An example scenario where this technology would be useful is in an outbreak investigation. Many epidemiologists are familiar with the food borne outbreak in Oswego, New York, U.S.A. on April 18th, 1940. In this outbreak, 75 of the 80 people known to have been present at the pot-luck church supper were interviewed. A survey was created and interviews were conducted with participants to determine the source of the contamination. While the Oswego study focused on a single region, the significant value of data synchronization can be seen by expanding this scenario to where interviews and data entry are conducted in different localities. Therefore, imagine that the Oswego church supper was attended by residents of the Oswego county and four other neighboring counties: Jefferson, Lewis, Oneida, and Wayne. Imagine two epidemiologists are investigating this outbreak; an Epidemic Intelligence Service (or EIS) officer investigating the outbreak in Oneida county and another officer at the state health department investigating the other counties. After data synchronization, both investigators will have a clear picture of the spread of the illness over space and time and the actual cause of the outbreak.