Introduction to Agriculture & Food Safety Data

Introduction to Agriculture & Food Safety Data

Vassilis ProtonotariosAgro-Know

2nd Sem

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Hackathon (in conjunction w

ith IRSS14)supported by:

Intro to the intro

This presentation aims to:

• Provide basic information regarding the various sources of agricultural and food safety data• ranging from definitions to actual data sources, data types and

attributes

• Highlight issues related to the management and use of this kind of data and possible solutions and ideas for the exploitation of such data

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why agricultural/food data?

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ackathon (in conjunction with IRSS

14)Agriculture is about to experience a “growth shock” in order to cover the exponentially increasing food needs of the global population

• All demographic and food demand projections suggest that, by 2050, the planet will face severe food crises due to our inability to meet agricultural demand – by 2050:

• 9.3 billion global population, 34% higher than today• 70% of the world’s population will be urban, compared to 49%

today• food production (net of food used for biofuels) must increase by 70%

• According to these projections, and in order to achieve the forecasted food levels by 2050, a total investment of USD 83 billion per annum will be required

• A large part of this investment will need to be focused on R&D

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Key facts about agricultural trends

One of the most promising routes to agriculture modernisation is the provision of Open Data to all interested parties

• In an era of Big Data, one of the most promising routes to achieve R&D excellence in agriculture is Open Data, and in particular:• provisioning, • maintaining,• enriching with relevant metadata and• making openly available a vast amount of open agricultural data

• The use and wide dissemination of these data sets is strongly advocated by a number of global and national policy makers such as:• The New Alliance for Food Security and Nutrition G-8 initiative• FAO of the UN• DEFRA & DFID in UK• USDA & USAID in the US

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IRSS14)Open Data in Agriculture

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why open data?

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open: definition

“Open data is data that can be freely used, reused and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike”

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Why open data?

• Open data, especially open government data, is a tremendous resource that is as yet largely untapped• individuals and organisations collect broad range of

different types of data to perform their tasks

• Government is particularly significant in this respect• quantity and centrality of data it collects• most is public data by law, could be made open and

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Closed data

Examples

…always bad?

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in agriculture: a political priority

“How Open Data can be harnessed to help meet the challenge of sustainably feeding nine billion people by 2050”

29-30/4/2013, Washington D.C., USAhttps://sites.google.com/site/g8opendataconference/home

about agricultural data

agricultural science

biodiversity

examples of variety & diversity

data sets

maps

photos

databases

• publications, theses, reports, other grey literature• educational material and content, courseware• primary data, such as measurements & observations• structured, e.g. datasets as tables• digitized, e.g. images, videos

• secondary data, such as processed elaborations• e.g. dendrograms, pie charts, models

• provenance information, incl. authors, their organizations and projects• experimental protocols & methods• social data, tags, ratings, etc.• …

research(+) content

where can I find this data?

Where to use this data?

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there is more…

…and more…

…and much much more

About food (safety) data

Data sources

Data sources

Using open data & knowledge sharing in agro-food sector

using open data to build an open and scalable infrastructure for food safety

using open data to support decision making for regional growth

browse agricultural resources and activities by geographical region to understand opportunities for grows at regional level

using open educational data to support training on organic agricultural

localize to specific region by adapting content and using state of art language technologies

localizing open educational data to train the trainers

organizing events to spur innovation

challenges creativity

excellencehack using open data

transferring innovation to the regional ecosystem

collaboration with stevianet.gr experiment

citytofarm.grplatform for ag-machinery sharing

accessing the data

How to get this data?

•APIs• SPARQL endpoints•OAI-PMH (for metadata)•HTML / data scraping•………

so, what’s the catch?

open data is not always ready to be used….

• Messy data• Should be collected/fused• Should be filtered• Should be validated• Should be enriched with metadata to become

discoverable• Should be standardized to allow interoperability

plug and play?•No!• requires a deep understanding of the data• requires excellent data processing & analysis skills• requires very good technical skills

•will evolve into a data-powered value chain• the companies that develop innovative agro/ food products

(agro apps consumers) need…• …companies that build apps on agro data (agro data

consumers, agro apps producers) who need…• companies that process agro data (data science powered)

thank you!

[email protected] http://www.agroknow.gr

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