This area includes the deliverables of the SHELTER project.

D1.1 - Data sources and Knowledge
Lead partner SISTEMA
This deliverable describes the “Identification of data and knowledge sources and integration and interoperability requirements” activities and outcomes with a focus on the identification, classification and evaluation of the data sources considered useful for Shelter scopes and on the applied methodology.
D1.2 - Building of best/next practices observatory
Lead partner UNIBO
The overall objective of this report is to provide an effective codification of existing knowledge. This is achieved by adapting existing ontologies, building of a lesson learned and next practices observatory based on existing best practices on adaptive governance for cultural heritage management, local knowledge and historical event.
D1.3 - Data Lake
Lead partner LINKS
This deliverable describes the data lake structure and the data lake model. The data lake is the concept chosen in SHELTER to manage the huge amount of heterogeneous, geospatial, non-geospatial, structured and unstructured knowledge collected and generated during the project activities. The data lake approach is the response to the need of a dynamic, flexible, scalable and continuously evolving data model to exploit and take the maximum benefit from existing social knowledge and the knowledge generated within the project by means of co-creation processes.
D1.4 - Multiscale data model
Lead partner EGIS
This deliverable describes the data models that will be implemented to share and visualize georeferenced data for the Open Labs. The complexity of the CHM domain implies a multisource approach that takes into account the temporal, the spatial, the social and the cultural dimensions adapted to different scales from city to region in different levels of detail. The multiscale-multisource data model is the way the data lake content will be spatially exploited by the consortium and by the stakeholders.
D2.1 - HA Resilience structure
Lead partner TECNALIA
This deliverable defines the strategy for the integration of the different project methodological results in the SHELTER operative knowledge framework. The workflow and the dimensions for developing the framework has been established defining the interplay (output and inputs) of the Open Labs and data driven platform.
D2.2 - HA Systemic resilience assessment and monitoring framework
Lead partner CRCM
This deliverable developed the multiscale indicator that will be the basis for the risk dependent resilience assessment based on hazard, exposure and vulnerability (of single risk and combinations of risks) at artefact, building and district scale but also for the generalised multiscale resilience.
D2.3 - Anatomy of Historic Areas (HA)
Lead partner POLITO
This deliverable developed the multiscale indicator that will be the basis for the risk dependent resilience assessment based on hazard, exposure and vulnerability (of single risk and combinations of risks) at artefact, building and district scale but also for the generalised multiscale resilience.
D2.4 - Characterisation of hazards, Climate Change events and impacts
Lead partner TECNALIA
The deliverable describes the methodology for characterisation of hazards, climate change events and impacts and projections/scenarios. It classifies events and related impacts affecting Cultural Heritage identifying different time horizon scenarios and establishing what we know and do not know, making a distinction between known types of events, unknown types of events, and unexpected It will identify key uncertainties and possible gaps due to missing information. It comprises other non-climate stresses, such as the socio-economic impacts of Climate Change, including tourism, within the selected sites including the local knowledge extracted in Open Labs.
D2.5 - Specific Hazard risk assessment
Lead partner EKO
The deliverable describes a spatially explicit methodology to assess the risk regarding specific hazards and their synergistic impact based on the results of D2.2 “HA Systemic resilience assessment and monitoring framework”, its application to case studies and its fine tuning. It includes the procedure definition with the identification of required/existing data sources, the definition to detect the techniques and needs for transform, standardise and impute missing values, the algorithms and multiscale data analytics and geospatial computing required for indicators calculation; and the methods for weighting and combining vulnerability/resilience factors and categorizing and performing sensitivity analysis.
D2.6 - Agent Based Modelling for scenario analysis
Lead partner EKOU
The report describes the scenario simulation methodology using Agent Based Modelling (ABM) regarding the preparedness of agents to cover spatial and temporal patterns in case of the occurrence of disruptions. It describes, as well, the results of the simulations to determine and compare parameters such as fatality number, injury number, total number of citizens exposed to disaster, financial impact and recovery rate provided and complete recovery time needed after the event and the evaluation of preparedness in terms of infrastructure and equipment, communication needs, administrative and insurance preparedness and recovery scenarios.
D2.7 - Historic Areas Systemic Resilience Index
Lead partner TECNALIA
The deliverable defines the procedure for the implementation of the systemic resilience assessment methodology at Historic Area (HA) scale that will integrate the specific hazard risk assessment described in D2.5 as a nested concept and the results from Agent Based Modelling (ABM) (D2.6). The methodology for HA Resilience Index is described: i) integrating multidimensional resilience assessments results (building environment, cultural, social, governance and institutional resilience, economic and environmental resilience), ii) identifying the required data analysis and index computation, and iii) performing sensitivity and uncertainty analysis.
D4.1 - Resilience ID incremental strategy
Lead partner TECNALIA
This deliverable includes the detailed definition of the incremental strategy for the implementation of the Resilience ID, the workflow to generate it using the Data Driven Platform, the structure of the information and the visualisation in the multiscale data model.
D4.2 - Strategy for early recovery roadmap
Lead partner UNIBO
The deliverable provides a guideline for identifying acceptable, effective and pre-planned strategies to generate a roadmap that will be tested in each cases study through Open Labs (OLs), including guidelines for identifying acceptable and effective and pre-planned strategies. It defines the use of Resilience ID (D4.1) and the back-up models for the identification of relevant information necessary for the reconstruction process.
D6.1 - GLOCAL user requirements
Lead partner CRCM
The deliverable identified GLOCAL user requirements for Disaster Risk Management and Climate Change Adaptation to heritage looking at the bottom-up (local) and top-down (global) levels. Identification is based on the use case scenarios, ex-post analysis and international experience.
D6.2 - ICT-community interaction rulebook
Lead partner ULIEGE
The deliverable outlines the development of a community interaction rulebook (CIR) aiming to explore the role of information communication technology (ICT) in adaptive governance and identifies some key ‘rules’ to guide the development of the Open Labs within the SHELTER Project.
D6.3 - Adaptive Governance Schemes Mapping
Lead partner ULIEGE
This document provides a visual mapping of the different types of governance structures applicable at different stages of the Disaster Risk Management (DRM), with a detailed description of their advantages and limitations. Linked with the document, the Toolkit for Cultural Heritage Stakeholders to Map Governance Structures using the Organigraph technique.
D6.4 - Historic Areas resilience co-production playbook
Lead partner CRCM
The deliverable details the co-creation strategies blueprints that cover diverse hazards, Historic Areas typologies, Disaster Risk Management phases and type of solutions.
D6.5 - Methodology for Local Knowledge extraction
Lead partner POLITO
The deliverable defines a theoretical and practical framework to include and take into account those informal knowledge and local factors that represent the peculiar long-lasting interaction of the communities with their environment, providing tools for extracting Local Knowledge, Sense of place and Peer learning addressed to local stakeholders in Open Labs.
D8.1 - Dissemination and communication plan
Lead partner EURONET
The deliverable serves as a guideline for the promotion activities carried out by SHELTER Consortium, including a scouting of relevant conferences, workshops, events and journals aligned with the project scopes.
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