D1.3 Data Management Plan

1 D1.3 Data Management Plan V0.3 Grant agreement: No. 101069689 From: Fraunhofer ISE Prepared by: Sebastian Helmling Date: 31/03/2023 2 TABLE OF CONTENTS TABLE OF CONTENTS .................................................................................................................................................................... 2 ABBREVIATIONS .................................................................................................................................................................................. 3 LIST OF FIGURES ................................................................................................................................................................................. 4 VERSIONS................................................................................................................................................................................................. 4 1. INTRODUCTION ............................................................................................................................................................................... 5 1.1 Objective of the deliverable ...................................................................................................................................... 5 1.3 Contribution of partners .................................................................................................................................................... 5 1.4 Relation with other activities in the project .......................................................................................................... 6 1.5 The FAIR data management principles .................................................................................................................. 6 1.6 information exchange platform ................................................................................................................................... 7 1.7 protection of personal data ............................................................................................................................................ 8 1.9 public deliverables ................................................................................................................................................................. 8 2. Monitoring .......................................................................................................................................................................................... 8 2.1 definition of system boundaries ................................................................................................................................... 8 2.2 Data collection ........................................................................................................................................................................ 9 3. Data Storage and Processing Platforms ....................................................................................................................... 9 3.1. Locally at demonstration Sites ........................................................................................................................ 10 3.2. Cloud Integration of data sets ......................................................................................................................... 10 3.2.1. IoT-Platform ................................................................................................................................................................. 10 3.2.2. Backup strategy ........................................................................................................................................................... 11 3.2.3. Time Series Storage ................................................................................................................................................. 11 3.2.4. Meta data ........................................................................................................................................................................ 11 3.2.5. Data storage Protection ....................................................................................................................................... 12 3.2.6. Data access for measurement data and derived data ................................................................. 13 3 3.2.7. Data Destruction ........................................................................................................................................................ 14 4. Data Protection Impact Assessment ............................................................................................................................. 14 4.1 Risks ................................................................................................................................................................................................ 14 4.2 Measures to reduce the risks ...................................................................................................................................... 15 5. List of references ......................................................................................................................................................................... 16 ABBREVIATIONS ACL Access Control List DPIA Data Protection Impact Assessment GDPR General Data Protection Regulation HUT Heat Upgrade Technology IoT Internet of Things IPR Intellectual Property WP Work Package 4 LIST OF FIGURES Figure 1: mondas IoT Platform .................................................................................................................................................... 11 Figure 2: meta data management tool ............................................................................................................................. 12 VERSIONS No. Name Partner Contribution Date 0.1 Sebastian Helmling Fraunhofer ISE First complete draft 17/02/2023 0.2 Sebastian Helmling ALL Checked by the partners 08/03/2023 0.3 Sebastian Helmling Fraunhofer ISE Final update 31/03/2023 5 1. INTRODUCTION 1.1 Objective of the deliverable The main objective of the deliverable is to provide a data management plan for the measurement data which is collected and the derived data which are generated within the PUSH2HEAT project. The Data Management Plan is the central document describing the life cycle of the data from collection to archiving, including all measures to ensure that the data remains available, usable, and comprehensible (understandable). During the project measurement data from the heat upgrade technologies (HUT) will be gathered at the three/four demonstration sites. This requires the installation of sensors and data acquisition systems on site. Furthermore, additional data sources such as the controllers of the heat upgrade devices and the process automation of the plants hosting the heat upgrade technologies must be connected. This requires the gathering, extraction, processing, storage and management of data sets coming from the PUSH2HEAT demonstration sites. This document specifies the data management plan that will be employed by the PUSH2HEAT project to ensure that all relevant data management policies are adhered to and to ensure that reliable data can be extracted and used for the PUSH2HEAT project development. This document is being developed in accordance with the H2020 Guidelines on Data Management [1]. This document is delivered in Month 6 of the project. It will be updated every 12 months and whenever it becomes necessary e.g. because of the integration of new data sets. 1.3 Contribution of partners The task T1.3 in WP1 is led by Fraunhofer ISE and participated by the WP Leaders, i.e. TECNALIA, FRAUNHOFER, POLIMI, OST and EHPA. 6 Since all project partners have an interaction with the measurement data, their input to this document is necessary. 1.4 Relation with other activities in the project The data management plan will set the basis for the interaction with measured and derived data in the project. It defines the rules for the interaction of the stakeholders of the project. The following tasks have a relation to that data and are therefore related to this deliverable.: - T3.5. Commissioning and first performance tests - T3.6. Assessment of commissioned demonstration systems. - T4.1. Monitoring plan - T4.2. Monitoring system integration and validation - T4.3. Monitoring, performance data analysis - T5.2. Replication studies - T5.3. Life cycle environmental and cost assessment (LCA/LCC) - T6.3. Communication and dissemination activation: creating impact and expanding outreach. 1.5 The FAIR data management principles The FAIR (Findable, Accessible, Interoperable, and Reusable) data management principles provide a framework for making research data more accessible and reusable. The principles are designed to ensure that data are available for reuse and that they are of high quality, reusable, and reliable. The Horizon Europe open access mandate aims to promote open access to scientific publications and research data, and it aligns with the FAIR data management principles. Here's a step-by-step breakdown of how PUSH2HEAT meets the FAIR data management principles [2]. 1. Findable: The first principle of FAIR data management is that data should be findable. This means that data should be easily discoverable and accessible. To meet this principle, the Push2Heat research data will be deposited and indexed In the OpenAIRE [3] infrastructure. 7 2. Accessible: The second principle of FAIR data management is that data should be accessible. This means that data should be available for reuse without any legal, technical, or financial barriers. To achieve this goal, an attempt is made to make the Push2Heat results available if no trade secrets or personal rights are violated by doing so. 3. Interoperable: The third principle of FAIR data management is that data should be interoperable. This means that data should be structured in a way that allows it to be easily integrated with other data sources. To meet this principle, PUSH2HEAT uses a standardized data format and a metadata schema. 4. Reusable: The fourth principle of FAIR data management is that data should be reusable. This means that data should be of high quality and suitable for reuse in different contexts. To meet this principle, PUSH2HEAT provides the documentation of the metadata that describes research data. 1.6 information exchange platform Push2Heat uses the Microsoft 365 SharePoint to manage all the documents in the project. Microsoft 365 SharePoint is a cloud-based platform that allows the PUSH2HEAT partners to collaborate and share files and resources. It is part of the Microsoft 365 suite of applications and provides a range of tools for creating, managing, and sharing content, including documents, images, and videos. SharePoint is used to manage their PUSH2HEAT workflows and content in a centralized and secure way. SharePoint provides powerful search capabilities, allowing PUSH2HEAT partners to quickly find the content they need. In addition, it includes version control and auditing features, which help ensure that content is always up-to-date and that changes are tracked. 8 1.7 protection of personal data E-mail addresses and phone numbers of the PUSH2HEAT partners are personal information and covered by the GDPR [4]. All the contact data of the PUSH2HEAT partners is stored in the Push2Heat Microsoft 365 SharePoint which is password protected. This ensures that only authorized PUSH2HEAT partners have access to this data. It is not permitted to share this data without the permit of the respective partner. 1.9 public deliverables The deliverables which are generated within the PUSH2HEAT will be accessible to the scientific and technological community, if not market sensitive. All the project papers will be published in full open access journals, as Open Research Europe, and stored in repositories that are accessible through the EC service OpenAIRE [2] and Google searches. Furthermore, the publications will be stored in the ZENODO [5] repository. 2. Monitoring The heat upgrade systems will be examined under real operating conditions. Both an energy evaluation and an investigation of the operating behaviour are to be carried out. For this purpose, the systems are tested within the framework of a metrological examination. 2.1 definition of system boundaries In order to be able to evaluate the systems based on uniform criteria, boundary conditions must be defined. These boundaries apply to all three/four sites in the same manner. First, the following three framework conditions are defined for the evaluation of the systems: 9 1. Heat upgrade technology (HUT) only. Purpose: calculate and monitor the performance of the machine under different operating conditions. 2. HUT + heat source circuits and heat sink circuits for evaluating the impact of the auxiliaries of the external circuits on the performances. 3. Entire energy system including other generators. Purpose: evaluate the absolute and relative impact of the HUT on the overall system (fuel savings, additional electrical consumption, both in specific and absolute terms). 2.2 Data collection For evaluating the performance of the PUSH2HEAT technologies data must be collected. This data will be gathered from three main data sources: Sensors, heat meters. electricity meters, etc. measuring the physical state variables among the heat upgrade devices. These sensors are connected to a local data acquisition system. Controller of the heat upgrade device: The controller connects sensors whose measured values are of interest for the evaluation of the PUSH2HEAT system. These data sets are either transferred to the data acquisition system via an appropriate protocol or sent to the Fraunhofer ISE server via an appropriate protocol. Production automation system: The process automation control system collects data that is of interest for evaluating the framework conditions of the technology. These data sets are either transferred to the data acquisition system via an appropriate protocol or sent to the Fraunhofer ISE server via an appropriate protocol. 3. Data Storage and Processing Platforms The data collected as part of the PUSH2HEAT project may be stored, maintained, and processed at several different points depending firstly on the nature of the data and secondly the provision of this data for access to other PUSH2HEAT tools. The remaining of this section provides an outline of each option that has been defined. 16 5. List of references [1] http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020hi-oa-data-mgt_en.pdf [2] https://www.openaire.eu/how-to-comply-with-horizon-europe-mandate-for-publications [3] https://provide.openaire.eu/home [4] https://gdpr.eu/ [5] https://zenodo.org/