Use Cases

The following scenarios highlight the benefits of acquiring a dataset from the BigDataGrapes data marketplace.

Scenario 1: Get the interconnected dataset that you need to build prediction models
Download a structured BigDataGrapes dataset with historical fraud cases reported for wine and use it to identify trends, study correlations between incidents and origin of the wine and apply your prediction models to predict events in the grapevine supply chain. The  dataset acquired by the marketplace combines unstructured data that is published by numerous National Authorities. You can use this dataset to build your models without spending time and resources to align data from all the different open data sources.

Scenario 2: Submit your unstructured data and get predictions

Upload your laboratory testing results for pesticides identified in grapes and combine them with millions of test results that the big data platform has. By submitting the data to the big data platform, your dataset will gain value since it will be transformed to an open and structured format, it will be enriched and combined with existing data for grapes and the BigDataGrapes prediction models will be used to produce a forecast of the results for the next 12 months.

Scenario 3: Combine different types of data to test hypothesis of the grapevine industry

The BigDataGrapes marketplace includes datasets for numerous data types that are semantically enriched and aligned. This means that you can combine the IoT dataset, with the laboratory testing results dataset and a food safety incidents dataset in order to test hypothesis about the correlation between different factors and stages of the grapevine supply chain.

How the BigDataGrapes datasets are compared to existing open source datasets for the grapevine industry

Lets see through an example from the food safety sector, why an expert working and/or conducting research in the grapevine industry, should acquire a dataset from the BigDataGrapes marketplace and which are the differences with the original source.

Open data sources such as the Rapid Alert System for Food and Feed (RASFF), provides  data with food safety incidents for products like wine which includes only reports collected from the European Authorities and it does not include critical information such as details about the company that has been involved in the food safety incident and the product brand.

BigDataGrapes dataset for food safety and fraud incidents in grapes, is a linked dataset that combines the very important dataset of RASFF with data from numerous Authorities from all around the world. Furthermore, it is a more rich dataset as it includes information about the company and details about the product brand.