A JSON protocol for sharing and storing real-time data streams. Common use would be for sharing location data.

json format for geo data

Common minimal format for sending just lat/long data
[
	{
		uuid: "550e8400-e29b-41d4-a716-446655440000",
		date: "2010-04-30T16:50:00Z",
		location: {
			position: { 
				latitude: 45.5118,
				longitude: -122.6433
			}
		},
		client: {
			name: "Geoloqi",
			version: "0.1",
			platform: "iPhone OS 4"
		}
	},
	{
		uuid: "550e8400-e29b-41d4-a716-446655440001",
		date: "2010-04-30T16:50:00Z",
		location: {
			position: { 
				latitude: 45.5128,
				longitude: -122.6435
			}
		},
		client: {
			name: "Geoloqi",
			version: "0.1",
			platform: "iPhone OS 4"
		}
	}
]

Full data format allowing custom information to be included based on source of location data
[{
	uuid: "550e8400-e29b-41d4-a716-446655440000",
	date: "2010-04-30T16:50:00Z", (iso8601 format)
	location: {
		position: {
			latitude: 45.5118,
			longitude: -122.6433,
			geojson: {
				type: "Polygon",
				coordinates: [[-122.643, 45.512], [-122.650, 45.512], [-122.643, 45.533], [-122.650, 45.533]]
			},
			altitude: null,
			heading: 190,
			speed: 56,
			horizontal_accuracy: 6.0,
			vertical_accuracy: 8.0 (in meters)
		}
		source: "hardware_gps,wifi,street_address,agps,twitter,foursquare,geomena"
		type: "latlng,address,neighborhood,city",
		raw: (from hardware gps device) {
			dop_h: 2.7,
			dop_v: 2.1,
			satellites: []
		},
		raw: (from wifi positioning) {
			aps: []
		}
		raw: (from twitter) {
			id: "103994853",
			created_at: "Tue Apr 07 22:52:51 +0000 2009",
			text: "At least I can get your humor through tweets. RT @abdur: I don't mean this in a bad way, but genetically speaking your a cul-de-sac.",
			source: "<a href="http://www.tweetdeck.com/">TweetDeck</a>",
			....etc....
		}
	},
	client: {
		name: "Geoloqi",
		version: "0.1",
		platform: "iPhone OS 4",
		other: "whatever"
	},
	environment: {
		air_temperature: {
			celsius: 20.3
		},
		humidity: {
			percent: 80
		},
		sound_pressure_level: {
			pascals: 10
		}
	},
	body: {
		heart_rate: {
			bpm: 100
		},
		core_temperature: {
			celsius: 25
		}
	}
}]


Format for querying positions of multiple users:
[{
	user: {
		id: "http://aaron.pk",
		display_name: "aaronpk",
		url: "http://aaronparecki.com",
		image_url: "http://aaron.pk/pic.jpg"
	},
	data: []
},
{
	user: {
		id: "@caseorganic",
		display_name: "caseorganic",
		url: "http://oakhazelnut.com",
		image_url: "http://a1.twimg.com/profile_images/116264220/kk-caseorganic-48px.jpg"
	},
	data: []
}]

I wonder if a collection of checkins could be of use in implementing a sort of differential correction. Location accuracy might be able to be increased by comparing some aspect of the user's perspective to the same aspect of nearby checkins.

For example, if nearby checkins included a photograph of some fixture in the users' environment (like a building with distinctive lines, a rock formation, a fiducial marker) along with camera inclination and heading, it might be possible to narrow down the user's current position.

Could a checkin leave behind some kind of breadcrumb (like correction data) that improves future checkin accuracy?