The WorldFAIR Webinar Series: Guidelines and Recommendations from Population Health and Urban Health

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The WorldFAIR Webinar Series: Guidelines and Recommendations from Population Health and Urban Health
08 Nov 2023 UTC

The WorldFAIR Webinar Series: Guidelines and Recommendations from Population Health and Urban Health

08 Nov 2023

8 November, 12:00 UTC 

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This webinar, part of the WorldFAIR series presenting project outputs, will discuss the published deliverables of the WorldFAIR Case studies in Population Health and Urban Health.


Welcome to the WorldFAIR webinar series Alex Delipalta, (RDA Europe)
Implementation Guidelines for Annotating Population Health Research Data Jim Todd (LSHM), Keith Tomlin, (LSHM)
Urban Health Data Mapping and Assessment: Guidelines and Recommendations Ana Ortigoza (Drexel University)
Ran Li (Drexel University)
Panel Discussion Jim Todd (LSHM), Keith Tomlin, (LSHM), Ana Ortigoza (Drexel University), Ran Li (Drexel University), Bilal Usama (Drexel University)
Audience Q&A  

About the case study on Population Health

The Implementation Network for Sharing Population Information from Research Entities (INSPIRE) project is assembling technologies and standards in support of a data hub that facilitates federated and/or shared research capable of interoperating across often-neglected low-resource settings: it aims to provide a platform-as-a-service, which can make data of disparate types available to many different styles of analysis, among which AI systems are increasingly prominent.

INSPIRE uses OMOP, a common data model that is becoming the gold standard for systematically integrating health data from disparate sources and conducting observational research at scale using routine clinical care data. However, OMOP is not completely FAIR and further work is needed to improve the ability to integrate diverse sources of data.

This case study works on improving the interoperation of OMOP with other standards to enable machine-actionable descriptions of data structure and provenance (e.g., DDI-CDI, PROV-O, SDTL); the composition of measurements focused on the objects of research (e.g., I-ADOPT); record linkage modeling for creating and evaluating bridges that connect domains, vocabularies (e.g., SKOS); and data discovery (e.g.,, DCAT). This suite of standards forms the basis of an ‘AI-Ready’ description of data suitable for use across domain and institutional boundaries.

About the case study on Urban Health

Cities are considered the primary contributors to global environmental change and human development, being at the centre of leading mitigation and adaptation strategies that could promote human health along with environmental sustainability. Given the transdisciplinary approach of Urban Health, challenges faced within this field are also common to other areas and consequently, solutions proposed from the Urban Health perspective could also promote advancement beyond its discipline.

The SALURBAL project (Urban Health for Latin American cities) is a five-year project based at the Urban Health Collaborative, Drexel University, and with partners throughout Latin America and in the United States that studies how urban environments and urban policies impact the health of residents from almost 370 cities in 11 Latin American countries.

The SALURBAL project 1) has systematized a process for city definition and operationalization that integrates multiple ways in which a city can be delimited; 2) has created a data structure that allowed the incorporation of data from different sources, making it shareable across several cores and disciplines; and 3) has developed procedures and standards that systematically documented issues related to data access, quality, and completeness during the process of data harmonization.

The case study will explore and further refine this approach to provide recommendations for urban health data that reflect the FAIR and CARE principles and contribute to promote best practices in data sharing and use within and beyond the Urban Health field.