CENTAUR: Cost Effective Neural Technique for Alleviation of Urban flood Risk. D4.4 Data Management Plan

Transcription

1 CENTAUR: Cost Effective Neural Technique for Alleviation of Urban flood Risk D4.4 Data Management Plan *Note: this deliverable has not yet been approved by the EC and hence may be subject to change* Lead Partner: USFD Revision: 1 st September 2017

2 Report Details Title: Data Management Plan Deliverable Number (If applicable): 4.4 Author(s): Simon Tait, Will Shepherd Dissemination Level: Public Document History Version Date Status Submitted by Checked by Comment 1.0 9/3/2016 Draft Simon Tait Will Shepherd /3/2016 Final Will Shepherd Simon Tait Agreed at GA meeting, uploaded to Sygma /9/2016 Draft of updated version 2.0 Will Shepherd Simon Tait Changes requested by Project Officer /09/16 Draft Simon Tait Will Shepherd Added new material /9/16 Draft Will Shepherd Simon Tait Minor revisions made /10/16 Final Simon Tait Will Shepherd ed to PO /05/17 Draft update Will Shepherd Simon Tait Update following acceptance of version 2.3 and GA meeting and prior to upload to Sygma /05/17 Final Simon Tait Will Shepherd Uploaded to Sygma /08/17 Draft of update /09/17 Final update Simon Tait Will Shepherd Revisions requested by Evaluator Will Shepherd Simon Tait Uploaded to Sygma Acronyms AC DoA DOI EAWAG EMS FCD IPR UoC USFD AC Aguas De Coimbra EM Description of the Action (Annex 1 to the Grant Agreement) Digital Object Identifier Eidgenoessische Anstalt Fuer Wasserversorgung Abwasserreinigung Und Gewaesserschutz Environmental Monitoring Solutions Flow Control Device Intellectual Property Rights Universidade de Coimbra University of Sheffield 2

3 Acknowledgements This project has received funding from the European Union s Horizon 2020 research and innovation programme under grant agreement No The contents of this report reflect the view of the authors. The Executive Agency for Small and Medium-sized Enterprises (EASME) of the European Commission is not responsible for any use that may be made of the information it contains. 3

4 Executive Summary CENTAUR is part of a pilot on open access being run within the H2020 research program. As part of the pilot, CENTAUR is required to produce a Data Management Plan. The H2020 research program is promoting open access of data and publications as the European Commission believes that the wide availability of data will lead to optimal use of public funding by reducing duplication and encouraging and supporting future research and innovation at little further cost. CENTAUR is an innovation project rather than a research and development project. The project s Data Management Plan attempts to follow the principle of open data access whilst accepting the need for confidentiality to address privacy needs to protect personal data, and to provide for Intellectual Property Rights (IPR) protection and the commercial confidentiality of the partners, especially for the non-university partners who are contributing financially to the project activities. These constraints and how the partners will act regarding these are clearly set out in the Project Consortium Agreement. The Data Management Plan now describes how the consortium will manage the competing needs of the partners with the aspirations of the European Commission. The Data Management Plan addresses how the partners plan to collect data, catalogue it and if appropriate make it available on an open access basis during and after the project. The plan also describes the review mechanism the consortium will take to ensure that as much of the data collected during the project can be made available as soon as is practicable. All academic publications from the project will be made available in an open access repository. The co-ordinator will provide facilities for storage of open access data and will archive this data and will deposit it in an enduring open access data repository by the end of the project. The Data Management Plan will be reviewed at each General Assembly meeting and reissued. A revision will be issued annually. Each revision of the Data Management Plan will list the open access data sets and also the data that is held confidential and the reason for this decision. This approach is intended to provide an appropriate balance between the aspiration for open access data and the need to retain some data within the consortium to support effective market replication and exploitation so that public benefit, in terms of jobs growth and enhanced flood protection can be obtained via readily available CENTAUR systems.

5 CONTENTS Executive Summary Introduction Partners Involved in Deliverable Project Details Project Summary Policies Data Collection, Documentation Sharing and Storage Overview Data handling during and after the project Summary of data being collected, processed and generated Flow survey data for development of the dual drainage model Virtual testing simulation data Laboratory testing Coimbra/Veolia pilot and demonstration testing Flow Control Device design data Site selection methodology and results Legal and Ethical Compliance Long Term Storage and Archiving Data security Summary References Appendix A. Register of Completed Datasets Appendix B. Example of Proposed Metadata for Open Access Data B.1 Metadata within the main Zenodo record B.2 Additional metadata as a pdf within the dataset

6 1 Introduction 1.1 Partners Involved in Deliverable USFD the deliverable has been drafted by USFD and has been commented on by all partners in the CENTAUR consortium. 1.2 Project Details CENTAUR - Cost Effective Neural Technique to Alleviate Urban Flood Risk Funded by: European Commission Contract No Start Date: 01 September 2015 Duration: 36 months Contact Details: centaur@sheffield.ac.uk Co-ordinating Institution: University of Sheffield Website: Project Summary The project will develop a radically new market ready approach to real time control (RTC) of sewer networks with the aim of reducing local flood risk in urban areas. Existing RTC projects (e.g. in the cities of Vienna, Dresden, and Aarhus) are characterised by complex sensor networks, linked to high cost centralised control systems governed by calibrated hydrodynamic modelling tools and often fed by high cost and complex radar rainfall technology. Such systems are expensive and complex to install and operate, requiring a high investment in new infrastructure, communication equipment and control systems, and highly trained staff. In contrast, this proposal will develop a novel low cost decentralised, autonomous RTC system. The concept is to be able to install such systems in existing infrastructure and for it to require low levels of maintenance and staff input. During the project the CENTAUR system will be installed, tested and demonstrated in a number of pilot study catchments. This RTC system will utilise data driven distributed intelligence combined with local, low cost monitoring systems installed at key points within existing sewer infrastructure. The system will utilise mechanically simple, robust devices to control flow in order to reduce flood risk at vulnerable sites. This system will be informed and governed directly by sensors distributed within the local network, without the need for an expensive hydrodynamic model or real time rainfall measurements. This system will deliver many of the benefits of RTC systems, whilst avoiding the high costs and complex nature of extensive sensor networks, centralised control systems, communications systems and infrastructure modifications. It is anticipated that such a system will be of significant benefit to operators of small to medium sized sewer networks. 6

7 2 Policies The project participants will at all times meet their obligation on the access rights and nondisclosure of data as set out in the project Consortium Agreement. Nothing in this Data Management Plan removes any rights or obligations as set out in the consortium agreement The project will aim to follow the H2020 guidelines as regards open access and data management and will also adhere to the principles of the data management policy of the co-ordinating institution, the University of Sheffield. H2020 Guidelines: -hi-oa-data-mgt_en.pdf. University of Sheffield Guidelines on the Management of Research Data: The Data Management Plan will also be reviewed by all partners at each General Assembly meeting and re-issued every 12 months. 3 Data Collection, Documentation Sharing and Storage 3.1 Overview The European Commission has recognised that to achieve the best return for their funding of research and development activities that any of the resultant research data should be capable of re-use. This is best achieved by making data and publications openly accessible. The data from CENTAUR will be made openly accessible, subject to any constraints set out in the Consortium Agreement on data ownership and its use by other parties. These constraints relate to compliance with any national legal requirements (e.g. Personal Data), the protection of IPR and commercial confidentiality in order to achieve effective market replication and exploitation of the CENTAUR technology and supporting knowledge developed during the project. Subject to the above constraints data will be made available, once it has been processed into a final formal, organised and catalogued and is free of error. Appendix A will contain a table of all completed data sets, including whether the data is open access. Partners will use current best practice in terms of data collection processing and validation and will ensure that sufficient resources are made available from the project funds to achieve these tasks. Adequate description of the context, measurement and processing methods will be made available. Details will be linked to each data set so that it is clear how it is structured. Adequate documentation will be provided so that it is searchable. Appendix B provides an example of what level of information will be provided for each open access data set. This will include information on the sensors used, their calibration and validation, and the file and parameter naming conventions. 7

8 The co-ordinator will produce a catalogue of available open access data and publish this on the project website. The co-ordinator is willing to host the open access data electronically and will transfer all accessible open access data to the Zenodo ( enduring open access repository. Any open access software tool will be stored either on Zenodo, or using GitHub, at the preference of the partner producing the tool. The project beneficiaries will ensure that sufficient resources are made available from the project funds to ensure that all the data sets that are uploaded onto the open access repository are organised, catalogued and practically free of error, and that sufficient metadata is provided so that a third party can use the data. The peer-reviewed scientific publications arising from the work in CENTAUR will follow the requirements set out in the Grant Agreement and Consortium Agreement. They will be openly accessible as this is a requirement of the Grant Agreement. All publications will be stored in an OpenAIRE compliant repository and listed on the CENTAUR page in the OpenAIRE portal. The co-ordinator will also list the details of all publications on the project website, along with links to access the publications. The Data Management Plan will be reviewed at each General Assembly meeting and reissued annually in light of experience gained during the project. Appendix A of the Data Management Plan will list completed data sets produced during the project. It will list those data sets that are open, and those that are restricted to the members of the consortium along with the reason why the data set has been restricted. Data sets can only be restricted for one of three reasons: to comply with national regulations for the protection of personal data; to protect IPR for future exploitation; and for data that is commercially confidential and the release of which would financially damage a partner. After generating a data set partners will be required to list these in Appendix A of the Data Management Plan and then state whether the data can be open access, if this is not possible then the reason will be given as to why the data set is not open access. These decisions will be reviewed periodically at the General Assembly meetings. If any objections are raised as to the status of any data set, this will be discussed at a General Assembly and the final decision of the status of a data set taken by the General Assembly following the decision making process described in the Consortium Agreement. 3.2 Data handling during and after the project The data will be collected or generated primarily by the University of Coimbra (UoC), University of Sheffield (USFD) and later in the project by Veolia. These partners will be supported in the field data collection by Environmental Monitoring Solutions (EMS). Steinhardt will generate data on the system design, EAWAG are expected to generate simulation data. Aguas de Coimbra are involved in the data being collected by UoC, but are not expected to generate any other data themselves. As a general principle, the primary responsibility for storage and handling of the data will lie with the partner originally collecting it. An understandable data structure will always be used for any data collected. For field and laboratory data collection filenames will 8

9 incorporate the date of collection and where appropriate the sensor id. This will then be linked to a spreadsheet providing further details including any calibration parameters and comments on any issues affecting data quality. For both laboratory and virtual testing datasets the filename will incorporate the date of the test or simulation and/or the test or simulation number. The date and run number will link to a spreadsheet summarising the testing carried out and including the relevant parameters for the test or simulation run. For field data, the datasets may cover a longer period, hence the filename would include both start and end date if applicable, but otherwise conform to the same basic standards as the laboratory and virtual testing data sets. Key metadata will be stored alongside the data, for field and laboratory measurements this may include calibration data, sensor details, sensor location, and details of the test being carried out. For virtual testing the metadata will included information on the hydro-dynamic model, the version of the algorithm and parameters used and the rainfall event(s) run. All data will be checked prior to storing, these checks are primarily sense checks such as mass balances where practical and cross-checking data between sensors for consistency. Data will be backed up on a regular (weekly) basis, with the backup stored at a different site by the partner that has collected it. Some of the data will be useful to other partners and will be shared as needed via the project s user controlled Google Drive folder. This data store is provided by the University of Sheffield and is password protected and provides an appropriate level of protection for data used within the project. The folder will be managed by the Project Co-ordinator. It is the responsibility of the partner collecting the data to deem it open access or restricted within the consortium or restricted to within the partner organisation following the principles outlined above. For data sets deemed to be open access, the Project Co-ordinator will work with the partner that generates the data and will assist in its placement in the Zenodo data repository which will enable the data set to be assigned a unique DOI (Digital Object Identifier). The data will be linked to the CENTAUR community on Zenodo ( and the data will also be linked to the CENTAUR page on OpenAIRE ( projectid=corda h2020:: a468749db757b4bb290b04b284706d8a). The project co-ordinator will ensure that the data sets uploaded to this repository are quality checked and placed in a structured manner that will allow 3 rd parties the ability to search and obtain data. Discoverability of the data sets would be ensured by including a clear abstract / description and relevant keywords within the Zenodo record, any publications referencing the data would use the DOI. Keywords should include the project name acronym, keywords listed in the DoA and any additional keywords specific to the data set (e.g. laboratory water depths). It is not expected that different versions of data sets would be made open access, however the dataset name would include a version, along with information in the description to identify characteristics of different versions. The Zenodo repository has a clear process to allow different versions of data sets to be uploaded ( For software tools deposited on GitHub, version control is a core feature of this platform. 9

10 After the project the coordinator will collect all the internal data on the project s Google Drive folder, archive it and store on at an institutional secure storage area for a period of at least 5 years. This will be the definitive record of the project data, the Google Drive service is subscribed to institutionally by USFD, hence there are no costs associated. This data will be available to project partners for this period, during which any follow on publications or studies would most likely be completed. There is no need for data recovery as the Google Drive is mirrored across multiple sites, accidental deletion should not be possible as files are removed to a trash folder and only completely deleted if subsequently removed from the trach folder. Appendix B includes an example of information that will be included as part of the metadata for the Open Access data sets. The open access data would be useable for the foreseeable future after the project ends, the repositories are free to use, hence no costs are involved. Long term preservation of data may be beneficial in providing free information to aid future studies. 3.3 Summary of data being collected, processed and generated There are a number of separate datasets which will be collected or generated during the CENTAUR project. The majority of datasets have common features in that the parameters recorded relate to flows and depths in sewer pipes, or on an urban catchment surface or to the status of the flow control device, these data sets will all be time series at a single location. The other types of data are the Steinhardt flow control device designs and the data created by EAWAG on site selection methodologies. There is likely to be limited existing data being re-used in this project, any data made open access will originate from the work of the project Flow survey data for development of the dual drainage model Purpose To calibrate and verify the dual drainage model of the Coimbra pilot study catchment Relation to project objectives A calibrated dual drainage model will allow the performance of the urban drainage network to be better understood and allow selection of a site to install the flow control device for pilot testing. The model will also be used in virtual testing to assess the performance of the flow control device (see 3.3.2) Timescale Winter 2015 and Spring Types and formats Observational data from installed pressure transducers and flow monitors. The data will be stored uncompressed and unencrypted in ASCII and/or spreadsheet formats. 10

11 Methodologies and standards Data collection and analysis is guided by the document A guide to short term flow surveys of sewer systems (WRc, 1987) Access to data and required metadata This data will not be made accessible as the associated metadata required to make the data re-usable includes details of the sewerage network, which is the confidential property of the water company which owns the sewer network. This data may also be used to identify the flood risk of individual properties. This data will be retained securely by the partners that collect and use it (EMS and UoC). If it is to be shared this will be done via password protected files or via the password protected project Google site folder. The key metadata includes the locations of the data collection, information on the surrounding drainage network, the sensor specifications and calibration details. This information will be stored alongside the data by UoC Virtual testing simulation data Purpose To develop and test the CENTAUR control algorithm using previously calibrated hydrodynamic sewer network models Relation to project objectives Prior to implementing the flow control device on an operational sewer network it must be tested both in the laboratory and using hydrodynamic models to confirm that the control algorithm is stable and safe Timescale From Spring 2016 until around Spring 2018, depending on development needs Types and formats Simulation data from calibrated hydro-dynamic models. The data will be stored uncompressed and unencrypted in ASCII and/or spreadsheet formats Methodologies and standards The models should have been produced in accordance with the Code of Practice for the Hydraulic Modelling of Sewer Systems (WaPUG, 2002) Access to data and required metadata This data will not be made accessible as the associated metadata required to make the data re-usable includes details of sewerage networks, which is the confidential property of the water companies which own the sewers. This data may also be used to identify the flood risk of individual properties. This data will be retained securely by the partners that collect and use it (EMS and UoC). If it is to be shared this will be done via password 11

12 protected files or via the password protected project Google site folder. The key metadata includes the details of the network model, the version of the software and the parameters used in the simulations. This information will be stored in a spreadsheet format alongside the results produced Laboratory testing Purpose To test the CENTAUR flow control device hardware and the control algorithm Relation to project objectives Prior to implementing the flow control device on an operational sewer network it must be tested both in the laboratory and using hydrodynamic models to confirm that the control algorithm is stable and safe and that the hardware is reliable and operates as expected Timescale Initially Summer 2016 to Autumn 2017, may be extended due to development needs Types and formats Experimental data from the laboratory test facility constructed for CENTAUR. The data will be stored uncompressed and unencrypted in ASCII and/or spreadsheet formats Methodologies and standards There are no relevant standards, however the data will be calibrated and checked for consistency before being accepted Access to data and required metadata This data will be made accessible via the Zenodo data repository after a period of 1 year to allow time for the consortium to publish papers. Metadata concerning the laboratory rig dimensions and information on the sensors will be provided, an example of the planned format and content is shown in Appendix B. Information on the control algorithm which operates the flow control device is commercially sensitive and will not be provided. The data will primarily be of interest to anybody wishing to replicate results presented in published papers, there is unlikely to be a significant amount of re-use as the data is very specific. It is expected that the total amount of data will be several hundred megabytes. The data will be made available on a Creative Commons Attribution-ShareAlike licence ( Coimbra/Veolia pilot and demonstration testing Purpose To test the CENTAUR flow control device hardware and the control algorithm. 12

13 Relation to project objectives Following virtual and laboratory testing, the flow control device and control algorithm will be tested in the Coimbra sewer network in Portugal and then in a demonstration site managed by Veolia Timescale From Autumn 2016 for 18 months Types and formats Observational data from the data from installed pressure transducers and the flow control device status. The data will be stored uncompressed and unencrypted in ASCII and/or spreadsheet formats Methodologies and standards There are no relevant standards, however the data will be calibrated and checked for consistency before being accepted Access to data and required metadata This data will not be made accessible as the associated metadata required to make the data re-usable includes details of sewerage networks, which is the confidential property of the water companies which own the sewers. This data may also be used to identify the flood risk of individual properties. This data will be retained securely by the partners that collect and use it (EMS, UoC and Veolia). If it is to be shared this will be done via password protected files or via the password protected project Google site folder. The performance data from the demonstration sites will also be commercially sensitive as it will be used to develop the commercial business case for the deployment of CENTAUR. The key metadata includes the locations of the data collection, information on the surrounding drainage network, the sensor specifications and calibration details. This information will be stored alongside the data by UoC and Veolia Flow Control Device design data Purpose Design information for the developed flow control device Relation to project objectives The flow control device is a key part of the CENTAUR system, allowing flows in the drainage network to be controlled Timescale Design will develop between the start of the project and the finalisation of the design for the demonstration site, i.e. September 2015 to September

14 Types and formats The data is consists of drawings, written specifications and tables showing the calculated flow rates under different conditions. These will be archived in pdf format Methodologies and standards N/A Access to data and required metadata This data will not be made accessible as the design is a key part of the CENTAUR IPR. If it is to be shared this will be done via password protected files or via the password protected project Google site folder. There is not expected to be any requirement for metadata beyond what is already within the documents Site selection methodology and results Purpose Developing a methodology to select optimum sites for the deployment of CENTAUR Relation to project objectives In order to efficiently market CENTAUR, a methodology to select sites from commonly available catchment and drainage network data will be very useful Timescale This part of Task 3.4 commenced early, hence the timescale is October 2016 to April Types and formats The data output form the methodology will score / rank the suitability of different parts of the drainage network for installation of a CENTAUR system and will be in ASCII format. The methodology is in the form of a java based software tool Methodologies and standards There are no relevant standards for the output data. The software tool is being version controlled through a GitHub repository Access to data and required metadata The output data will not be made accessible as the associated metadata required to make the data re-usable includes details of sewerage networks, which is the confidential property of the water companies which own the sewers. This data will be retained securely by EAWAG. If it is to be shared this will be done via password protected files or via the password protected project Google site folder. 14

15 The software tool will be made open access through a GitHub repository, this repository includes the relevant metadata to allow the tool to be run (i.e. instructions). This tool may be utilised by other researchers and practitioners investigating in sewer storage. 4 Legal and Ethical Compliance At all times will the partners comply with national legal requirements as regards the protection of personal data. The co-ordinating institution has a rigorous policy on the collection and storage of personal data ( expectations). This will be adhered to by all partners. After an assessment at the start of the project by the Project Co-ordinator no personal data is planned to be collected in this project. It is not expected that any of the partners will explicitly generate personal data during the project. 5 Long Term Storage and Archiving The co-ordinator will provide electronic storage facilities for open access data and its metadata created by any partner during the project. This data will be uploaded to the Zenodo data archive. Any software tool produced will be stored either on the Zenodo repository, or GitHub. The co-ordinator will not provide long term storage for any personal data, or data that is required to protect IPR and commercially confidential information. At the end of the project, the co-ordinator will archive any files and data (not containing personal data or commercially confidential information) on the shared project Google drive and make this available to all the partners. All peer-reviewed scientific publications relating to the results of CENTAUR will be openly accessible. The partner producing the publication will be responsible for storing these publications in an enduring repository which is compatible with OpenAIRE (it can be institutional, subject-based or centralised) as soon as possible, and at the latest on publication. Such publications will be listed and linked to on OpenAIRE (at projectid=corda h2020:: a468749db757b4bb 290b04b284706d8a) and also providing links for access on the project website. 6 Data security Data will be stored securely for two reasons, to ensure its integrity and also to ensure compliance with personal data protection regulations, IPR protection and commercial confidentiality. Devices that contain data will be password protected securely stored when not in use. Data sets available online will be in a password protected folder, such as the project s Google Drive. Any personal data that is stored by the consortium partners will be encrypted. 15

16 Data that is open access will not be password protected and will be made available via the open access data repository Zenodo. 7 Summary CENTAUR will endeavour to make the data it produces open access following the H2020 guidelines. It will take into account any constraints on data availability described in the Consortium Agreement and any national legal requirements on the protection of data. The project beneficiaries will ensure that sufficient resources are made available from the project funds to ensure that all the data sets that are uploaded onto the open access repository Zenodo are organised, catalogued and practically free of error, and that sufficient metadata is provided so that a third party can use the data. The partners will ensure all peer-reviewed scientific publications relating to the results of CENTAUR are available through an open access route and will be listed on the CENTAUR page of the OpenAIRE portal. The co-ordinator will collate a list of all data collected during the project and will require partners to declare whether data is open access or restricted in line with the policy outlined in the Data Management Plan. Access to Open data will be unrestricted, apart from where an embargo period is deemed necessary to allow academic publications to be finalised. Appendix A of the Data Management Plan will list all completed data sets and their availability. The co-ordinator will ensure that all open access data produced during the project is appropriately archived and will deposit this in an enduring open access repository. The data management plan will be reviewed periodically at each General Assembly and will contain a record of the data sets collected and the status of each data set as regards its availability. 8 References WaPUG, Code of Practice for the Hydraulic Modelling of Sewer Systems. Version Available at: Practice-for-the-Hydraulic-Modelling-of-Sewer-Systems.pdf WRc, A guide to short term flow surveys of sewer systems. Swindon: WRc Engineering. 16

17 Appendix A. Register of Completed Datasets Date added to Data Register Lead Partner Description of Data (Data, metadata, format and size) Status of Data (Open/Restricted) Justification of Status / Other comments Location of Data 03/10/2016 UoC Flow survey data for development of the dual drainage model. Flow and water level data at various locations in the Coimbra sewer network. Text and spreadsheet format, several hundred megabytes in total. Restricted Cannot share vital metadata, see Data may identify individual property s flood risk personal data. UoC 17

18 Appendix B. Example of Proposed Metadata for Open Access Data B.1 Metadata within the main Zenodo record Digital Object Identifier: /Zenodo.xxxxxx Publication date: YYYY-MM-DD Title: Laboratory Testing of Centaur System ver 1.0 Authors and Affiliations: Mohamad Abdel-Aal, University of Sheffield Will Shepherd, University of Sheffield James Shucksmith, University of Sheffield Simon Tait, University of Sheffield Description: The laboratory facility consists of a 30 m long sewer pipe, 0.2 m in diameter with four manholes. Each manhole is 1.5 m high and 1 m in diameter. Water is pumped into the system by two submersible pumps capable of a combined output flow of 50 l/s, with the flow rate controlled by butterfly valves after each pump. A further butterfly valve, at the downstream end of the 0.2 m diameter sewer pipe controls the water depth in the pipe. The butterfly valves are controlled by a LabVIEW programme. A flow control device (FCD) (Steinhardt ElectroSlide 200) with 0.2 m gate diameter is installed in the third manhole and controlled by a Fuzzy Logic control algorithm developed by the CENTAUR partners. Figure 1 shows the layout of the laboratory setup. The facility is instrumented with pressure transducers measuring water depths in the third (control) manhole upstream of the FCD and the fourth (flood location) manhole. Water level data is collected at 0.1 Hz and the FCD control algorithm runs every 60 seconds. A variety of different downstream valve closure profiles and flow rates have been tested and the results have been used to refine the control algorithm. Keywords: Urban Water Management, autonomous systems, real time control, sensors, urban flood risk, climate change adaptation, full scale laboratory facility, flow data, depth data. Additional notes: If required Access right: Open Access or Embargoed Access with release date License: Creative Commons Attribution Share-Alike 4.0 Communities: CENTAUR Cost Effective Neural Technique for Alleviation of Urban Flood Risk Grants: European Commission: CENTAUR - Cost Effective Neural Technique for Alleviation of Urban Flood Risk (641931)

19 B.2 Additional metadata as a pdf within the dataset Contact details: Mohamad Abdel-Aal, m.abdel-aal@sheffield.ac.uk Post-Doc Researcher responsible for data collection and storage Will Shepherd, w.shepherd@sheffield.ac.uk Post-Doc Researcher James Shucksmith, j.shucksmith@sheffield.ac.uk Senior Lecturer Simon Tait, s.tait@sheffield.ac.uk Project coordinator Brief Description of Experimental Set-up The laboratory facility consists of a 30 m long sewer pipe, 0.2 m in diameter with four manholes. Each manhole is 1.5 m high and 1 m in diameter. Water is pumped into the system by two submersible pumps capable of a combined output flow of 50 l/s, with the flow rate controlled by butterfly valves after each pump. A further butterfly valve, at the downstream end of the 0.2 m diameter sewer pipe controls the water depth in the pipe. The butterfly valves are controlled by a LabVIEW programme. A flow control device (FCD) (Steinhardt ElectroSlide 200) with 0.2 m gate diameter is installed in the third manhole and controlled by a Fuzzy Logic control algorithm developed by the CENTAUR partners. Figure 1 shows the layout of the laboratory setup. The facility is instrumented with pressure transducers measuring water depths in the third (control) manhole upstream of the FCD and the fourth (flood location) manhole. Water level data is collected at 0.1 Hz and the FCD control algorithm runs every 60 seconds. A variety of different downstream valve closure profiles and flow rates have been tested and the results have been used to refine the control algorithm. Figure 1: Laboratory setup, MH stands for manhole. 19

20 Sensors The laboratory facility has three sensors installed to record flow and water depths. An electromagnetic flow meter is installed in the primary supply pipe, allowing flows up to 22 l/s to be recorded. Two pressure transducers are installed, one in manhole 3 and one in manhole 4. Details of these sensors are shown in Table 1. Table 1: Sensors specifications Sensor type Manufacturer / model Operating principle Units Accuracy Resolution Pressure transducer Keller / Series 26 Y Piezo-resistivity effects m +/- 0.5 % 0.01 m Electromagnetic flow meter Arkon / MAG X2 Faraday's law of electromagnetic induction l/s +/- 2 % l/s Test Parameters. The tests were carried out using different downstream valve profiles and various constant and variable flow rates. The test parameters are recorded in the spreadsheet CENTAURLAboratoryTestData.xlsx and information on the recorded parameters is summarised in Table 2. Table 2: Parameters recorded for each laboratory test Parameter Units Comments Test ID N/A Identification number of each test in chronological order Date N/A Date when the test was carried out in dd/mm/yyyy format Start time N/A Start time of the test in HH:MM:SS End Time N/A End time of the test in HH:MM:SS Flow or Valve profile? D/S Valve opening or profile name N/A ma or N/A Flow means variable flow was used in the test. Valve indicates variable downstream valve profile. Fixed opening in ma or variable opening following named profile Flow rate or profile name l/s or N/A Fixed flow rate in l/s / variable opening following named profile D/S valve profile step s Time step between rows in the named valve profile Flow profile step s Time step between rows in the named flow profile PLC status N/A Auto: FCD is controlled by CENTAUR algorithm. Manual: FCD position is set manually Comments N/A Brief notes about the test aim and performance Sampling interval seconds Frequency at which water level and flow data is recorded Table 3 shows an example of data defining a triangular shaped flow profile where the flow rises from an initial steady flow to a peak flow in Time rising then returns to the initial flow rate in Time dropping. 20

21 Table 3: Example of data defining a time carrying flow profile Profile Initial flow (l/s) Time rising (s) Peak flow (l/s) Time dropping (s) Data storage format Data uploaded to repository is all in csv format with one row of data per time stamp. An example row of data, with headers is shown in Table 4. Table 4: Example of water level data Timestamp MH3 Water Level MH3 Water Level MH4 yyyy.mm.dd HH:MM:SS m m ' :55:00'