Editing Mika/Temp/WikiFCD/Grants (section)

=Outputs=
* list products and other outputs
* Wikibase instance with FCD data from multiple sources
* SPARQL query code to combine this data with subsets of Wikidata data
* Data models for food items, food composition tables, recipes, and other resources encoded as ShEx schemas
* Visualizations of this data

The primary output of this work is a knowlege graph of structured data published in a publicly-avilable instance of the Wikibase platform. Wikibase is a set of extensions to the MediaWiki software platform and is developed by the Wikimedia Foundation as free software [https://www.mediawiki.org/wiki/Wikibase].  Wikibase is a novel infrastructural platform for data management suitable for data from many domains. This is the first application built on Wikibase tailored to the needs of the epidemiological community. The output of this research will be a knowledge graph of structured data in the form of a Wikibase instance populated with data from heterogeneous food composition tables. 

Multiple data visualization options are available via the Query Service of our Wikibase instance. The Query Service is a SPARQL endpoint which supports querying the data in the knowledge graph via the SPARQL query language [https://www.w3.org/TR/sparql11-query/]. Graphs, charts, network diagrams, and maps are some of the visualizations we will be able to offer end-users of this knowledge base.  

* Case Study One: Fermented foods
The nutrient composition of fermented foods commonly changes as the fermentation process progresses. We will select 15 fermented foods to use in a case study of modeling nutrient composition that changes over time. We will develop an algorithm for use in our Wikibase for converting a set of food items into a fermented food recipe that will result in accurate nutrient information for the dish. 

* Case Study Two: Time Series Data
Agricultural practices, local conditions, and global weather patterns all influence nutrient density in food crops. Designing a data model to represent time series data will allow us to track changes in nutrient density over time. For example, we have designed our knowledge base to accommodate nutrient composition data for a single varietal of a species grown on the same farm that is re-analyzed yearly for nutrition information. 

* Case Study Three: Georeferenced Data
Wild food is food that is gathered from the environment rather than cultivated agriculturally. The nutrient composition of wild foods are determined by the ecology of their location. Building a data model for georeferenced data will allow us to track the coordinate locations of wild food item sources. In this way we will be able to document the location of harvest and combine that with the nutrient composition way at the level of the statement of each fact. Each harvesting episode for which we have nutrient composition data will be modeled individually, as we acquire additional data for wild harvests, we will be able to compare the nutritional information across spaces as well as time.