20141030 linda workshop echallenges2014 - environmental pilot

Workshop 8d, 30 October 2014 eChallenges e-2014 Copyright 2014 , Ubitech Ltd.

Linked Open Data for EU SMEsThe case of Environment Analytics

Anastasios Zafeiropoulos, Ubitech Ltd./R&D [email protected] Zanetti, Hyperborea


Environment Analytics Pilot

– Work on elaborating datasets that describe the ecological status of provinces in Italy based on various parameters related to polluting emissions, waste production, water discharge, water sample etc.

– Objective: use these data in order to proceed to analysis and extract conclusions about the health impact of environmental pollution in Italy taking into account the climate conditions in each area. – examine frequency and type of occurrence of diseases in specific

geographical areas in correlation with environmental conditions and indicators for pollution in the area.

– examine epidemiological incurrences and factors.– realise risk management and forecasting analysis


Environment Analytics Pilot

• Series of health problems in areas with augmenting concentration of dangerous components in the air, water and terrain, biodiversity loss as well as the wide publication of this issue at the media.

• Italian case of the triangle of death (Italian: Triangolo della morte) – increasing deaths caused by cancer and

other diseases that exceeds the Italian national average.

– mainly caused by pollution from illegal waste disposal.


Challenges

• Private datasets: part of the datasets are not publicly available. • Spatial statistics: geo-location data are considered crucial towards

analysing the impact of pollution in health of citizens in various areas.• Quality and Accuracy of data as well as differences in their

interpretation within heterogeneous databases consist important factors that affect the analysis’ results.

• Process:– access to series of data covering different decades of years;– capacity to register cases of mortality, diseases, etc.; as well as pollution

relevant data (e.g. wastes, air pollution)– capacity to geo-localise those cases (spatial statistics are considered

crucial for these studies);– capacity to realize correlation and forecasting analysis.


Datasets (1)

– Generic/ Environmental/Health – National/ International– I.Stat - National Institute of Statistics in Italy

– environmental indicators, health indicators and demographic indicators

– I Tumori in Italia – estimates of incidence, prevalence and mortality for several

locations broken down by age, region and macro area

– ITACAN - Italian Association of Cancer Registries– key epidemiological indicators of the most common cancers based

on the data of the Italian Cancer Registries

• ISS - Istituto Superiore di Sanità– description of the mortality observed in Italy in the period 1980-2011


Datasets (2)

– SIRA - Sistema Informativo Regionale dell'Ambiente della Toscana– Water monitoring parameters regarding surface water, groundwater

and coastal waters.

– UNEP and its partners in the Global Environment Outlook – Freshwater, Population, Forests, Emissions, Climate, Disasters,

Health and GDP

– World Bank Open Data – data for environment, climate change and health

– Private datasets in collaboration with scientists


Analysis Subjects

• There is any correlation among the pollution levels in an area, the climate conditions, demographic characteristics and the incidence of diseases (especially those related with cancer) in the population?

• There is any correlation among part of the above-mentioned parameters?

• How we may find abnormalities (anomalies) in the instances of diseases during the years?

• When the change in the number of instances can be considered to have epidemiological characteristics?


Analysis Subjects

• What estimates may we produce regarding the evolution of the instances of diseases the upcoming years?

• Does it exist any type of correlation on the instances of diseases in areas with similar climate condition and pollution levels?

• Can we assume the existence of clusters with similar characteristics or trends with regards to the expansion of diseases?

• What kind of preventive actions can be undertaken in cases with large number of incidents or pessimistic predictions in order to restrict the spreading of specific diseases?


Analysis/Algorithms

• Point pattern analysis, geo-statistics and geographic correlation studies – study the geographical factors and their effects on geographically

differentiated health outcomes

• Disease mapping and analysis – visual representations of geographic data and disease maps– survey high-risk areas and help policy formulation

• Spatial regression – take account of the lack of independence that typically exists

between measurements made at nearby locations.

• Clustering and association algorithms– detect areas that present similar trends and commonalities in the

identified incidents (identify disease clusters, or spatial groupings of proximity and characteristically related epidemics).


Collaborations

• SDI4APPS project– Expression of interest from SDIAPPS SMEs– Signed MoU

• LIFE project in Italy - http://www.hia21.eu/en/index.php– The goal of the project is the application of the Health Impact

Assessment (HIA) procedure, integrated with Local Agenda 21 practices, the assessment of current and future impacts of urban waste cycle planning and management policy.

• Instituto di Fisiologia Clinica of National Research Council in Pisa

• Interaction with scientists worldwide

info @

LinDA-project.eu

@LinDA_FP7

+

LinDA-project.eu

LinDAFP7

Thank you! Questions? Anastasios Zafeiropoulos| [email protected]

Senior R&D Architect

Ubitech Ltd.| www.ubitech.eu

20141030 linda workshop echallenges2014 - environmental pilot

Presentations & Public Speaking