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Big Data opportunities for marketing of
horticultural products
“Lightning talk” in the workshop on “Big data for food,
agr...
Issues w.r.t. management
 Market orientation of the horticulture sector can be
enhanced:
● Many growers are production or...
Issues w.r.t. data
 Available statistics do not present the level of detail
required for management decisions
● E.g., pro...
Big Data opportunities
 Current detailed data on production, stocks, and
(expected) supply are abundant in many public an...
Relevant data for horticultural markets
 External factors affecting supply and demand:
● Weather conditions, exchange rat...
Market information for the horticulture
sector: Big Data challenges
 Data are present in public administrations, but not ...
The BIGt&u project
 A Dutch public-private partnership
 To develop an infrastructure for market information
 Access a d...
Consortium
 Knowledge institutions: fundamental and applied
research (Agriculture, IT, Data Analytics)
 Organizations an...
9
Work packages
1. Research on Semantic Technologies for data access and
data integration
2. Research on Social Media filter...
Uniform interface and standard classifications for apps and ERP
Conceptual architecture
11
Social Media - Unstructured - E...
Information
tim.verwaart@wur.nl
12
Efficient, uniform access to a wide
variety of sources for market data
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SC2 Workshop 1: Big Data opportunities for marketing of horticultural products

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“Lightning talk” in the Big Data Europe (BDE) workshop on “Big data for food, agriculture and forestry: opportunities and challenges” taking place on 22.9.2015 in Paris by Tim Verwaart (Wageningen UR).

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SC2 Workshop 1: Big Data opportunities for marketing of horticultural products

  1. 1. Big Data opportunities for marketing of horticultural products “Lightning talk” in the workshop on “Big data for food, agriculture and forestry: opportunities and challenges” INRA, Paris, 22 September 2015, Tim Verwaart
  2. 2. Issues w.r.t. management  Market orientation of the horticulture sector can be enhanced: ● Many growers are production oriented ● For many traders, their transactions are the main source of information  No tradition of data based supply planning  Reactive management, little anticipation 2
  3. 3. Issues w.r.t. data  Available statistics do not present the level of detail required for management decisions ● E.g., product categories: “Pears” versus varieties like Beurré, Williams etc.  Available data are not current, e.g. export statistics  Growers and traders lack data about consumer trends and how the products are used and appreciated 3
  4. 4. Big Data opportunities  Current detailed data on production, stocks, and (expected) supply are abundant in many public and private sources  Social Media: ● Data on consumers’ appreciation and applications of products are abundant in Social Media ● Growers’ communications in Social Media indicate future supply  Analytic methods to interpret the data are advanced
  5. 5. Relevant data for horticultural markets  External factors affecting supply and demand: ● Weather conditions, exchange rates, energy prices  Consumption: ● Market research, retail sales data, Social Media  Production: ● Areas/capacities, actual production, forecasts, FADN  (International) trade: ● Import/export statistics, phytosanitary certification requests, stocks, expected arrivals at (air)ports  News media: ● News about health aspects; food safety incidents 5
  6. 6. Market information for the horticulture sector: Big Data challenges  Data are present in public administrations, but not open ● Governments promote Open Data, but at a lower level many obstacles must be overcome ● Entrepreneurs are concerned about competitive relations  Semantic heterogeneity (in product classifications, etc.)  Many SMEs in this sector have limited capacity to invest in the IT required for Big Data applications, including the collection of relevant Social Media data and semantic integration of data from a diversity of sources 6
  7. 7. The BIGt&u project  A Dutch public-private partnership  To develop an infrastructure for market information  Access a diversity of data sources  Collect and structure data from Social Media  Provide mappings between classifications of products etc.  Offer a uniform interface with standard classifications  Boost applications of market data  Enhance market orientation & data based supply planning  Minimize investment cost for individual SMEs 7
  8. 8. Consortium  Knowledge institutions: fundamental and applied research (Agriculture, IT, Data Analytics)  Organizations and companies from horticulture and IT sectors  Cooperation between fruit/vegetables and flowers/ornamental plants subsectors  Participation of government and public data suppliers 8
  9. 9. 9
  10. 10. Work packages 1. Research on Semantic Technologies for data access and data integration 2. Research on Social Media filtering and real-time clustering 3. Data source descriptions (metadata) and mapping of classifications 4. IT architecture and development of software and other infrastructure 5. Social, legal, and financial aspects (competition, data usage rights, business case) 6. Application prototyping and community building across horticulture and IT sectors 10
  11. 11. Uniform interface and standard classifications for apps and ERP Conceptual architecture 11 Social Media - Unstructured - Event-driven Systems – Structured - Transaction-driven Topics Trends Alerts Norms Transactions Registrations Anonimize Aggregate Map Collect Filter Cluster BUSINESS EDUCATION RESEARCH SUPPLY CHAINCONSUMERS
  12. 12. Information tim.verwaart@wur.nl 12 Efficient, uniform access to a wide variety of sources for market data

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