
being determined by calculations. SBP data centre is equipped with a high
temperature office heating system (natural gas boilers)

The latter one provides information on an energy reuse system, subtracting
waste heat from the DC DRUPS system flywheel part towards the DRUPS generator
part, pre-heating the generator by the use of the flywheel waste heat instead
of electrical heating systems. The pilot part is based upon calculations on
waste heat reuse effectiveness on the primary energy consumption of the DRUPS
system. Detailed description of the SBP pilot is presented in D7.3

  * Pilot 4: QRN Distributed HPC 

  

For the pilot, QRN distributed DC will use a dedicated test bed representative
of the production environment. DC controller will collect all the data usually
monitored and collected during regular operation, such as heatsink and ambient
temperature. Power consumption is also an important data monitored in QRN
infrastructure.

The test bed corresponds to one flat containing 7 heaters, i.e. 21 nodes,
therefore approximately 2.5kW maximum.

##  Non-pilots technical data sources

Apart from data collected directly from infrastructure used by project DC
pilots, data related to other potential configurations (difficult to impose in
real systems), larger systems or the whole markets are used by the project.
These data can be based on the outcomes of simulations, models, etc. from
other WPs.

In particular, the simulation data complements data collected from pilots in
order to investigate various configurations and conditions. The simulation
data include the whole data centre simulation using the System of Systems
approach, Computational Fluid Dynamics (CFD) simulations, and predictions made
using machine learning methods.

For example, in order to prepare training dataset for ML algorithm, a set of
CFD simulations were performed (as described in deliverable D4.1 Smart Energy
Flexibility Modelling). The purpose was to obtain various server room unsteady
responses for diverse initial and boundary conditions. For the needs of the
study, a simplified model of a server room was utilized. The model consisted
of two server racks and raised floor cooling system. The model and all the
simulations setups were prepared with PSNC's framework dedicated for server
rooms based on OpenFOAM [ **2** ] software. Data come from simulations based
on diverse parameters: initial internal server room temperature, air
conditioner volumetric flow rate, air conditioner outlet temperature and power
consumption of both racks present in virtual room. Results are collected from
simulations covered records from virtual probes located in specific points of
the domain. It contains records of several physical variables such as
temperature, velocity, pressure and turbulence parameters. Together with
mentioned results, also configuration files of every scenario are stored to
preserve the possibility to run them for the longer time period in the future.

A definition of data sets related to simulations and predictions can be found
in Section 7.2.2.

##  Market data sources

Over the course of the project, CATALYST Marketplace data will be generated in
a simulated way using fake names and values. Specifically, the following data
will be generated:

  * general information about energy prices, market sessions, market actions, transactions, invoices; 

  

  * personal data about market participants, market operator, aggregators, DSO(s); 

  

  * user credentials, hashed using PBKDF2 algorithm (only the hashed value is preserved) 

  

A definition of a data set related to the CATALYST Marketplace can be found in
Section 7.2.4.

##  Social data sources

In addition to the technical work on trials with the use of software developed
within the project and applied to CATALYST pilots, it is foreseen that data
sets with information about people interacting with the project will be also
collected. For example, data about Green Data Centre Stakeholder Group (GDC-
SG) members, possibly with their opinions and knowledge, will be processed
within the project. Therefore, initial data set for this kind of data has been
also defined in this deliverable.

The purpose of creating these data sets is to receive feedback from relevant
stakeholders of the energy flexibility ecosystems based on data centres.
Generally, data will consists of personal data, opinions, minutes, and
questionnaires. These data sets will be used internally for steering of
project development. The conclusions coming from the analysis of the data sets
related to GDC-SG may be used as interesting source of information about
future of data centres and as a validation of applicability of the CATALYST
concepts and results.

A definition of a data set related to GDC-SG can be found in Section 7.2.3.

#  Data sharing and re-use

##  Making data findable, including provisions for metadata

Data sets are identified based on a simple taxonomy.

The _Data Source_ is defined as:

  * pilot 

  

  * external 

  

  * simulated 

  

  * other 

  

_Infrastructure type_ defines specific system, from which data is collected:

  * data centre 

  

  * colocation 

  

  * enterprise 

  

  * cloud 

  

  * HPC 

  

  * distributed 

  

  * renewable energy source, 

  

  * smart grid, ▪ others 

  

_Infrastructure purpose_ is defined as:

  * testbed, 

  

  * real production infrastructure 

  

  * mixed environment 

  

Each data set related to trials will be identified with the following
_Identifier_ : [TrialID/PilotID/InfrastructureID]. Additionally, the data sets
will be identified by time, in which the corresponding data was collected.

For those data sets that can be shared the metadata will be defined according
to requirements of sharing platforms (as defined in Section 4.2.3).

Data collected and processed within the project will be stored either using a
simple key-value format or the CATALYST data format, which is based on
extended ICT Topology Graph Database from the DOLFIN project. Hence, data will
be provided in a universal and simple way allowing its analysis and potential
re-use.

##  Data sharing

###  Data sharing procedure

Data collected, generated and processed by the CATALYST project will be
available in the following locations:

  * CATALYST website, 

  

  * Local repositories, testbeds and websites such as  _http://labee.psnc.pl_ (at PSNC), 

  

  * Storage systems for monitoring data in data centres and other infrastructure (e.g. BMS in buildings), 

  

  * External repositories such as OpenAIRE. 

  

Depending on security constraints and data reusability, selected data sets
will be moved to public repositories. To this end, restrictions on access must
be defined for each data set (see Section 7). To control this process a Data
Access Committee will be established consisting of project coordinator, data
management officer and data owner.

The sources of data sets in CATALYST along with a procedure for data sharing
decisions are illustrated in Figure 1.

Figure 1 Data set sources and procedure for data sharing decisions

Data sets will be mostly generated by pilots within WP7, however, other
sources related, for instance, to marketplaces or any other data
generated/used by other work packages are also possible as indicated in the
diagram (and summarised in Sections 3 and 7). When a data set is defined and
is going to be collected and/or used in the project the data owner or WP
leader must inform the Data Management Officer. The Data Access Committee
decides whether and how this data set will be shared. If there are
restrictions due to internal policies of data owners decision about denying
access can be taken. The Data Access Committee may also decide to pre-process
data before sharing, for example, performing anonymization or restricting
access to only parts of data. For shared data, license and access details will
be defined (e.g. location, identifiers). Depending on the volume, usefulness
and time when information is outdated specific sets can be accessible from
local repositories or public open repositories such as OpenAIRE [ **3** ].

###  Data sets availability

The following table summarizes the availability of particular data sets:

Table 1 - Available data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

Owner

</th>  
<th>

Accessibility

</th>  
<th>

Where

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

Micro data centre

</td>  
<td>

PSNC

</td>  
<td>

Public (for

selected data)

</td>  
<td>

Local (  _https://labee.psnc.pl/_ ,  for registered users) and public (Zenodo)
repositories (for selected data)

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

Photovoltaic system

</td>  
<td>

PSNC

</td>  
<td>

Public (for

selected data)

</td>  
<td>

Local (  _https://labee.psnc.pl/_ ,  for registered users) and public (Zenodo)
repositories (for selected data)

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

Main data centre

</td>  
<td>

PSNC

</td>  
<td>

Only within the project

</td>  
<td>

Local repositories

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

PUT buildings

</td>  
<td>

PUT

</td>  
<td>

Only within the project (PSNC)

</td>  
<td>

Local repositories

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

Distributed DC Testbed

</td>  
<td>

QRN

</td>  
<td>

Only within the project

</td>  
<td>

Local repositories

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

DC CFD simulations

</td>  
<td>

PSNC

</td>  
<td>

Public

</td>  
<td>

Local (  _https://labee.psnc.pl/_ ,  for registered users) and public (Zenodo)
repositories (for selected data)

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

GDC-SG

</td>  
<td>

GIT

</td>  
<td>

Only within the project

</td>  
<td>

Local repositories

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

PSM

</td>  
<td>

ENG

</td>  
<td>

Only within the project

</td>  
<td>

Local repositories

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

Prediction and optimisation of DC flexibility

</td>  
<td>

TUC

</td>  
<td>

Public

</td>  
<td>

Local repositories (for selected data) and public repositories (for selected
data)

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

Waste heat reuse offices

</td>  
<td>

SBP

</td>  
<td>

Public

</td>  
<td>

Local repositories

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

Waste heat reuse utilities

</td>  
<td>

SBP

</td>  
<td>

Public

</td>  
<td>

Local repositories

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

Comparison UPS systems

</td>  
<td>

SBP

</td>  
<td>

Public

</td>  
<td>

Local repositories

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

Drinking Water Cooling

</td>  
<td>

SBP

</td>  
<td>

Public

</td>  
<td>

Local repositories

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

Electricity Flexibility Emergency Power pool: 1: Agreement

</td>  
<td>

SBP / ALD

</td>  
<td>

Public

</td>  
<td>

Local repositories

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

Electricity Flexibility Emergency Power pool: 2:

test data

</td>  
<td>

SBP / ALD

</td>  
<td>

Only within the project

</td>  
<td>

Local repositories

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

IT load migration

</td>  
<td>

SBP / QRN

</td>  
<td>

Only within the project

</td>  
<td>

Local repositories

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

###  Sharing CATALYST data sets in public repositories

Data generated and gathered within the CATALYST project, that meets data
protection requirements, will be provided to the public access using OpenAIRE
[ **3** ].

OpenAIRE stands for Open Access Infrastructure for Research in Europe. It
started as a project and, nowadays, become an organization that aims at
exposing entities supporting Open Access policies. It consists of a
decentralized network of data sources including data and literature
repositories, publishers and research information systems. By these means, it
facilitates combining data and publications together with the corresponding
projects.

OpenAIRE is not a repository itself. Instead, it harnesses the contents of
various (compatible) publication and data repositories and exposures
corresponding metadata. Nevertheless, it supports, to a certain degree,
sharing and publishing data, by guiding the user through this process. It
enables selecting a proper repository according to the domain of the data or
suggesting repository related to the data provider’s institution. The third
option is to use Zenodo repository [ **4** ] that originated from OpenAIRE.

OpenAIRE delivers also the content provider management system. It does not
support repository creation, but similarly to data sharing, it suggests
repositories that could be linked to OpenAIRE. These repositories have to be
prior registered in OpenDOAR (in case of literature ones) or in re3data
registry [ **5** ] (in case of data repositories).

As mentioned, the system is designed towards proper project metadata
management and labelling. It focuses on managing the metadata but not the
data. To facilitate this, it provides a dedicate API allowing developers to
access the metadata information space. Bulk access is available via Open
Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). There is also
a possibility to use HTTP API for selective access to publications, data,
software and projects. In order to work with OpenAIRE, there is account (and
thus registration) needed.

Zenodo, offered as a solution for data sharing by OpenAIRE, is a general-
purpose open-access repository operated by CERN [ **6** ] and developed under
the OpenAIRE program. It is already registered within the re3data registry,
and thus can be seamlessly and easily used as a repository accessible via
OpenAIRE. Publishing data with Zenodo is pretty straightforward. Zenodo’s
system offers easy drag and drop mechanism. In this way publications,
datasets, images, software, presentations, etc. can be uploaded. The only
restriction is the size of the data, which is limited to 50 GB per data set.
Zenodo offers a possibility to define the basic characteristic of the uploaded
data like:

  * Title, 

  

  * Authors, 

  

  * Publication Data, 

  

  * Short Description, ▪ Keywords, 

  

  * Digital Object Identifier 

  

Moreover, it offers a fine-grained definition of access rights:

  * Open Access 

  

  * Embargoed Access 

  

  * Restricted Access ▪ Closed Access 

  

together with corresponding data licenses.

Last but not least, related projects and grants can be defined. Of course,
there is a lot of additional information that can be assigned to each of the
uploaded data set. Their full list can be seen in [ **7** ].

Apart from that Zenodo, can be integrated with popular services like Dropbox -
for uploading files or GitHub - for code sharing.

Zenodo comes with two APIs for managing the data: REST API that currently
supports only upload and publishing; and OAI-PMH that allows the user to
harvest entire repository via the Open Archives. In order to work with Zenodo,
one should create an account in advanced.

All the aforementioned features make Zenodo a nice alternative repository in
case of lack of data storage infrastructure or proper, re3data registered,
repository on particular project’s participants sites.

To be registered in re3data registry, a research data repository has to meet
the following requirements [ **5** ]:

  * must be run by a legal entity, such as a sustainable institution (e.g. library, university) 

  

  * must clarify access conditions to the data and repository as well as the terms of use 

  

  * must be focused on research data 

  

Figure 2 summarizes the procedure of sharing data with OpenAIRE

Figure 2: Sharing data in public repositories using OpenAIRE

Using the Zenodo platform as a repository, it is also possible to define the
set of aforementioned metadata that can be later on use to find the given
publication/data set. The following information is especially relevant from
the perspective of CATALYST project.

  * Data type: publication, data set, presentation, etc 

  

  * Publication date – date of the publication (Zenodo does not offer the possibility to define the date range in which the data was gathered – this could be a part of Description section) 

  

  * Title – identifying the data scope 

  

  * Authors – authors/providers of the data 

  

  * Description – description of the data (due to the general purpose of the Zenodo repository, and thus, the lack of specified metadata, this section should provide a detailed description of the data) 

  

  * Language – language in which the data is provided 

  

  * Keywords – keywords identifying the data (similarly to the description - this section specify the information typical for the given data) 

  

  * Access rights – access rights to the data 

  

  * License – license under which the data will be available 

  

  * Grant/project – reference to the CATALYST project, grant number 

  

  * Contributors – other people who contributed to the given data (in case of collaboration with other projects) 

  

  * References – references to papers/presentations in which the data was mentioned 

  

##  Making data interoperable

If possible, CATALYST will follow existing good practises, standards and data
formats to make data interoperable and ensure compliance.

Plan towards interoperability will include:

  * Application of recognized CATALYST good practices, e.g.: o Generic format used by DOLFIN to store measurement data – flexible enough for various data description 

    * Data model based on GEYSER experiences to describe the data centre along with its ecosystem (interfaces to marketplaces, etc.) for the CATALYST optimiser 

  

    * Taxonomy for describing DC applied in CATALYST – based on existing classifications of DC, their subsystems, etc. 

  

    * Taking into consideration a compliance with relevant standards and regulations when establishing measurement procedures, data naming, etc., 

  

  

  * Applying Green Grid PUE monitoring guidelines [8] when performing energy measurements and calculating PUE (standard PUE – EN50600-4-2) 

  

  * If calculating the Renewable Energy Factor (REF) referring to standard EN50600-4-3 [9] 

  

  * Checking if applied strategies are related to best practices defined in the EU Code of Conduct (and CLC/TR 50600-99-1 standard to which these practices have been incorporated) [10] 

  

  * Referring to ASHRAE TC 9.9 2015 for thermal guidelines and server types [10] 

  

  * Looking at other EN50600 standard series, e.g. EN50600-4-4 and EN50600-4-5 if KPIs such as IT Equipment Energy Efficiency and Energy Utilisation for Servers must be monitored [9] 

  

  * Publishing the data in public repositories with well defined metadata, standards of storing the data and access interfaces 

  

##  Increase data re-use (through clarifying licences)

The data management plan establishes how licensing will be addressed in the
project lifetime according to the identified data set. At this stage of the
project, we initially classified the project data sets and provided the
positioning of the project in reference to licensing. In the frame of the
project, three main categories of data are identified as follows:

  * Project data sets for dissemination: this kind of data will be open access by default in order to validate scientific publications; this can include some of data coming from pilots, simulations and results of studies. ▪ Data sets produced by work packages: this kind of data will be reused in accordance with the specific WP policy. For example some data created and stored during the project can be for internal management and communication within the consortium. Some other can be shared outside the project and useable by third parties. 

  

  * Technical data sets: those data are about the Pilots and are mainly about pilots measurement collected within the project timeframe. Simulation data are considered as well. General assumptions regarding these data sets are as follows: 

    * Data sets that enclose personal data cannot be shared as-is for privacy reasons. This is the case of QRN DC which handle multiple radiators deployed in residential/office buildings. Even if these data cannot be tied to one person or household, they have to be treated cautiously; the QRN data set will be shared only within the CATALYST project members upon request. 

  

    * Data sets that require aggregation or anonymizing for security or commercial reasons prior to release. This is the case of PSM DC: raw data can be shared only for the objective of the trial and in the scope of the project; otherwise aggregated data, the final result of the CATALYST solution exploited in the PSM Pilot, can be shared not only for the objective of the trial. o Data sets that can be shared without any restriction (but according to the defined license): this is the case of PSNC Micro data centre testbed 

  

    * Data sets that cannot be shared outside the project: this is the case of PSNC DC related to the High Performance Computing centre, SBP DC related to the collocation data centre, and data from BMS of Poznan University of Technology (PUT) buildings. 

  

  

More specific licenses/restrictions are defined per each data set below.

###  Pilot data

  * Pilot 1: ENG PSM 

  

Table 2 - ENG PSM data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

Owner

</th>  
<th>

Restrictions

</th>  
<th>

License

</th>  
<th>

Availability after the end of the project

</th>  
<th>

Justification (if needed)

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

Pilot 1: ENG PSM

</td>  
<td>

ENG

</td>  
<td>

Proprietary data. Not public

</td>  
<td>

Use in the project

</td>  
<td>

No

</td>  
<td>

Customer data

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

  * Pilot 2: PSNC – HPC 

  

Table 3 - PSNC - HPC data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

Owner

</th>  
<th>

Restrictions

</th>  
<th>

License

</th>  
<th>

Availability after the end of the project

</th>  
<th>

Justification (if needed)

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

Micro data

centre

</td>  
<td>

PSNC

</td>  
<td>

Shared

</td>  
<td>

Open Data

Commons

(ODC-BY)

</td>  
<td>

Yes (selected sets)

</td>  
<td>

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

Photovoltaic system

</td>  
<td>

PSNC

</td>  
<td>

Sharing subset of data

</td>  
<td>

Open Data

Commons

(ODC-BY)

</td>  
<td>

Yes (subsets)

</td>  
<td>

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

Main data

centre

</td>  
<td>

PSNC

</td>  
<td>

Critical data. Not public

</td>  
<td>

Use in

project

</td>  
<td>

the

</td>  
<td>

No

</td>  
<td>

Internal DC

data

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

PUT buildings

</td>  
<td>

PUT

</td>  
<td>

Proprietary data. Not public

</td>  
<td>

Use in

project

</td>  
<td>

the

</td>  
<td>

No

</td>  
<td>

Data owned by PUT

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

  * Pilot 3: SBP Co-location data center 

  

Table 4 - SBP data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

Owner

</th>  
<th>

Restrictions

</th>  
<th>

License

</th>  
<th>

Availability after the end of the project

</th>  
<th>

Justification (if needed)

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

Waste heat

reuse offices

</td>  
<td>

SBP

</td>  
<td>

Shared

</td>  
<td>

Open Data

</td>  
<td>

Yes, calculation data

</td>  
<td>

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

Waste heat

reuse utilities

</td>  
<td>

SBP

</td>  
<td>

Shared

</td>  
<td>

Open Data

</td>  
<td>

Yes, calculation data

</td>  
<td>

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

Comparison UPS systems

</td>  
<td>

SBP

</td>  
<td>

Shared

</td>  
<td>

Open Data

</td>  
<td>

Yes, overview data

</td>  
<td>

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

Drinking Water Cooling

</td>  
<td>

SBP

</td>  
<td>

Shared

</td>  
<td>

Open Data

</td>  
<td>

Yes, calculation data

</td>  
<td>

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

Electricity

Flexibility

Emergency Power pool: 1: Agreement

</td>  
<td>

SBP / ALD

</td>  
<td>

Shared

(anonymized)

</td>  
<td>

Open Data

</td>  
<td>

Yes, text

document

</td>  
<td>

Anonymization

for

confidentiality reason

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

Electricity

Flexibility

Emergency Power pool: 2:

test data

</td>  
<td>

SBP / ALD

</td>  
<td>

Critical data, Not public

</td>  
<td>

Use in the project (basic data)

</td>  
<td>

No

</td>  
<td>

DC data,

confidentiality

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

IT load migration (pilot continuity pending)

</td>  
<td>

SBP / QRN

</td>  
<td>

Critical data, Not public

</td>  
<td>

Use in the project (basic data)

</td>  
<td>

No

</td>  
<td>

DC data,

confidentiality

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

  * Pilot 4: QRN Distributed HPC 

  

Table 5 - QRN data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

</th>  
<th>

Owner

</th>  
<th>

Restrictions

</th>  
<th>

License

</th>  
<th>

Availability after the end of the project

</th>  
<th>

Justification needed)

</th>  
<th>

(if

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

Distributed Testbed

</td>  
<td>

DC

</td>  
<td>

QRN

</td>  
<td>

Proprietary

data. Not

public

</td>  
<td>

Use in the project

</td>  
<td>

No

</td>  
<td>

Personal data

</td>  
<td>

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

###  Non-pilots data

Table 6 - Non-pilots data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

Owner

</th>  
<th>

Restrictions

</th>  
<th>

License

</th>  
<th>

Availability after the end of the project

</th>  
<th>

Justification (if needed)

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

DC CFD

simulations

</td>  
<td>

PSNC

</td>  
<td>

Shared

</td>  
<td>

Open Data

Commons

(ODC-BY)

</td>  
<td>

Yes (selected

sets)

</td>  
<td>

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

Prediction and optimisation of DC flexibility

</td>  
<td>

TUC

</td>  
<td>

Shared

</td>  
<td>

Open Data

Commons

(ODC-BY)

</td>  
<td>

Yes (selected

sets)

</td>  
<td>

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

###  Social data

Table 7 - Social data sets  
  
<table>  
<tr>  
<th>

Data set

</th>  
<th>

Owner

</th>  
<th>

Restrictions

</th>  
<th>

License

</th>  
<th>

Availability after the end of the project

</th>  
<th>

Justification (if needed)

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

GDC-SG

</td>  
<td>

GIT

</td>  
<td>

Public information only after members have

granted their permission

</td>  
<td>

Use in the project

</td>  
<td>

Taken care by

GDC-SG

</td>  
<td>

Personal data

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

###  Market data

Simulated Marketplace data will be used only for the CATALYST experimentation
objective and in the scope of the project. Access to marketplace data
generated during the marketplace instance operation is subject to
authorization control and permission rights granted per user group, when
attempted both programmatically or through the marketplace user interface.
User credentials are hashed using PBKDF2 algorithm.

#  Allocation of resources

##  Allocation of resources within project lifetime

Allocation of resources is about costs for making research data findable,
accessible, interoperable and reusable (FAIR) in the project.

These costs can be different according to the specific data set that is
considered.

Regarding the provision of DMP, the related costs involves WP7 - _Trials &
Performance Validation _ since Task 7.1 – _Specification of trials and
evaluation methodology_ is responsible for the preparation of data management
plan. These costs are covered by budget associated to WP7.

PSNC as WP7 leader is responsible along with other WP7 (especially ENG)
partners for the overall data management process.

Resources can be also related to the long-term preservation of data. How those
data will be kept for specific data sets is discussed in Section 5.2. However,
it can be assumed that storage of pilot-related data sets and potential access
beyond the project lifetime will be covered by partner formally responsible of
CATALYST pilots.

##  Covering long-term preservation of data

In this section the identification of resources for storage of pilot-related
data sets (and others) and potential access beyond the project lifetime is
discussed. Information for each data set owner are summarised below. _PSNC_

Subsets of data sets concerning PSNC’s micro data centre, photovoltaic system,
and simulation data will be stored after the end of the project according to
the definition in Section 4.4. Financing of these data storage will be by PSNC
through the PSNC micro data centre laboratory and LABEE portal (
_http://labee.psnc.pl_ )  and other projects that make use of either this
environment or specific data set available at this portal. Additionally, the
most important data sets considered for public sharing will be shared via
OpenAIRE/Zenodo.

####  _QRN_

Data corresponding to QRN distributed operation is stored into production
database for internal purposes.

Therefore these data will be stored on a long-term basis by QRN and thus we’ll
be retrievable after the project. Data created during the project for the
project needs will be stored on an internal repository and be stored according
the project requirements.

####  _GIT_

Data related to GDC-SG members will be handled by GDC-SG after the project
ends. The core members of the group will be responsible for defining
organizational structure being in charge for storing and sharing the _data_ .

####  _TUC_

The data sets concerning the thermal ad energy prediction and flexibility
optimization will be maintained by TUC team and stored on distributed systems
research laboratory secured data stage servers as well as in specific
platforms for public sharing via OpenAIRE.

####  _ENG_

Data will be preserved in the DC during the project and for a period of 1 year
after the end of the Project. The associated cost will be covered by ENG.

#  Data security and Ethical aspects

##  Data security

Data security is about the provision of data protection in the project
lifetime. The aim of DMP is to provide information about data recovery, secure
storage and transfer of sensitive data as well.

The DC pilots-related data sets will be stored in pilot DCs where there is
high level of security and redundancy to prevent failures and data losses.

Certified repositories will be taken into account for project data that has to
be curated and preserved for long time. Some repository like OpenAIRE will be
considered to share data outside the project.

More detailed information (concerning the security level at data set owners
data storage, recover possibilities, etc.) is provided according to the
specific data set below.

###  ENG-PSM

Measurement from PSM DC are stored at PSM side. Only users belonging to the
Project consortium could access to testbed measurements. These data will be
stored on the CATALYST Data Base that will be deployed in PSM in a server
accessible only through a VPN; only authenticated users will access to this
DB. All security mechanisms, applied to the overall DC, are therefore extended
to the PSM testbed.

###  PSNC

Measurements from PSNC data centre are stored at PSNC side, in the BMS
providing secure storage (without external access) and data replication.
Measurements from PSNC testbed will be available for the registered users
(registration is provided on demand). To increase the security, entrance to
the testbed is possible via a single access point via SSH (using Key-Based
authentication). PSNC will also benefit from the data coming form Poznan
University of Technology, which also utilizes BMS that ensures secure storage
and data replication.

###  SBP

Measurements from SBP data centre are stored inside BMS responsible for
ensuring proper security level.

###  QRN

As personal data is involved when it comes to QRN distributed DCs, data is
pseudonymised to avoid any risks in case of data leakage. Data is stored in a
secure database hosted in a “regular” DC.

###  TUC

The data will be stored in a secured data storage hosted in a cloud DC. The
over-riding priority will be to assure data confidentiality by making sure
that no identifiable information is made available. The security and
confidentiality are achieved by building appropriate access rights, encryption
and anonymization into the core data models to be provided.

###  GIT

Data at GIT’s is stored within the organization's team repository. Default
security policies are used for each of the systems.

###  Data outside the CATALYST project

Data that will be shared using Zenodo repository is stored in CERN Data Center
[ **11** ]. According to Zenodo, both data files and metadata are kept in
multiple online and independent replicas. Moreover, CERN guarantees to collect
and store “100s of PBs of LHC data as it grows over the next 20 years”
together with maintaining their data centre. In case of closing the operations
by Zenodo, they ensure to migrate all content to other repositories. Zenodo’s
Terms Of Use makes the uploader responsible for providing content that
complies privacy, data protection and intellectual property rights.

##  Ethical aspects

Ethical aspects mainly concern personal data. If this data has to be shared,
this aspect has to be taken into account. Indeed, as stated in chapter 5 of
CATALYST Description of Action (DoA), the Consortium is aware of EU and
national legislation and policies referring to protecting personal data and
privacy, especially in the context of smart grid. The CATALYST consortium is
committed to taking all necessary measures to ensure that all project
activities comply with the European Chart of Fundamental rights and all data
protection relevant EU regulations, soft – law, standardisation and policy
initiatives.

To ensure the appropriate protection of data sets, CATALYST will be tracing
and checking the relevance for CATALYST data sets. Moreover, CATALYST will
adopt, if needed, at least the following procedures/regulations:

  * GDPR (General Data Protection Regulation) for data protection 

  

  * Data protection regulation framework in smart energy grids 

  

  * The Regulation (EU) 2016/679 on the protection [12] of natural persons with regard to the processing of personal data and on the free movement of such data 

  

  * The Directive (EU) 2016/680 [13] on the protection of natural persons with regard to the processing of personal data by competent authorities for the purposes of the prevention, investigation, detection or prosecution of criminal offences 

  

  * Ad-hoc frameworks on data privacy in smart grids, including Data Protection Impact Assessment (DPIA) [14]. 

  

  * Data Protection Impact Assessment Template [14] (supported by Commission Recommendation 

  

2014/724/EU)

Moreover, the project will assure the respect of personal data protection
through a dedicated Data Protection Officer (DPO). It works at project level
in order to ensure that an appropriate data management plan is developed and
used to protect the privacy of data. As reported in the CATALYST DoA, section
3.2.1.1 Project Management Structure, the role of the CATALYST DPO will be
compliant to the GDPR (EU 2016/679, EU 2016/680). The CATALYST DPO is Dr.
Ariel Oleksiak (PSNC).

Focusing on technical data sets collected so far, in some cases the pilot data
sets can contain “personal data” like for the QRN pilot where data come from
owners of heaters. As anticipated in Section 6.1.4, data is pseudonymised to
avoid any risks in case of data leakage. Proper information about processing
of data collected from heaters is provided by QRN to users, according to GDPR
regulations.

Regarding Social data sets, potential questionnaires to collect data from GDC-
SG members may contain personal data and will include information about goals
and rules related to processing these data.

#  Data sets

##  Data set structure

The template used to describe data sets has been based on the guidelines from
EC enhanced by (i) specific parameters related to CATALYST needs (such as
Trial ID) and (ii) additional guidelines related to given parts (e.g. type of
data centre in the case of CATALYST DC pilots).

The template to describe data sets is given below:

Table 8 - Data sets template  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Who is the researcher responsible for this data set?

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

Collecting period

</td>  
<td>

Timeframe within which data were collected

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

Trial ID

</td>  
<td>

Identifier of the CATALYST trial

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

Data set reference and name

</td>  
<td>

What data are collected and how are they named?

  * Type of infrastructure/system 

  

(colocation/enterprise/cloud/ HPC data centre, renewable energy source, smart
grid, etc.),

  * Purpose of infrastructure (testbed, real production infrastructure or mix), 

  

  * Identifier: [TrialID/PilotID/InfrastructureID] 

  

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

Data set description

</td>  
<td>

Description of the data, the origin, nature and scale and for what purpose
they were generated. Type of data, e.g.

  * Power/energy measurements: of servers, cooling systems, other devices 

  

  * Energy production and supply: RES production, heat re-used, 

  

  * Environmental data: temperatures in server rooms, humidity, flow, etc. 

  

  * IT monitoring: utilization of servers, VM management, 

  

  * Energy market: prices of energy 

  

  * Other Source 

  

  * Origin: laboratory/infrastructure measurements, experiments, simulations, etc. 

  

  * Specific subset of infrastructure Volume 

  

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

</th>  
<th>

  * Total volume of data, number of files, etc. Data and file formats ▪ Format of data 

  

  * Standards, open/common formats used 

  

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

Standards and metadata

</td>  
<td>

Are there any suitable standards and what metadata will be crated?

Metadata to identify data set

  * Identification of trial, pilot and specific part of infrastructure (or other systems and sources used) for which this data set has been prepared and/or used 

  

More advanced metadata to (possibly to be synchronised with a CATALYST data
model)

  * help to understand and interpret data ▪ provide details about experiment setup (who, when, in which conditions, tools, versions, etc.) ▪ help identify and discover new data 

  

Any community standards used to enable interoperability

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

Data sharing

</td>  
<td>

Describe if and how the data will be shared (access, procedure, embargo
periods, technical mechanisms, necessary software and tools, repositories). In
case the data cannot be shared describe the reason. Which data will be shared?

  * Final result? ▪ Intermediate data? 

  

Data protection

  * Who will have access? ▪ Is there a need to preprocess the data, e.g. 

  

anonymize?

  * What are constraints and reasons of limited access 

  

if this is the case

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

Archiving and preservation

</td>  
<td>

Where and how long will the data be preserved? What is the approximated end
volume, what are the associated costs and how will they be covered?

Which data should/needs to be preserved?

▪ What has to be kept e.g. data underlying publications?

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

</td>  
<td>

▪

</td>  
<td>

What can’t be recreated e.g. environmental recordings?

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

</td>  
<td>

▪

</td>  
<td>

What is potentially useful to others?

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

</td>  
<td>

For how long?

What is the final size of data?

Where it can be stored?

What is the cost and who will pay for it?

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

##  Data sets

This section contains the description of data sets related to each pilot. It
provides corresponding updates for the data sets with respect to the
information included in D7.1. For individual data sets their description
remained the same as in D7.1

###  Pilots data sets

Pilot 1: ENG PSM  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Marilena Lazzaro

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

Collecting period

</td>  
<td>

The data set will be collected in the timeframe within the application of use
cases in the PSM Pilot: M16 (January 2019) – M36 (September 2020).

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

Trial ID

</td>  
<td>

PSM_DC_TC_1

PSM_DC_TC_2

PSM_DC_TC_3

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

Data set reference and name

</td>  
<td>

_[TrialID/PSM]_

▪ colocation data centre

• Mix: measurement data from the real production DC infrastructure; only data
relevant for the CATALYST trials will be part of the testbed.

Identifier: TrialID/PSM/ColocationDC

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

Data set description

</td>  
<td>

Measurement data from both facilities and IT Type of data:

  * Power/energy measurements: Electrical consumption of cooling devices, Main incomer, Server room incomer, UPS. 

  

  * Energy production and supply: geothermal system is used for cooling the DC (bunkers and offices), heat recovery system to supply heat to office buildings. 

  

  * Environmental data: temperatures in server rooms, Chilled air/water flow rate, Relative/Absolute humidity of the server room, Ambient air temperature. 

  

▪ IT monitoring: CPU utilization (%) of servers, Storage utilisation (%),
Network utilisation (%) Source

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

</td>  
<td>

  * Specific subset of DC infrastructure measurements 

  

Volume

  * From tens of MB to GB depending on the time experimentation will last and on the data that will be necessary for the trials 

  

Data and file formats

  * Format of data monitored through the Honeywell OPC Server Data Access meets the specification of the OPC Data Access Standard version 1.0a or 2.0. This data are the Power/energy measurements and the Environmental data. 

  

Format of IT monitoring data depends on the specific tool that is used like
NAGIOS for Storage utilisation (%) and ORION for Network utilisation (%).

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

Standards and metadata

</td>  
<td>

Data is identified by a related timeframe. Within CATALYST Trial ID will be
used to identify data sets. Other metadata will include information about data
centre type and components as defined in Section

4.1.

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

Data sharing

</td>  
<td>

Row Data from PSM DC can be shared only for the trial’s objective and in the
scope of the project. How this will be done is under evaluation according to
the specific use cases to be demonstrated. The limited access to this data is
due to the internal policy of PSM DC.

Aggregated Data, the final result of the PSM Pilot, can be shared not only for
the objective of the trial.

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

Archiving and preservation

</td>  
<td>

Currently the PSM DC allows the data achieving according to the specific
contract agreed upon the customer. These data are mainly related to alarm
events and are stored as .data files.

Regarding the data set described in this template, if historical data are
needed for the purpose of the trial, the achieving mechanism already in place
in the DC will be properly extended to the PSM pilot. Data will be preserved
in the DC during the Project and for a period of 1 year after the end of the
Project.

The associated cost will be covered by ENG.

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

Pilot 2: PSNC – HPC

PSNC pilot consists of several parts. First of all, Poznan Supercomputing and
Networking Center operates High Performance Computing (HPC) Center mostly
addressed (not only though) to scientific users. In addition to the
operational DC PSNC provide access a testbed of the energy-efficient
technologies laboratory. Data will be complemented by detailed monitoring of
the photovoltaic system, which can be connected to the testbed.

_Micro data centre testbed_  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Ariel Oleksiak

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

Collecting period

</td>  
<td>

Selected periods from October 2017 to September 2020

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

Trial ID

</td>  
<td>

PSNC_DC_TC_1

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

Data set reference and name

</td>  
<td>

_[TrialID/PSNC/MicroDC]_

• PSNC micro data centre laboratory

Laboratory/testbed used in CATALYST trials

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

Data set description

</td>  
<td>

Measurement data from both facilities and IT. Data from around 20-100 server
nodes with power usage in order of 3-10kW. Servers can be partially powered by
energy produced by photovoltaic system.

Type of data:

  * Power usage of servers and cooling; 

  

  * Utilisation of servers; 

  

  * Temperature of servers, room and coolant (for 

  

direct liquid cooling);

  * if needed other statistics related to workload execution (e.g. OpenStack, SLURM) 

  

Source

  * Micro data centre laboratory – a testbed at which experiments related to CATALYST trials can be executed 

  

Volume

  * Currently the size of data is in the order of 30GB per one month and more than 70GB per year 

  

(older data is stored with lower sampling rate) Data and file formats

▪ Mostly key-value pairs for various parameters. Data can be easily translated
into the CATALYST format (partially done for monitoring in DOLFIN).

Purpose

Experiments with data centres, analysis of trial results

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

Standards and metadata

</td>  
<td>

Data is identified by a related timeframe. Within CATALYST Trial ID will be
used to identify data sets.

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

Data sharing

</td>  
<td>

Data from PSNC micro data centre can be shared.

Currently are stored in file-based database at PSNC. Intermediate detailed
data can be stored in relational databases.

Data is partially available to registered users via _
https://labee.man.poznan.pl.  _ Sharing of data subsets via OpenAIRE
repository is considered.

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

Archiving and preservation

</td>  
<td>

Measurements from micro data centre are currently stored at PSNC for at least
period of 1 year. The total volume collected during 1 year currently (using
RRD database that automatically decrease size of older data) is equal to 77GB.
If the whole high frequency data is

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

</td>  
<td>

stored then, depending on trials timeframe, the total volume can reach up to
0.5TB.

This data set can demonstrate details of a trial in which certain results were
achieved.

These data can be stored at PSNC.

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

_Photovoltaic system_  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Ariel Oleksiak

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

Collecting period

</td>  
<td>

Selected periods from October 2017 to September 2020

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

Trial ID

</td>  
<td>

PSNC_DC_TC_1

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

Data set reference and name

</td>  
<td>

_[TrialID/PSNC/RES-PV]_

PSNC photovoltaic system energy production

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

Data set description

</td>  
<td>

Monitored energy generation of the PSNC photovoltaic system. The data come
from 80 solar modules that can generate up to 20kW in peak and energy storage
(leadacid batteries of 75 kWh capacity).

Type of data:

  * Values of energy produced in time 

  

  * Other parameters: P, S, Q x4, day yield, grid frequency, grid voltage x3, total yield 

  

  * Data collected every 5s 

  

Source

  * PSNC photovoltaic system (inverters, batteries) 

  

Volume

  * Currently the size of data is in the order of 25MB per one month and around 50MB per year (older data is stored with lower sampling rate) but may be increased up to 600MB if more data monitored and the whole data stored 

  

Data and file formats

  * Mostly key-value pairs of time and power (other parameters also possible). Data can be easily translated into the CATALYST format (partially done for monitoring in DOLFIN). 

  

Purpose

Analysis of trials with on-site renewable energy use

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

Standards and metadata

</td>  
<td>

Data is identified by a related timeframe. Within CATALYST Trial ID will be
used to identify data sets. Other metadata will include information about the
PV system configuration and location.

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

Data sharing

</td>  
<td>

Data from PSNC photovoltaic system can be shared on request.

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

</td>  
<td>

Currently data are stored in file-based and relational databases at PSNC.
Sharing of data subsets via the LABEE portal or OpenAIRE repository is
considered.

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

Archiving and preservation

</td>  
<td>

Measurements from photovoltaic system are currently stored at PSNC for at
least period of 1 year. Currently, the total volume collected during 1 year
currently (using RRD database that automatically decrease size of older data)
is equal to 50MB. If the whole high frequency data is stored then, depending
on trials timeframe, depending on trials timeframe the total volume can reach
600MB.

This data set can demonstrate details of a trial in which certain results were
achieved.

This data is stored at PSNC.

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

_PSNC data centre_  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Ariel Oleksiak

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

Collecting period

</td>  
<td>

Selected periods from October 2017 to September 2020

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

Trial ID

</td>  
<td>

PSNC_DC_TC_2

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

Data set reference and name

</td>  
<td>

_[TrialID/PSNC/DC]_

• PSNC data centre

High Performance Computing centre

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

Data set description

</td>  
<td>

Measurement data from both facilities and IT. Data comes from 2MW data centre
consisting of diverse systems – various HPC architectures, network equipment
and others. The data includes amounts of heat re-used within the building for
office heating.

Type of data:

  * Energy consumption of servers and cooling; 

  

  * Temperature of coolant (high/low) 

  

  * Flow 

  

  * Power 

  

  * Heat exchanged 

  

  * Power usage of heat exchanger pump 

  

  * Ambient temperature 

  

  * Possibly other parameters – on request. 

  

Source

  * PSNC data centre, heat exchanger Volume 

  

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

</td>  
<td>

• Size of data to be calculated depending on data required in trials

Data and file formats

  * Mostly key-value pairs for various parameters 

  

Purpose

  * Analysis of real large-scale data centre operation and its thermal flexibility (heat re-use capacity) 

  

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

Standards and metadata

</td>  
<td>

Data is identified by a related timeframe and typical metrics such energy
consumption, etc.

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

Data sharing

</td>  
<td>

Data from PSNC data centre cannot be shared outside the consortium.

Currently are stored in file-based and relational databases at PSNC.

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

Archiving and preservation

</td>  
<td>

Measurements from the PSNC data centre are stored at PSNC (coming from the
BMS).

This data set can provide insights for development of CATALYST framework and
exploitation plans.

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

_PSNC-PUT heat exchange_  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Ariel Oleksiak

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

Collecting period

</td>  
<td>

Selected periods from October 2017 to September 2020

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

Trial ID

</td>  
<td>

PSNC_DC_TC_2

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

Data set reference and name

</td>  
<td>

_[TrialID/PSNC/DC]_

Heat exchange capabilities and requirements between PSNC and PUT

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

Data set description

</td>  
<td>

Data based on the PSNC data canter heat production (see _PSNC data centre_
paragraph above) and from 5 heating seasons at PUT Type of data:

  * Values of required (also for various temperature conditions) and ordered heat 

  

  * Supply/return water temperature for PUT 

  

buildings

  * Energy costs 

  

  * PSNC-PUT heat transfer Installation schema and costs 

  

Source

  * Poznan University of Technology (PUT) BMS system 

  

Volume

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

</th>  
<th>

  * Depending on period 

  

Data and file formats

  * Key-value pairs (from BMS) 

  

Purpose

Analysis of trials evaluating heat re-use capabilities using data centre heat

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

Standards and metadata

</td>  
<td>

Data is identified by a related timeframe. Other metadata will include
information about data centre type and components as defined in Section 4.1

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

Data sharing

</td>  
<td>

Data from PUT and PSNC data centre cannot be shared outside the consortium.

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

Archiving and preservation

</td>  
<td>

Measurements from PUT are stored at PUT. Measurements from the PSNC data
centre are stored at PSNC (in file-based and relational databases).

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

Pilot 3: SBP Co-location data centre  
  
<table>  
<tr>  
<th>

</th>  
<th>

Project name

</th>  
<th>

CATALYST

</th>  
<th>

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

ID

</th>  
<th>

768739

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

Project coordinator

</th>  
<th>

Diego Arnone

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

Project description

</th>  
<th>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</th>  
<th>

H2020-EE-2016-2017

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

Principal researchers

</th>  
<th>

Erwin Out / Paul Corneth

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

Collecting period

</th>  
<th>

December 2018 - August 2019

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

Trial ID’s

</th>  
<th>

SBP_DC_TC_1: DC Waste heat reuse for office heating;

SBP_DC_TC_2: Utility waste heat reuse for pre-heating DRUPS generator;

SBP_DC_TC_3: Comparison between static and dynamic

UPS systems;

SBP_DC_TC_4: River water DC free cooling;

SBP_DC_TC_5: Grid power flexibility – DC switch-off from grid;

SBP_DC_TC_6: IT load migration QRN – SBP DC

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

Data set reference and name

</th>  
<th>

What data are collected and how are they named?

  * Type of infrastructure/system (colocation), • Purpose of infrastructure (no physical test), 

  

  * Identifier: n.a. 

  

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

Data set description

</th>  
<th>

Description of the data, the origin, nature and scale and for what purpose
they were generated.

Type of data, e.g.

  * Power consumption calculation; 

  

  * Natural gas consumption calculation; 

  

  * Environmental data: temperatures in server rooms, offices: design parameters; 

  

  * IT monitoring: n.a. 

  

  * Energy market: prices of energy (power, natural gas) 

  

Source

  * Origin: calculations (SBP_DC_TC_1, SBP_DC_TC_2, SBP_DC_TC_4), study (SBP_DC_TC_3), Building 

  

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

</th>  
<th>

Management System (SBP_DC_TC_5); measurements (SBP_DC_TC_5, SBP_DC_TC_6

[optionally])

  * Schematics (SBP_DC_TC_1, SBP_DC_TC_4, SBP_DC_TC_5); 

  

Volume

  * No measurement data (SBP_DC_TC_1, 

  

SBP_DC_TC_2, SBP_DC_TC_3, SBP_DC_TC_4);

  * Limited calculation data (SBP_DC_TC_1, SBP_DC_TC_2, SBP_DC_TC_4); 

  

  * Basic measurement data, limited volume 

  

(SBP_DC_TC_5, SBP_DC_TC_6 [optionally])

Data and file formats

  * Word, Excel; 

  

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

Standards and metadata

</td>  
<td>

Data standards, metadata sets: Metadata to identify data set ▪ N.a.

More advanced metadata to (possibly to be synchronised with a CATALYST data
model)

• N.a.

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

Data sharing

</td>  
<td>

Shared data:

  * Pilot part reports including attachments; 

  

  * Calculation results, limited volumes (attachment to reports) (SBP_DC_TC_1, SBP_DC_TC_2, 

  

SBP_DC_TC_4); Data protection:

  * Measured data (data only for internal CATALYST 

  

project use, no life streaming);

  * Data from SBP data centre cannot be shared outside the consortium. 

  

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

Archiving and preservation

</td>  
<td>

Archiving and data preservation:

  * CATALYST website; 

  

Which data should/needs to be preserved? • Pilot part report plus attachments;

  * Recreation options: 

  

  * no restrictions, based on Amsterdam annual average environmental data (SBP_DC_TC_1); operation parameters (SBP_DC_TC_2); 

  

  * restrictions on river water temperatures, performances 

  

  * Useful for others: Systems principles, schematics (SBP_DC_TC_1, SBP_DC_TC_2, SBP_DC_TC_4), Grid power flexibility agreement (SBP_DC_TC_5), Grid power switch-off test and communication protocol (SBP_DC_TC_5), IT load migration system 

  

(SBP_DC_TC_6, optionally)

Preservation period:

  * CATALYST website availability; What is the final size of data 

  

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

</th>  
<th>

  * T.b.d., standard report size, limited amount of calculation / measurement data, estimation: < 0,5 Gb; 

  

Storage location:

  * CATALYST website; 

  

Storage costs / cost allocation:

  * Overall CATALYST project; 

  

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

Pilot 4: QRN Distributed HPC  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Nicolas SAINTHERANT

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

Collecting period

</td>  
<td>

TBD

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

Trial ID

</td>  
<td>

QRN_DC_TC_1

QRN_DC_TC_2

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

Data set reference and name

</td>  
<td>

_[TrialID/Qarnot/DistributedDC]_

• QRN distributed cloud HPC data centre Real production housing building

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

Data set description

</td>  
<td>

Measurements are used for platform management and scheduling needs, according
to the size of the building we can get data from 20 to 300 servers. Such
installation is simply connected to local regular energy grid.

Type of data:

  * Power usage of the servers 

  

  * Temperatures (targets, dissipators, room) 

  

  * IT monitoring: CPU utilization (%) of servers, 

  

  * Global site metrics: Storage utilisation (%), Network utilisation (%), total power consumption of the building (if we are connected to smart power counters) 

  

  * Energy market: prices of energy (almost 

  

static)

  * Internet bandwidth, latency, and global 

  

quality

  * Cap on the total energy we are allowed to use, or the building is allowed to use (almost static) 

  

Source

  * One housing building (TBD) Volume 

  

▪ TBD Depends on the time frequency…

Data and file formats

• TBD

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

Standards and metadata

</td>  
<td>

Data is identified by a related timeframe. Within CATALYST Trial ID will be
used to identify data sets.

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

</td>  
<td>

Other metadata will be rather limited as location and other details are
sensible data.

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

Data sharing

</td>  
<td>

Data from QRN distributed DC cannot be shared asis, primarily for user privacy
reasons. It encloses personal data and as such should be treated cautiously,
even if these data cannot be tied to one person or household.

The data sets will be shared only within the CATALYST project members upon
request.

About data protection, this data sets will be accessible to authorized person
at Qarnot, mainly researchers working on the CATALYST project.

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

Archiving and preservation

</td>  
<td>

Similar data sets are stored in data centre, the CATALYST trial data set will
most probably be stored in a regular data centre as well. Again, the end
volume will depend on many parameters, but especially the frequency and the
time frame.

The storage costs will be covered by Qarnot as regular data sets storage. The
data sets will be kept during all the project duration and during 3 years
after at least. Depending on further use of this data, data protection and
storage policy may evolve after the project.

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

###  Non-pilots data sets

Simulation data coming from tools and studies performed within CATALYST
project are summarized below.

Prediction and optimisation of DC flexibility  
  
<table>  
<tr>  
<th>

</th>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</th>  
<th>

768739

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

Project coordinator

</th>  
<th>

Diego Arnone

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

Project description

</th>  
<th>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</th>  
<th>

H2020-EE-2016-2017

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

Principal researcher

</th>  
<th>

Tudor Cioara

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

Collecting period

</th>  
<th>

The data set will be generated during the development and evaluation of
CATALYST DC Energy Flexibility Prediction & Optimization Components (in
relation with WP4)

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

Trial ID

</th>  
<th>

N/A

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

Data set reference and name

</th>  
<th>

_[Flexibility &OptimizationDataSet] _

The data set will include simulated data related to the electrical and thermal
flexibility estimation in various situations as well as the optimization
actions for flexibility shifting to offer different services.

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

Data set description

</th>  
<th>

Type of data:

Over the course of the project, flexibility data will be generated in various
input contexts using WP4 defined models taking into account the hardware
configuration of the CATALYST pilot DCs. Specifically:

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

</td>  
<td>

Minimum and maximum electrical energy flexibility availability for each
individual DC component and aggregated;

Maximum thermal flexibility availability for the server room;

Also the optimization actions taken by the energy optimizer to provide
specific flexibility services.

Source

  * Simulated. Volume 

  

  * Hundreds of MB, depending on how long tests and experimentation will last. 

  

Data and file formats

  * The data will be stored in a database; from which they can be easily exported as a Raw Data file or as a set of INSERT statements that recreate the records in the tables. Data will be also exportable as CSV files that can be used to recreate the records in the tables in other Optimizer instances, regardless of the underlying database infrastructure. 

  

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

Standards and metadata

</td>  
<td>

The relational database stores and provides access not only to the data but
also to metadata in a structure called data dictionary or system catalogue. It
holds information about tables, columns, data types, constraints, table
relationships, and many more.

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

Data sharing

</td>  
<td>

The simulated data can be shared only for the CATALYST experimentation
objective and in the scope of the project. Access to data generated during the
experimentation period is subject to authorization control and permission
rights granted per user group.

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

Archiving and preservation

</td>  
<td>

Data will be archived and preserved in the trial DCs during the Project and
for a period of 1 year after the end of the Project.

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

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Ariel Oleksiak

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

Collecting period

</td>  
<td>

N/A

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

Trial ID

</td>  
<td>

N/A

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

Data set reference and name

</td>  
<td>

_[SimulationID/CFD]_

• CFD simulations of a server room

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

CFD simulations of a server room  
  
<table>  
<tr>  
<th>

Data set description

</th>  
<th>

The data set consists transient CFD simulations data from scenarios calculated
for the needs of ML algorithm. It covers 3125 different scenarios of an
airflow and heat transfer in simplified server room. Scenarios are varied with
5 key parameters: initial internal server room temperature, air conditioner
volumetric flow rate, air conditioner outlet temperature and power consumption
of both racks present in virtual room. Snapshots of simulations results are
collected in 30-second simulated time intervals (the total simulated time
interval is 10 minutes). Aside from complete volumetric results, records from
specific domain points (virtual probes) are saved in 1-second simulated time
intervals. In the data set several physical variables are stored, such as
temperature, velocity, pressure and parameters related to turbulence
modelling.

Type of data:

  * temperature; 

  

  * velocity; 

  

  * pressure; 

  

  * turbulence parameters; 

  

Source

  * CFD simulations made with PSNC’s framework dedicated for server rooms analyses based on OpenFOAM software. 

  

Volume

  * Size of all the volumetric data is around 500GB 

  

  * The data collected by virtual probes is in the order of 1 GB. 

  

Data and file formats

  * The data is stored in native OpenFOAM format (volumetric data: binary files; probe data: plain ASCII files). 

  

Purpose

▪ Analysis of thermal processes and cooling in a server room; Composition of
training data set for ML algorithm

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

Standards and metadata

</td>  
<td>

Data is described by a definition of models using standard formats used for
geometry models and simulation data. The specific instance of data set is
identified by set of parameters for boundary conditions and timestamp values.

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

Data sharing

</td>  
<td>

The simulation data are considered to be shared through the LABEE portal and a
public repository.

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

Archiving and preservation

</td>  
<td>

Currently all the dataset is stored at the PSNC Eagle cluster. At present, the
time of storing is not limited. The data is protected with periodic backups.
All the configuration files of all scenarios are also stored, preserving the
possibility to continue calculations for longer time period. Sharing via local
and public repositories is planned.

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

###  Social data sets

_GDC-SG data set_

Data set related to the GDC-SG.  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

John Booth (GIT)

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

Collecting period

</td>  
<td>

During the project’s lifetime

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

Trial ID

</td>  
<td>

N/A

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

Data set reference and name

</td>  
<td>

▪ Information on members of the Green Data Centre –

Stakeholder Group (GDC-SG) and the project’s Advisory Board. The latter is
essentially a subset of the former.

• This data set is related to Task 8.5

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

Data set description

</td>  
<td>

Type of data, e.g.

  * Personal info such as, photo, name, job description and affiliation, contact info (such as email), possible social media profile info on LinkedIn and Twitter. 

  

  * Their activity and participation to GDC-SG meetings, events and related tasks. This includes for example meeting minutes, event proceedings, photos, presentations and conference calls records. 

  

Source

  * The members interested in the GDC-SG 

  

Volume

  * Depends on the number of members, related events and meetings. 

  

Data and file formats

  * As applicable, for example an excel file for the members directory, meeting minutes in doc or pdf format. 

  

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

Standards and metadata

</td>  
<td>

TBD at a later stage once we obtain more information and experience on the
GDC-SG membership and operations

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

Data sharing

</td>  
<td>

Which data will be shared?

  * The directory of GDC-SG members will always be public 

  

  * Private meeting minutes will be shared only within the GDC-SG 

  

  * Public events proceedings, presentations, videos and such will be public Data protection 

  

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

</td>  
<td>

▪ The whole consortium will always have access to these data.

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

Archiving and preservation

</td>  
<td>

After the completion of the project, the GDC-SG will be responsible for
storing and sharing the data

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

###  Market data sets

Simulated Marketplace related data  
  
<table>  
<tr>  
<th>

Project name

</th>  
<th>

CATALYST

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

ID

</td>  
<td>

768739

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

Project coordinator

</td>  
<td>

Diego Arnone

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

Project description

</td>  
<td>

Converting DCs into Energy Flexibility Ecosystems

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

Funder

</td>  
<td>

H2020-EE-2016-2017

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

Principal researcher

</td>  
<td>

Diego Arnone

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

Collecting period

</td>  
<td>

The data set will be generated during the CATALYST Marketplace implementation
phases and during the integration phases from M7 (Apr 2018) to M36 (Sept
2020).

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

Trial ID

</td>  
<td>

N/A

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

Data set reference and name

</td>  
<td>

_[CATALYSTMarketplace]_

  * The data set will include _simulated_ data related to the four variants of the CATALYST Marketplace: 

  

Electricity, Flexibility, Heat/Cold, IT Load.

Identifier:

  * CATALYSTMarketplace/Electricity 

  

  * CATALYSTMarketplace/Flexibility 

  

  * CATALYSTMarketplace/Heat/Cold 

  

  * CATALYSTMarketplace/IT Load 

  

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

Data set

description

</td>  
<td>

Simulated Marketplace related data Type of data:

• Over the course of the project, CATALYST Marketplace data (market
participants, market sessions, bids, offers, market sessions results) will be
generated in a simulated way and entered into a relational database.
Specifically, the following data will be generated:

o General information about energy prices, marketplaces, market sessions,
market actions, transactions, invoices

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

</td>  
<td>

o

</td>  
<td>

Personal data about market participants, market operator, aggregators, DSO(s)

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

</td>  
<td>

o

Source

</td>  
<td>

User credentials, hashed using PBKDF2 algorithm (only the hashed value is
preserved)

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

</td>  
<td>

</td>  
<td>

  * Simulated. 

  

Volume

  * Hundreds of MB, depending on how long tests and experimentation will last. 

  

Data and file formats

  * The data will be stored in a Postgres database, from which they can be easily exported as a Raw Datafile or as a set of INSERT statements that recreate the records in the tables. 

  

  * Data will be also exportable as Django dumps exported as plain text JSON files that can be used to recreate the records in the tables in other Marketplace instances, regardless of the underlying database infrastructure. 

  

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

Standards metadata

</td>  
<td>

and

</td>  
<td>

The relational database store and provide access not only to the data but also
to metadata in a structure called data dictionary or system catalogue. It
holds information about tables, columns, data types, constraints, table
relationships, and many more.

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

Data sharing

</td>  
<td>

</td>  
<td>

Simulated Marketplace data can be shared only for the CATALYST experimentation
objective and in the scope of the project.

Access to marketplace data generated during the marketplace instance operation
is subject to authorization control and permission rights granted per user
group, when attempted both programmatically and through the marketplace user
interface. User credentials are hashed using PBKDF2 algorithm.

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

Archiving and preservation

</td>  
<td>

</td>  
<td>

Data will be archived and preserved in the trial DCs during the Project and
for a period of 1 year after the end of the Project.

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

#  Conclusions

This document provides the CATALYST Data Management Plan. It delivers a
template for data descriptions with definitions of possible data sets and
along with data management methodology and data protection measures.

The report provides overall description of the sources delivering the data
within the CATALYST project including security and preservation data. It
summarizes the availability of the data during the project lifetime and after
the end of the project including the possibility of sharing the data in
external repositories accessible via OpenAIRE. Finally detailed description of
particular data sets (including newly defined ones) is given.

This is the final version of the DMP, however, during realisation of trials,
some updates of data sets depending on configurations, results of experiments
and external data availability may appear. Further information on how specific
data sets are processed in the project along with results from trials will be
provided in D7.4.

Significant part of the project data is for internal use as it comes from
critical infrastructure or contains sensible data, however, some data sets are
planned to be shared publicly and preserved after the end of the project.