diff --git a/backend/promis/backend_api/fixtures/init_data.json b/backend/promis/backend_api/fixtures/init_data.json
index 33cc05d..3745779 100644
--- a/backend/promis/backend_api/fixtures/init_data.json
+++ b/backend/promis/backend_api/fixtures/init_data.json
@@ -1,749 +1,1020 @@
-[
-{
-    "model": "backend_api.space_projecttranslation",
-    "pk": 1,
-    "fields": {
-        "name": "Potential",
-        "description": "The space scientific experiment \"Potential\" on the ionosphere aboard the Ukrainian Sich-2 microsatellite (2011-2012)",
-        "language_code": "en",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.space_projecttranslation",
-    "pk": 2,
-    "fields": {
-        "name": "\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b",
-        "description": "\u041d\u0430\u0443\u043a\u043e\u0432\u0438\u0439 \u0456\u043e\u043d\u043e\u0441\u0444\u0435\u0440\u043d\u0438\u0439 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u0438\u0439 \u0435\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442 \"\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\" \u043d\u0430 \u0431\u043e\u0440\u0442\u0443 \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u043e\u0433\u043e \u043c\u0456\u043a\u0440\u043e\u0441\u0443\u043f\u0443\u0442\u043d\u0438\u043a\u0430 \"\u0421\u0456\u0447-2\" (2011-2012)",
-        "language_code": "uk",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.space_projecttranslation",
-    "pk": 3,
-    "fields": {
-        "name": "Variant",
-        "description": "The space scientific experiment \"Variant\" on the ionosphere aboard the Ukrainian Sich-1M satellite (2004-2005)",
-        "language_code": "en",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.space_projecttranslation",
-    "pk": 4,
-    "fields": {
-        "name": "\u0412\u0430\u0440\u0456\u0430\u043d\u0442",
-        "description": "\u041d\u0430\u0443\u043a\u043e\u0432\u0438\u0439 \u0456\u043e\u043d\u043e\u0441\u0444\u0435\u0440\u043d\u0438\u0439 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u0438\u0439 \u0435\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442 \"\u0412\u0430\u0440\u0456\u0430\u043d\u0442\" \u043d\u0430 \u0431\u043e\u0440\u0442\u0443 \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u043e\u0433\u043e \u0441\u0443\u043f\u0443\u0442\u043d\u0438\u043a\u0430 \"\u0421\u0456\u0447-1\u041c\" (2004-2005)",
-        "language_code": "uk",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.space_project",
-    "pk": 1,
-    "fields": {
-        "klass": [
-            "classes.potential.Potential"
-        ],
-        "date_start": "2011-08-30",
-        "date_end": "2012-11-01"
-    }
-},
-{
-    "model": "backend_api.space_project",
-    "pk": 2,
-    "fields": {
-        "klass": [
-            "classes.variant.Variant"
-        ],
-        "date_start": "2005-02-01",
-        "date_end": "2005-03-25"
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 1,
-    "fields": {
-        "name": "Electric probe (EP)",
-        "description": "Electric probes are intended for the measurement of electric field intensity in space plasma with the help of two similar probes placed at a known distance. Potential project used a single probe setup that can be used to measure the spacecraft's own electric potential.",
-        "language_code": "en",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 2,
-    "fields": {
-        "name": "\u0415\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u0438\u0439 \u0437\u043e\u043d\u0434 (EP)",
-        "description": "\u0414\u0430\u0432\u0430\u0447 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 \u043f\u0440\u0438\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u043d\u0430\u043f\u0440\u0443\u0436\u0435\u043d\u043e\u0441\u0442\u0456 \u0437\u043c\u0456\u043d\u043d\u043e\u0433\u043e \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f \u0443 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u0456\u0439 \u043f\u043b\u0430\u0437\u043c\u0456 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u0434\u0432\u043e\u0445 \u043f\u043e\u0434\u0456\u0431\u043d\u0438\u0445 \u0434\u0430\u0432\u0430\u0447\u0456\u0432, \u0440\u043e\u0437\u043d\u0435\u0441\u0435\u043d\u0438\u0445 \u043d\u0430 \u0432\u0456\u0434\u043e\u043c\u0443 \u0432\u0456\u0434\u0441\u0442\u0430\u043d\u044c. \u0410\u043b\u0435 \u0432 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u043e\u043c\u0443 \u0435\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442\u0456 \u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b \u0432\u0456\u043d \u0431\u0443\u0432 \u043e\u0434\u0438\u043d :(",
-        "language_code": "uk",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 3,
-    "fields": {
-        "name": "Neutral gase parameters sensor (NCP)",
-        "description": "A system of two pressure probes using an inverse-magnetron converter as a sensor. (The device to produce the i/v characteristics from which the ITM team is to obtain the neutral gas density and pressure.)",
-        "language_code": "en",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 4,
-    "fields": {
-        "name": "\u0414\u0430\u0442\u0447\u0438\u043a \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0456\u0432 \u043d\u0435\u0439\u0442\u0440\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u0433\u0430\u0437\u0443 \u041d\u041a\u041f",
-        "description": "\u041d\u041a\u041f \u0441\u043a\u043b\u0430\u0434\u0430\u0454\u0442\u044c\u0441\u044f \u0437 \u0434\u0432\u043e\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 \u0442\u0438\u0441\u043a\u0443 \u0437 \u0456\u043d\u0432\u0435\u0440\u0441\u043d\u043e-\u043c\u0430\u0433\u043d\u0435\u0442\u0440\u043e\u043d\u043d\u0438\u043c \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u044e\u0432\u0430\u0447\u0435\u043c \u0432 \u044f\u043a\u043e\u0441\u0442\u0456 \u0447\u0443\u0442\u043b\u0438\u0432\u043e\u0433\u043e \u0435\u043b\u0435\u043c\u0435\u043d\u0442\u0443",
-        "language_code": "uk",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 5,
-    "fields": {
-        "name": "Plasma parameters sensor (ECP)",
-        "description": "A single cylindrical Langmiur probe measuring 0.05 cm in radius with 12 cm in length along with a protective electrode measuring 0.2 cm in radius and 12.5 cm in length. (The device to produce the i/v characteristics from which the ITM team is to obtain the plasma density and the electron temperature)",
-        "language_code": "en",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 6,
-    "fields": {
-        "name": "\u0414\u0430\u0442\u0447\u0438\u043a \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0456\u0432 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u043e\u0457 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u043f\u043b\u0430\u0437\u043c\u0438 (\u0415\u041a\u041f)",
-        "description": "\u041e\u0434\u0438\u043d\u0438\u0447\u043d\u0438\u0439 \u0446\u0438\u043b\u0456\u043d\u0434\u0440\u0438\u0447\u043d\u0438\u0439 \u0437\u043e\u043d\u0434 \u041b\u0435\u043d\u0433\u043c\u044e\u0440\u0430 \u0440\u0430\u0434\u0456\u0443\u043e\u043c 0,05 \u0441\u043c \u0456 \u0434\u043e\u0432\u0436\u0438\u043d\u043e\u044e 12 \u0441\u043c \u0437 \u043e\u0445\u043e\u0440\u043e\u043d\u043d\u0438\u043c \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u0434\u043e\u043c \u0440\u0430\u0434\u0456\u0443\u0441\u043e\u043c 0,2 \u0441\u043c \u0434\u043e\u0432\u0436\u0438\u043d\u043e\u044e 12,5 \u0441\u043c",
-        "language_code": "uk",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 7,
-    "fields": {
-        "name": "Set of 4 Electric probes (EZ1, EZ2, EZ3, EZ4)",
-        "description": "",
-        "language_code": "en",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 8,
-    "fields": {
-        "name": "\u041a\u043e\u043c\u043f\u043b\u0435\u043a\u0441 \u0437 4 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u0438\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 (EZ1, EZ2, EZ3, EZ4)",
-        "description": "",
-        "language_code": "uk",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 9,
-    "fields": {
-        "name": "\u041a\u043e\u043c\u043f\u043b\u0435\u043a\u0441 \u0437 \u0434\u0432\u043e\u0445 \u0445\u0432\u0438\u043b\u044c\u043e\u0432\u0438\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 (WZ1, WZ2)",
-        "description": "\u041a\u043e\u043c\u043f\u043b\u0435\u043a\u0441 \u0437 \u0434\u0432\u043e\u0445 \u0445\u0432\u0438\u043b\u044c\u043e\u0432\u0438\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 (WZ1, WZ2), \u0449\u043e \u0432\u0438\u043c\u0456\u0440\u044e\u044e\u0442\u044c \u0434\u0432\u0456 \u043e\u0440\u0442\u043e\u0433\u043e\u043d\u0430\u043b\u044c\u043d\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0437\u043c\u0456\u043d\u043d\u043e\u0433\u043e \u043c\u0430\u0433\u043d\u0456\u0442\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f (Bx, By) \u0442\u0430 \u0434\u0432\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0433\u0443\u0441\u0442\u0438\u043d\u0438 \u0437\u043c\u0456\u043d\u043d\u043e\u0433\u043e \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u0441\u0442\u0440\u0443\u043c\u0443 (Jxz, Jyz)",
-        "language_code": "uk",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.devicetranslation",
-    "pk": 10,
-    "fields": {
-        "name": "Set of 2 Wave probes (WZ1, WZ2)",
-        "description": "A complex of two wave probes (WZ1, WZ2) measuring two orthogonal variable components of the magnetic field (Bx, By) and two variable components of the current electric density (Jxz, Jyz)",
-        "language_code": "en",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.device",
-    "pk": 1,
-    "fields": {
-        "space_project": 1
-    }
-},
-{
-    "model": "backend_api.device",
-    "pk": 2,
-    "fields": {
-        "space_project": 1
-    }
-},
-{
-    "model": "backend_api.device",
-    "pk": 3,
-    "fields": {
-        "space_project": 1
-    }
-},
-{
-    "model": "backend_api.device",
-    "pk": 4,
-    "fields": {
-        "space_project": 2
-    }
-},
-{
-    "model": "backend_api.device",
-    "pk": 5,
-    "fields": {
-        "space_project": 2
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 1,
-    "fields": {
-        "short_name": "V",
-        "long_name": "Volts",
-        "language_code": "en",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 2,
-    "fields": {
-        "short_name": "\u0412",
-        "long_name": "\u0412\u043e\u043b\u044c\u0442\u0438",
-        "language_code": "uk",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 3,
-    "fields": {
-        "short_name": "V\u22c5m\u22121",
-        "long_name": "Volts per metre",
-        "language_code": "en",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 4,
-    "fields": {
-        "short_name": "\u0412\u22c5\u043c\u22121",
-        "long_name": "\u0412\u043e\u043b\u044c\u0442 \u043d\u0430 \u043c\u0435\u0442\u0440",
-        "language_code": "uk",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 5,
-    "fields": {
-        "short_name": "nT",
-        "long_name": "Nanotesla",
-        "language_code": "en",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 6,
-    "fields": {
-        "short_name": "\u043d\u0422\u043b",
-        "long_name": "\u041d\u0430\u043d\u043e\u0442\u0435\u0441\u043b\u0430",
-        "language_code": "uk",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 7,
-    "fields": {
-        "short_name": "A\u22c5cm\u22122",
-        "long_name": "Amper per square centimetre",
-        "language_code": "en",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.unittranslation",
-    "pk": 8,
-    "fields": {
-        "short_name": "\u0410\u22c5\u0441\u043c\u22122",
-        "long_name": "\u0410\u043c\u043f\u0435\u0440 \u043d\u0430 \u0441\u0430\u043d\u0442\u0438\u043c\u0435\u0442\u0440 \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u043d\u0438\u0439",
-        "language_code": "uk",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.unit",
-    "pk": 1,
-    "fields": {}
-},
-{
-    "model": "backend_api.unit",
-    "pk": 2,
-    "fields": {}
-},
-{
-    "model": "backend_api.unit",
-    "pk": 3,
-    "fields": {}
-},
-{
-    "model": "backend_api.unit",
-    "pk": 4,
-    "fields": {}
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 1,
-    "fields": {
-        "name": "Electric potential",
-        "description": "Electric field potential",
-        "language_code": "en",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 2,
-    "fields": {
-        "name": "\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f",
-        "description": "\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f (\u0435\u043b\u0435\u043a\u0442\u0440\u043e\u0441\u0442\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b)",
-        "language_code": "uk",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 3,
-    "fields": {
-        "name": "Electric potential difference",
-        "description": "",
-        "language_code": "en",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 4,
-    "fields": {
-        "name": "\u0420\u0456\u0437\u043d\u0438\u0446\u044f \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u0438\u0445 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0456\u0432",
-        "description": "",
-        "language_code": "uk",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 5,
-    "fields": {
-        "name": "Electric field",
-        "description": "",
-        "language_code": "en",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 6,
-    "fields": {
-        "name": "\u0412\u0435\u043a\u0442\u043e\u0440 \u043d\u0430\u043f\u0440\u0443\u0436\u0435\u043d\u043d\u043e\u0441\u0442\u0456 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f",
-        "description": "",
-        "language_code": "uk",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 7,
-    "fields": {
-        "name": "Magnetic field",
-        "description": "",
-        "language_code": "en",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 8,
-    "fields": {
-        "name": "\u0412\u0435\u043a\u0442\u043e\u0440 \u0456\u043d\u0434\u0443\u043a\u0446\u0456\u0457 \u043c\u0430\u0433\u043d\u0456\u0442\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f",
-        "description": "",
-        "language_code": "uk",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.valuetranslation",
-    "pk": 9,
-    "fields": {
-        "name": "Current density",
-        "description": "Electric current density",
-        "language_code": "en",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.value",
-    "pk": 1,
-    "fields": {
-        "short_name": "Ve",
-        "units": 1
-    }
-},
-{
-    "model": "backend_api.value",
-    "pk": 2,
-    "fields": {
-        "short_name": "\u0394Ve",
-        "units": 1
-    }
-},
-{
-    "model": "backend_api.value",
-    "pk": 3,
-    "fields": {
-        "short_name": "E",
-        "units": 2
-    }
-},
-{
-    "model": "backend_api.value",
-    "pk": 4,
-    "fields": {
-        "short_name": "B",
-        "units": 3
-    }
-},
-{
-    "model": "backend_api.value",
-    "pk": 5,
-    "fields": {
-        "short_name": "j",
-        "units": 4
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 1,
-    "fields": {
-        "name": "EZ low-frequency channel",
-        "description": "Low-frequency channel of the electric potential measurement (1Hz)",
-        "language_code": "en",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 2,
-    "fields": {
-        "name": "EZ \u043d\u0438\u0437\u044c\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b",
-        "description": "\u041d\u0438\u0437\u044c\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f  (1 \u0413\u0446)",
-        "language_code": "uk",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 3,
-    "fields": {
-        "name": "EZ high-frequency channel",
-        "description": "High-frequency channel of the electric potential measurement (1kHz)",
-        "language_code": "en",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 4,
-    "fields": {
-        "name": "EZ \u0432\u0438\u0441\u043e\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b",
-        "description": "\u0412\u0438\u0441\u043e\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f  (1 \u043a\u0413\u0446)",
-        "language_code": "uk",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 5,
-    "fields": {
-        "name": "\u0394E1, \u0394E2, \u0394E3",
-        "description": "\u0394E1 = EZ1 - EZ4 \r\n\u0394E2 = EZ1 - EZ3\r\n\u0394E3 = EZ1 - EZ3",
-        "language_code": "en",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 6,
-    "fields": {
-        "name": "Bx~, By~ (not calibrated)",
-        "description": "",
-        "language_code": "en",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 7,
-    "fields": {
-        "name": "Jxz~, Jyz~ (not calibrated)",
-        "description": "",
-        "language_code": "en",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 8,
-    "fields": {
-        "name": "\u0394E1, \u0394E2, \u0394E3",
-        "description": "\u0394E1 = EZ1 - EZ4 \r\n\u0394E2 = EZ1 - EZ3\r\n\u0394E3 = EZ1 - EZ3",
-        "language_code": "uk",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 9,
-    "fields": {
-        "name": "Bx~, By~ (\u043d\u0435 \u0442\u0430\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u0456)",
-        "description": "",
-        "language_code": "uk",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.channeltranslation",
-    "pk": 10,
-    "fields": {
-        "name": "Jxz~, Jyz~ (\u043d\u0435 \u0442\u0430\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u0456)",
-        "description": "",
-        "language_code": "uk",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.channel",
-    "pk": 1,
-    "fields": {
-        "value": 1,
-        "exponent": -3,
-        "device": 1,
-        "klass": [
-            "classes.base_data.SingleVarTimeSeries"
-        ]
-    }
-},
-{
-    "model": "backend_api.channel",
-    "pk": 2,
-    "fields": {
-        "value": 1,
-        "exponent": -3,
-        "device": 1,
-        "klass": [
-            "classes.base_data.ObliqueThreeVarTimeSeriesHF"
-        ]
-    }
-},
-{
-    "model": "backend_api.channel",
-    "pk": 3,
-    "fields": {
-        "value": 2,
-        "exponent": 0,
-        "device": 4,
-        "klass": [
-            "classes.base_data.ObliqueThreeVarTimeSeriesHF"
-        ]
-    }
-},
-{
-    "model": "backend_api.channel",
-    "pk": 4,
-    "fields": {
-        "value": 1,
-        "exponent": 0,
-        "device": 5,
-        "klass": [
-            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
-        ]
-    }
-},
-{
-    "model": "backend_api.channel",
-    "pk": 5,
-    "fields": {
-        "value": 1,
-        "exponent": 0,
-        "device": 5,
-        "klass": [
-            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
-        ]
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 1,
-    "fields": {
-        "name": "V (electric potential LF Fs = 1 Hz)",
-        "description": "Electric potential measured in low frequency (Fs = 1 Hz)",
-        "language_code": "en",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 2,
-    "fields": {
-        "name": "V (\u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b LF Fs = 1 \u0413\u0446)",
-        "description": "\u041d\u0438\u0437\u044c\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0456 \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 (Fs = 1 \u0413\u0446)",
-        "language_code": "uk",
-        "master": 1
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 3,
-    "fields": {
-        "name": "V (\u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b HF Fs = 1 \u043a\u0413\u0446)",
-        "description": "\u0412\u0438\u0441\u043e\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0456 \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 (Fs = 1 \u043a\u0413\u0446)",
-        "language_code": "uk",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 4,
-    "fields": {
-        "name": "V (electric potential HF Fs = 1 kHz)",
-        "description": "Electric potential measured in high frequency (Fs = 1 kHz)",
-        "language_code": "en",
-        "master": 2
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 5,
-    "fields": {
-        "name": "Ex, Ey, Ez (three components of electric field HF Fs = 31.25 kHz)",
-        "description": "",
-        "language_code": "en",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 6,
-    "fields": {
-        "name": "Ex, Ey, Ez (\u0442\u0440\u0438 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0432\u0435\u043a\u0442\u043e\u0440\u0443 \u043d\u0430\u043f\u0440\u0443\u0436\u0435\u043d\u043d\u043e\u0441\u0442\u0456 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f HF Fs = 31.25 \u043a\u0413\u0446)",
-        "description": "",
-        "language_code": "uk",
-        "master": 3
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 7,
-    "fields": {
-        "name": "Bx, By (two components of magnetic field HF Fs = 31,25 kHz)",
-        "description": "",
-        "language_code": "en",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 8,
-    "fields": {
-        "name": "Bx, By (\u0434\u0432\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u043c\u0430\u0433\u043d\u0456\u0442\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f HF Fs = 31,25 \u043a\u0413\u0446)",
-        "description": "",
-        "language_code": "uk",
-        "master": 4
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 9,
-    "fields": {
-        "name": "Jxz, Jyz (two components of current density Fs = 31.25 kHz)",
-        "description": "",
-        "language_code": "en",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.parametertranslation",
-    "pk": 10,
-    "fields": {
-        "name": "Jxz, Jyz (\u0434\u0432\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0433\u0443\u0441\u0442\u0438\u043d\u0438 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u0441\u0442\u0440\u0443\u043c\u0443 Fs = 31.25 \u043a\u0413\u0446)",
-        "description": "",
-        "language_code": "uk",
-        "master": 5
-    }
-},
-{
-    "model": "backend_api.parameter",
-    "pk": 1,
-    "fields": {
-        "value": 1,
-        "exponent": -3,
-        "channel": 1,
-        "klass": [
-            "classes.base_data.SingleVarTimeSeries"
-        ]
-    }
-},
-{
-    "model": "backend_api.parameter",
-    "pk": 2,
-    "fields": {
-        "value": 1,
-        "exponent": -3,
-        "channel": 2,
-        "klass": [
-            "classes.base_data.SingleVarTimeSeries"
-        ]
-    }
-},
-{
-    "model": "backend_api.parameter",
-    "pk": 3,
-    "fields": {
-        "value": 3,
-        "exponent": 0,
-        "channel": 3,
-        "klass": [
-            "classes.base_data.OrthogonalThreeVarTimeSeriesHF"
-        ]
-    }
-},
-{
-    "model": "backend_api.parameter",
-    "pk": 4,
-    "fields": {
-        "value": 4,
-        "exponent": 0,
-        "channel": 4,
-        "klass": [
-            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
-        ]
-    }
-},
-{
-    "model": "backend_api.parameter",
-    "pk": 5,
-    "fields": {
-        "value": 5,
-        "exponent": 0,
-        "channel": 5,
-        "klass": [
-            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
-        ]
-    }
-}
-]
+[
+{
+    "model": "backend_api.space_projecttranslation",
+    "pk": 1,
+    "fields": {
+        "name": "Potential",
+        "description": "The space scientific experiment \"Potential\" on the ionosphere aboard the Ukrainian Sich-2 microsatellite (2011-2012)",
+        "language_code": "en",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.space_projecttranslation",
+    "pk": 2,
+    "fields": {
+        "name": "\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b",
+        "description": "\u041d\u0430\u0443\u043a\u043e\u0432\u0438\u0439 \u0456\u043e\u043d\u043e\u0441\u0444\u0435\u0440\u043d\u0438\u0439 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u0438\u0439 \u0435\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442 \"\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\" \u043d\u0430 \u0431\u043e\u0440\u0442\u0443 \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u043e\u0433\u043e \u043c\u0456\u043a\u0440\u043e\u0441\u0443\u043f\u0443\u0442\u043d\u0438\u043a\u0430 \"\u0421\u0456\u0447-2\" (2011-2012)",
+        "language_code": "uk",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.space_projecttranslation",
+    "pk": 3,
+    "fields": {
+        "name": "Variant",
+        "description": "The space scientific experiment \"Variant\" on the ionosphere aboard the Ukrainian Sich-1M satellite (2004-2005)",
+        "language_code": "en",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.space_projecttranslation",
+    "pk": 4,
+    "fields": {
+        "name": "\u0412\u0430\u0440\u0456\u0430\u043d\u0442",
+        "description": "\u041d\u0430\u0443\u043a\u043e\u0432\u0438\u0439 \u0456\u043e\u043d\u043e\u0441\u0444\u0435\u0440\u043d\u0438\u0439 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u0438\u0439 \u0435\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442 \"\u0412\u0430\u0440\u0456\u0430\u043d\u0442\" \u043d\u0430 \u0431\u043e\u0440\u0442\u0443 \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u043e\u0433\u043e \u0441\u0443\u043f\u0443\u0442\u043d\u0438\u043a\u0430 \"\u0421\u0456\u0447-1\u041c\" (2004-2005)",
+        "language_code": "uk",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.space_project",
+    "pk": 1,
+    "fields": {
+        "klass": [
+            "classes.potential.Potential"
+        ],
+        "date_start": "2011-08-30",
+        "date_end": "2012-11-01"
+    }
+},
+{
+    "model": "backend_api.space_project",
+    "pk": 2,
+    "fields": {
+        "klass": [
+            "classes.variant.Variant"
+        ],
+        "date_start": "2005-02-01",
+        "date_end": "2005-03-26"
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 1,
+    "fields": {
+        "name": "Electric probe (EP)",
+        "description": "Electric probes are intended for the measurement of electric field intensity in space plasma with the help of two similar probes placed at a known distance. Potential project used a single probe setup that can be used to measure the spacecraft's own electric potential.",
+        "language_code": "en",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 2,
+    "fields": {
+        "name": "\u0415\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u0438\u0439 \u0437\u043e\u043d\u0434 (EP)",
+        "description": "\u0414\u0430\u0432\u0430\u0447 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 \u043f\u0440\u0438\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u043d\u0430\u043f\u0440\u0443\u0436\u0435\u043d\u043e\u0441\u0442\u0456 \u0437\u043c\u0456\u043d\u043d\u043e\u0433\u043e \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f \u0443 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u0456\u0439 \u043f\u043b\u0430\u0437\u043c\u0456 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u0434\u0432\u043e\u0445 \u043f\u043e\u0434\u0456\u0431\u043d\u0438\u0445 \u0434\u0430\u0432\u0430\u0447\u0456\u0432, \u0440\u043e\u0437\u043d\u0435\u0441\u0435\u043d\u0438\u0445 \u043d\u0430 \u0432\u0456\u0434\u043e\u043c\u0443 \u0432\u0456\u0434\u0441\u0442\u0430\u043d\u044c. \u0410\u043b\u0435 \u0432 \u043a\u043e\u0441\u043c\u0456\u0447\u043d\u043e\u043c\u0443 \u0435\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442\u0456 \u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b \u0432\u0456\u043d \u0431\u0443\u0432 \u043e\u0434\u0438\u043d :(",
+        "language_code": "uk",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 3,
+    "fields": {
+        "name": "Neutral gase parameters sensor (NCP)",
+        "description": "A system of two pressure probes using an inverse-magnetron converter as a sensor. (The device to produce the i/v characteristics from which the ITM team is to obtain the neutral gas density and pressure.)",
+        "language_code": "en",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 4,
+    "fields": {
+        "name": "\u0414\u0430\u0442\u0447\u0438\u043a \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0456\u0432 \u043d\u0435\u0439\u0442\u0440\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u0433\u0430\u0437\u0443 \u041d\u041a\u041f",
+        "description": "\u041d\u041a\u041f \u0441\u043a\u043b\u0430\u0434\u0430\u0454\u0442\u044c\u0441\u044f \u0437 \u0434\u0432\u043e\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 \u0442\u0438\u0441\u043a\u0443 \u0437 \u0456\u043d\u0432\u0435\u0440\u0441\u043d\u043e-\u043c\u0430\u0433\u043d\u0435\u0442\u0440\u043e\u043d\u043d\u0438\u043c \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u044e\u0432\u0430\u0447\u0435\u043c \u0432 \u044f\u043a\u043e\u0441\u0442\u0456 \u0447\u0443\u0442\u043b\u0438\u0432\u043e\u0433\u043e \u0435\u043b\u0435\u043c\u0435\u043d\u0442\u0443",
+        "language_code": "uk",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 5,
+    "fields": {
+        "name": "Plasma parameters sensor (ECP)",
+        "description": "A single cylindrical Langmiur probe measuring 0.05 cm in radius with 12 cm in length along with a protective electrode measuring 0.2 cm in radius and 12.5 cm in length. (The device to produce the i/v characteristics from which the ITM team is to obtain the plasma density and the electron temperature)",
+        "language_code": "en",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 6,
+    "fields": {
+        "name": "\u0414\u0430\u0442\u0447\u0438\u043a \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0456\u0432 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u043e\u0457 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u043f\u043b\u0430\u0437\u043c\u0438 (\u0415\u041a\u041f)",
+        "description": "\u041e\u0434\u0438\u043d\u0438\u0447\u043d\u0438\u0439 \u0446\u0438\u043b\u0456\u043d\u0434\u0440\u0438\u0447\u043d\u0438\u0439 \u0437\u043e\u043d\u0434 \u041b\u0435\u043d\u0433\u043c\u044e\u0440\u0430 \u0440\u0430\u0434\u0456\u0443\u043e\u043c 0,05 \u0441\u043c \u0456 \u0434\u043e\u0432\u0436\u0438\u043d\u043e\u044e 12 \u0441\u043c \u0437 \u043e\u0445\u043e\u0440\u043e\u043d\u043d\u0438\u043c \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u0434\u043e\u043c \u0440\u0430\u0434\u0456\u0443\u0441\u043e\u043c 0,2 \u0441\u043c \u0434\u043e\u0432\u0436\u0438\u043d\u043e\u044e 12,5 \u0441\u043c",
+        "language_code": "uk",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 7,
+    "fields": {
+        "name": "Set of 4 Electric probes (EZ1, EZ2, EZ3, EZ4)",
+        "description": "",
+        "language_code": "en",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 8,
+    "fields": {
+        "name": "\u041a\u043e\u043c\u043f\u043b\u0435\u043a\u0441 \u0437 4 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u0438\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 (EZ1, EZ2, EZ3, EZ4)",
+        "description": "",
+        "language_code": "uk",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 9,
+    "fields": {
+        "name": "\u041a\u043e\u043c\u043f\u043b\u0435\u043a\u0441 \u0437 \u0434\u0432\u043e\u0445 \u0445\u0432\u0438\u043b\u044c\u043e\u0432\u0438\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 (WZ1, WZ2)",
+        "description": "\u041a\u043e\u043c\u043f\u043b\u0435\u043a\u0441 \u0437 \u0434\u0432\u043e\u0445 \u0445\u0432\u0438\u043b\u044c\u043e\u0432\u0438\u0445 \u0437\u043e\u043d\u0434\u0456\u0432 (WZ1, WZ2), \u0449\u043e \u0432\u0438\u043c\u0456\u0440\u044e\u044e\u0442\u044c \u0434\u0432\u0456 \u043e\u0440\u0442\u043e\u0433\u043e\u043d\u0430\u043b\u044c\u043d\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0437\u043c\u0456\u043d\u043d\u043e\u0433\u043e \u043c\u0430\u0433\u043d\u0456\u0442\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f (Bx, By) \u0442\u0430 \u0434\u0432\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0433\u0443\u0441\u0442\u0438\u043d\u0438 \u0437\u043c\u0456\u043d\u043d\u043e\u0433\u043e \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u0441\u0442\u0440\u0443\u043c\u0443 (Jxz, Jyz)",
+        "language_code": "uk",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 10,
+    "fields": {
+        "name": "Set of 2 Wave probes (WZ1, WZ2)",
+        "description": "A complex of two wave probes (WZ1, WZ2) measuring two orthogonal variable components of the magnetic field (Bx, By) and two variable components of the current electric density (Jxz, Jyz)",
+        "language_code": "en",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 11,
+    "fields": {
+        "name": "Faraday cups (FC1, FC2)",
+        "description": "",
+        "language_code": "en",
+        "master": 6
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 12,
+    "fields": {
+        "name": "Rogowski coil",
+        "description": "",
+        "language_code": "en",
+        "master": 7
+    }
+},
+{
+    "model": "backend_api.devicetranslation",
+    "pk": 13,
+    "fields": {
+        "name": "Fluxgate magnetometer FZM",
+        "description": "",
+        "language_code": "en",
+        "master": 8
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 1,
+    "fields": {
+        "space_project": 1
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 2,
+    "fields": {
+        "space_project": 1
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 3,
+    "fields": {
+        "space_project": 1
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 4,
+    "fields": {
+        "space_project": 2
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 5,
+    "fields": {
+        "space_project": 2
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 6,
+    "fields": {
+        "space_project": 2
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 7,
+    "fields": {
+        "space_project": 2
+    }
+},
+{
+    "model": "backend_api.device",
+    "pk": 8,
+    "fields": {
+        "space_project": 2
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 1,
+    "fields": {
+        "short_name": "V",
+        "long_name": "Volts",
+        "language_code": "en",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 2,
+    "fields": {
+        "short_name": "\u0412",
+        "long_name": "\u0412\u043e\u043b\u044c\u0442\u0438",
+        "language_code": "uk",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 3,
+    "fields": {
+        "short_name": "V\u22c5m\u22121",
+        "long_name": "Volts per metre",
+        "language_code": "en",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 4,
+    "fields": {
+        "short_name": "\u0412\u22c5\u043c\u22121",
+        "long_name": "\u0412\u043e\u043b\u044c\u0442 \u043d\u0430 \u043c\u0435\u0442\u0440",
+        "language_code": "uk",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 5,
+    "fields": {
+        "short_name": "nT",
+        "long_name": "Nanotesla",
+        "language_code": "en",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 6,
+    "fields": {
+        "short_name": "\u043d\u0422\u043b",
+        "long_name": "\u041d\u0430\u043d\u043e\u0442\u0435\u0441\u043b\u0430",
+        "language_code": "uk",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 7,
+    "fields": {
+        "short_name": "A\u22c5cm\u22122",
+        "long_name": "Amper per square centimetre",
+        "language_code": "en",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.unittranslation",
+    "pk": 8,
+    "fields": {
+        "short_name": "\u0410\u22c5\u0441\u043c\u22122",
+        "long_name": "\u0410\u043c\u043f\u0435\u0440 \u043d\u0430 \u0441\u0430\u043d\u0442\u0438\u043c\u0435\u0442\u0440 \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u043d\u0438\u0439",
+        "language_code": "uk",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.unit",
+    "pk": 1,
+    "fields": {}
+},
+{
+    "model": "backend_api.unit",
+    "pk": 2,
+    "fields": {}
+},
+{
+    "model": "backend_api.unit",
+    "pk": 3,
+    "fields": {}
+},
+{
+    "model": "backend_api.unit",
+    "pk": 4,
+    "fields": {}
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 1,
+    "fields": {
+        "name": "Electric potential",
+        "description": "Electric field potential",
+        "language_code": "en",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 2,
+    "fields": {
+        "name": "\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f",
+        "description": "\u041f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f (\u0435\u043b\u0435\u043a\u0442\u0440\u043e\u0441\u0442\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b)",
+        "language_code": "uk",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 3,
+    "fields": {
+        "name": "Electric potential difference",
+        "description": "",
+        "language_code": "en",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 4,
+    "fields": {
+        "name": "\u0420\u0456\u0437\u043d\u0438\u0446\u044f \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u0438\u0445 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0456\u0432",
+        "description": "",
+        "language_code": "uk",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 5,
+    "fields": {
+        "name": "Electric field",
+        "description": "",
+        "language_code": "en",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 6,
+    "fields": {
+        "name": "\u0412\u0435\u043a\u0442\u043e\u0440 \u043d\u0430\u043f\u0440\u0443\u0436\u0435\u043d\u043d\u043e\u0441\u0442\u0456 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f",
+        "description": "",
+        "language_code": "uk",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 7,
+    "fields": {
+        "name": "Magnetic field",
+        "description": "",
+        "language_code": "en",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 8,
+    "fields": {
+        "name": "\u0412\u0435\u043a\u0442\u043e\u0440 \u0456\u043d\u0434\u0443\u043a\u0446\u0456\u0457 \u043c\u0430\u0433\u043d\u0456\u0442\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f",
+        "description": "",
+        "language_code": "uk",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.valuetranslation",
+    "pk": 9,
+    "fields": {
+        "name": "Current density",
+        "description": "Electric current density",
+        "language_code": "en",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.value",
+    "pk": 1,
+    "fields": {
+        "short_name": "Ve",
+        "units": 1
+    }
+},
+{
+    "model": "backend_api.value",
+    "pk": 2,
+    "fields": {
+        "short_name": "\u0394Ve",
+        "units": 1
+    }
+},
+{
+    "model": "backend_api.value",
+    "pk": 3,
+    "fields": {
+        "short_name": "E",
+        "units": 2
+    }
+},
+{
+    "model": "backend_api.value",
+    "pk": 4,
+    "fields": {
+        "short_name": "B",
+        "units": 3
+    }
+},
+{
+    "model": "backend_api.value",
+    "pk": 5,
+    "fields": {
+        "short_name": "j",
+        "units": 4
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 1,
+    "fields": {
+        "name": "EZ low-frequency channel",
+        "description": "Low-frequency channel of the electric potential measurement (1Hz)",
+        "language_code": "en",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 2,
+    "fields": {
+        "name": "EZ \u043d\u0438\u0437\u044c\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b",
+        "description": "\u041d\u0438\u0437\u044c\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f  (1 \u0413\u0446)",
+        "language_code": "uk",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 3,
+    "fields": {
+        "name": "EZ high-frequency channel",
+        "description": "High-frequency channel of the electric potential measurement (1kHz)",
+        "language_code": "en",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 4,
+    "fields": {
+        "name": "EZ \u0432\u0438\u0441\u043e\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b",
+        "description": "\u0412\u0438\u0441\u043e\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0438\u0439 \u043a\u0430\u043d\u0430\u043b \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f  (1 \u043a\u0413\u0446)",
+        "language_code": "uk",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 5,
+    "fields": {
+        "name": "\u0394E1, \u0394E2, \u0394E3",
+        "description": "\u0394E1 = EZ1 - EZ4 \r\n\u0394E2 = EZ1 - EZ3\r\n\u0394E3 = EZ1 - EZ3",
+        "language_code": "en",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 6,
+    "fields": {
+        "name": "Bx~, By~ (not calibrated)",
+        "description": "",
+        "language_code": "en",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 7,
+    "fields": {
+        "name": "Jxz~, Jyz~ (not calibrated)",
+        "description": "",
+        "language_code": "en",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 8,
+    "fields": {
+        "name": "\u0394E1, \u0394E2, \u0394E3",
+        "description": "\u0394E1 = EZ1 - EZ4 \r\n\u0394E2 = EZ1 - EZ3\r\n\u0394E3 = EZ1 - EZ3",
+        "language_code": "uk",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 9,
+    "fields": {
+        "name": "Bx~, By~ (\u043d\u0435 \u0442\u0430\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u0456)",
+        "description": "",
+        "language_code": "uk",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 10,
+    "fields": {
+        "name": "Jxz~, Jyz~ (\u043d\u0435 \u0442\u0430\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u0456)",
+        "description": "",
+        "language_code": "uk",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 11,
+    "fields": {
+        "name": "\u0394E1=, \u0394E2=, \u0394E3=",
+        "description": "",
+        "language_code": "en",
+        "master": 6
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 12,
+    "fields": {
+        "name": "FC1~, FC2~",
+        "description": "",
+        "language_code": "en",
+        "master": 7
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 13,
+    "fields": {
+        "name": "JF~",
+        "description": "",
+        "language_code": "en",
+        "master": 8
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 14,
+    "fields": {
+        "name": "Bx, By, Bz",
+        "description": "",
+        "language_code": "en",
+        "master": 9
+    }
+},
+{
+    "model": "backend_api.channeltranslation",
+    "pk": 15,
+    "fields": {
+        "name": "FC1=, FC2=",
+        "description": "",
+        "language_code": "en",
+        "master": 10
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 1,
+    "fields": {
+        "value": 1,
+        "exponent": -3,
+        "device": 1,
+        "klass": [
+            "classes.base_data.SingleVarTimeSeries"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 2,
+    "fields": {
+        "value": 1,
+        "exponent": -3,
+        "device": 1,
+        "klass": [
+            "classes.base_data.SingleVarTimeSeries"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 3,
+    "fields": {
+        "value": 2,
+        "exponent": 0,
+        "device": 4,
+        "klass": [
+            "classes.base_data.ObliqueThreeVarTimeSeriesHF"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 4,
+    "fields": {
+        "value": 1,
+        "exponent": 0,
+        "device": 5,
+        "klass": [
+            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 5,
+    "fields": {
+        "value": 1,
+        "exponent": 0,
+        "device": 5,
+        "klass": [
+            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 6,
+    "fields": {
+        "value": 2,
+        "exponent": 0,
+        "device": 4,
+        "klass": [
+            "classes.base_data.ObliqueThreeVarTimeSeriesLF"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 7,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "device": 6,
+        "klass": [
+            "classes.base_data.ScalarValueDifference"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 8,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "device": 7,
+        "klass": [
+            "classes.base_data.SingleVarTimeSeries"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 9,
+    "fields": {
+        "value": 4,
+        "exponent": 0,
+        "device": 8,
+        "klass": [
+            "classes.base_data.OrthogonalThreeVarTimeSeriesLF"
+        ]
+    }
+},
+{
+    "model": "backend_api.channel",
+    "pk": 10,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "device": 6,
+        "klass": [
+            "classes.base_data.ScalarValueDifference"
+        ]
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 1,
+    "fields": {
+        "name": "V (electric potential LF Fs = 1 Hz)",
+        "description": "Electric potential measured in low frequency (Fs = 1 Hz)",
+        "language_code": "en",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 2,
+    "fields": {
+        "name": "V (\u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b LF Fs = 1 \u0413\u0446)",
+        "description": "\u041d\u0438\u0437\u044c\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0456 \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 (Fs = 1 \u0413\u0446)",
+        "language_code": "uk",
+        "master": 1
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 3,
+    "fields": {
+        "name": "V (\u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b HF Fs = 1 \u043a\u0413\u0446)",
+        "description": "\u0412\u0438\u0441\u043e\u043a\u043e\u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0456 \u0432\u0438\u043c\u0456\u0440\u044e\u0432\u0430\u043d\u043d\u044f \u0435\u043b\u0435\u043a\u0442\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0430\u043b\u0443 (Fs = 1 \u043a\u0413\u0446)",
+        "language_code": "uk",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 4,
+    "fields": {
+        "name": "V (electric potential HF Fs = 1 kHz)",
+        "description": "Electric potential measured in high frequency (Fs = 1 kHz)",
+        "language_code": "en",
+        "master": 2
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 5,
+    "fields": {
+        "name": "Ex, Ey, Ez (three components of electric field HF)",
+        "description": "",
+        "language_code": "en",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 6,
+    "fields": {
+        "name": "Ex, Ey, Ez (\u0442\u0440\u0438 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0432\u0435\u043a\u0442\u043e\u0440\u0443 \u043d\u0430\u043f\u0440\u0443\u0436\u0435\u043d\u043d\u043e\u0441\u0442\u0456 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f HF Fs = 31.25 \u043a\u0413\u0446)",
+        "description": "",
+        "language_code": "uk",
+        "master": 3
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 7,
+    "fields": {
+        "name": "Bx, By (two components of magnetic field HF)",
+        "description": "",
+        "language_code": "en",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 8,
+    "fields": {
+        "name": "Bx, By (\u0434\u0432\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u043c\u0430\u0433\u043d\u0456\u0442\u043d\u043e\u0433\u043e \u043f\u043e\u043b\u044f HF Fs = 31,25 \u043a\u0413\u0446)",
+        "description": "",
+        "language_code": "uk",
+        "master": 4
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 9,
+    "fields": {
+        "name": "Jxz, Jyz (two components of current density)",
+        "description": "",
+        "language_code": "en",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 10,
+    "fields": {
+        "name": "Jxz, Jyz (\u0434\u0432\u0456 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0438 \u0433\u0443\u0441\u0442\u0438\u043d\u0438 \u0435\u043b\u0435\u043a\u0442\u0440\u0438\u0447\u043d\u043e\u0433\u043e \u0441\u0442\u0440\u0443\u043c\u0443 Fs = 31.25 \u043a\u0413\u0446)",
+        "description": "",
+        "language_code": "uk",
+        "master": 5
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 11,
+    "fields": {
+        "name": "E1=, E2=, E3= (three components of electric field LF)",
+        "description": "",
+        "language_code": "en",
+        "master": 6
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 12,
+    "fields": {
+        "name": "\u0394FC~",
+        "description": "",
+        "language_code": "en",
+        "master": 7
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 13,
+    "fields": {
+        "name": "JF~ (current density)",
+        "description": "",
+        "language_code": "en",
+        "master": 8
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 14,
+    "fields": {
+        "name": "Bx, By, Bz (three components of magnetic field)",
+        "description": "",
+        "language_code": "en",
+        "master": 9
+    }
+},
+{
+    "model": "backend_api.parametertranslation",
+    "pk": 15,
+    "fields": {
+        "name": "\u0394FC=",
+        "description": "",
+        "language_code": "en",
+        "master": 10
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 1,
+    "fields": {
+        "value": 1,
+        "exponent": -3,
+        "channel": 1,
+        "klass": [
+            "classes.base_data.SingleVarTimeSeries"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 2,
+    "fields": {
+        "value": 1,
+        "exponent": -3,
+        "channel": 2,
+        "klass": [
+            "classes.base_data.SingleVarTimeSeries"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 3,
+    "fields": {
+        "value": 3,
+        "exponent": 0,
+        "channel": 3,
+        "klass": [
+            "classes.base_data.ObliqueThreeVarTimeSeriesHF"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 4,
+    "fields": {
+        "value": 4,
+        "exponent": 0,
+        "channel": 4,
+        "klass": [
+            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 5,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "channel": 5,
+        "klass": [
+            "classes.base_data.OrthogonalTwoVarTimeSeriesHF"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 6,
+    "fields": {
+        "value": 2,
+        "exponent": 0,
+        "channel": 6,
+        "klass": [
+            "classes.base_data.ObliqueThreeVarTimeSeriesLF"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 7,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "channel": 7,
+        "klass": [
+            "classes.base_data.ScalarValueDifference"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 8,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "channel": 8,
+        "klass": [
+            "classes.base_data.SingleVarTimeSeries"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 9,
+    "fields": {
+        "value": 4,
+        "exponent": 0,
+        "channel": 9,
+        "klass": [
+            "classes.base_data.OrthogonalThreeVarTimeSeriesLF"
+        ]
+    }
+},
+{
+    "model": "backend_api.parameter",
+    "pk": 10,
+    "fields": {
+        "value": 5,
+        "exponent": 0,
+        "channel": 10,
+        "klass": [
+            "classes.base_data.ScalarValueDifference"
+        ]
+    }
+}
+]
diff --git a/backend/promis/backend_api/models.py b/backend/promis/backend_api/models.py
index ae92492..ca09e30 100644
--- a/backend/promis/backend_api/models.py
+++ b/backend/promis/backend_api/models.py
@@ -3,6 +3,7 @@
 from django.db import models
 from django.db.models.fields import ( DateTimeField, IntegerField, CharField,
     DateField, FloatField, TextField )
+from django.contrib.postgres.fields import ArrayField
 from django.db.models.fields.related import ForeignKey
 from jsonfield import JSONField
 from django.contrib.gis.db.models import LineStringField
@@ -92,6 +93,9 @@ class Session(models.Model):
     # but ensures distances and intersections are caclulated correctly
     # TODO: srid should eventually be 4979 see #222
     geo_line = LineStringField(dim = 3, srid = 4326, geography=True)
+
+    # TODO: 4D coordinates, see #256
+    altitude = ArrayField(FloatField())
     space_project = ForeignKey('Space_project', null = True)
 
     class Meta:
diff --git a/backend/promis/backend_api/serializer.py b/backend/promis/backend_api/serializer.py
index c193dee..cfbc616 100644
--- a/backend/promis/backend_api/serializer.py
+++ b/backend/promis/backend_api/serializer.py
@@ -83,7 +83,9 @@ def get_geo_line(self, obj):
         #return obj.geo_line.wkb.hex()
 
         # TODO: study whether pre-building the list or JSON would speed up things
-        return parsers.wkb(obj.geo_line.wkb) # <- Generator
+        # TODO: ugly hack before #256
+        # geo_line.wkb calls a generator implicitly
+        return ( (*geo[:2], alt) for alt, geo in zip(obj.altitude, parsers.wkb(obj.geo_line.wkb)) )   
 
     def get_timelapse(self, obj):
         # TODO: change to time_start in model for consistency
diff --git a/backend/promis/classes/base_data.py b/backend/promis/classes/base_data.py
index ba62ac2..bd38aeb 100644
--- a/backend/promis/classes/base_data.py
+++ b/backend/promis/classes/base_data.py
@@ -41,6 +41,15 @@ def data_start(self):
     def frequency(self):
         return self.measurement.sampling_frequency
 
+    def __len__(self):
+        return len(self.doc)
+
+    def __getitem__(self, idx):
+        return self.doc[idx]
+
+    def data(self, selection = slice(None)):
+        return self.doc[selection]
+
     def timeslice(self, start, end):
         '''
         Returns a slice for accessing data between start and end inclusively.
@@ -77,14 +86,6 @@ class SingleVarTimeSeries(BaseData):
 
     # Underlying document is a simple list
     # delegate sequence protocol there
-    def __len__(self):
-        return len(self.doc)
-
-    def __getitem__(self, idx):
-        return self.doc[idx]
-
-    def data(self, selection = slice(None)):
-        return self.doc[selection]
 
     # TODO: propagate upwards?
     def quicklook(self, points, selection = slice(None)):
@@ -134,26 +135,58 @@ def avg_float(l, n, span):
             yield avg_float(v, int(span * i), span)
 
 
-# TODO: realize
 class ObliqueThreeVarTimeSeriesHF(BaseData):
     """
     [en]: Three high frequency components in oblique coordinate system
     [uk]: Три високочастотні компоненти вектора величини в косоугольній системі координат
     """
+    def quicklook(self, points, selection = slice(None)):
+        return
 
-
-# TODO: realize
 class OrthogonalThreeVarTimeSeriesHF(BaseData):
     """
     [en]: Three high frequency components in orthogonal coordinate system
     [uk]: Три високочастотні компоненти вектора величини в ортогональній системі координат
     """
+    def quicklook(self, points, selection = slice(None)):
+        return
 
+class ObliqueThreeVarTimeSeriesLF(BaseData):
+    """
+    [en]: Three low frequency components in oblique coordinate system
+    [uk]: Три низькочастотні компоненти вектора величини в косоугольній системі координат
+    """
+    def quicklook(self, points, selection = slice(None)):
+        return
+
+class OrthogonalThreeVarTimeSeriesLF(BaseData):
+    """
+    [en]: Three low frequency components in orthogonal coordinate system
+    [uk]: Три низькочастотні компоненти вектора величини в ортогональній системі координат
+    """
+    def quicklook(self, points, selection = slice(None)):
+        return
 
-# TODO: realize
 class OrthogonalTwoVarTimeSeriesHF(BaseData):
     """
     [en]: Two high frequency components in orthogonal coordinate system
     [uk]: Дві високочастотні компоненти вектора величини в ортогональній системі координат
     """
-    pass
+    def quicklook(self, points, selection = slice(None)):
+        return
+
+class ObliqueTwoVarTimeSeriesHF(BaseData):
+    """
+    [en]: Two high frequency components in oblique coordinate system
+    [uk]: Дві високочастотні компоненти вектора величини в косоугольній системі координат
+    """
+    def quicklook(self, points, selection = slice(None)):
+        return
+
+class ScalarValueDifference(BaseData):
+    """
+    [en]: Scalar difference of two values
+    [uk]: Скалярна різниця двух змінних
+    """
+    def quicklook(self, points, selection = slice(None)):
+        return
diff --git a/backend/promis/classes/potential.py b/backend/promis/classes/potential.py
index 921e454..e1b09e0 100644
--- a/backend/promis/classes/potential.py
+++ b/backend/promis/classes/potential.py
@@ -132,7 +132,10 @@ def fetch(self, daydir):
                                 ez_time_end = time_end
 
                                 # Generator for the orbit
-                                line_gen = ( (y.lon, y.lat, t) for t, y, _ in orbit.generate_orbit(orbit_path, time_start, time_end) )
+                                # TODO: rewrite as generator if possible at all
+                                path = [ (y.lon, y.lat, y.alt, t) for t, y, _ in orbit.generate_orbit(orbit_path, time_start, time_end) ]
+                                line_gen = [ (x, y, t) for x, y, _, t in path ]
+                                alt_gen = [ alt for _, _, alt, _ in path ]
                                 # Converting time to python objects for convenience
                                 # This is the point where onboard time gets converted to the UTC
                                 time_start = unix_time.maketime(time_start)
@@ -143,7 +146,8 @@ def fetch(self, daydir):
                                 # Creating a session object
                                 # TODO: make it more readable
                                 # TODO: srid should be 4979 see #222
-                                ez_sess_obj = model.Session.objects.create(time_begin = time_start, time_end = time_end, geo_line = LineString(*line_gen, srid = 4326), space_project = self.project_obj )
+                                ez_sess_obj = model.Session.objects.create(time_begin = time_start, time_end = time_end, altitude = alt_gen,
+                                        geo_line = LineString(*line_gen, srid = 4326), space_project = self.project_obj )
 
                                 # TODO: record data_id in the object
                                 # TODO: somehow generalise this process maybe
diff --git a/backend/promis/classes/variant.py b/backend/promis/classes/variant.py
index 9740ce4..a25876e 100644
--- a/backend/promis/classes/variant.py
+++ b/backend/promis/classes/variant.py
@@ -19,12 +19,51 @@
 # permissions and limitations under the Licence.
 #
 
-
+from django.contrib.gis.geos import LineString
 from classes.base_project import BaseProject
 
+import datetime
+import ftp_helper, parsers, unix_time, orbit
+import backend_api.models as model
 
-# TODO: implement obtaining of Variant data
-
+sessions_time = {
+    "597": {
+      'time_start': datetime.datetime(2005, 2, 1, 8, 22, 59).timestamp(),
+      'time_end': datetime.datetime(2005, 2, 1, 8, 43, 29).timestamp()
+    },
+    "1056": {
+      'time_start': datetime.datetime(2005, 3, 2, 17, 23, 10).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 2, 17, 27, 37).timestamp()
+    },
+    "1057": {
+      'time_start': datetime.datetime(2005, 3, 3, 5, 42, 57).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 3, 5, 44, 37).timestamp()
+    },
+    "1071": {
+      'time_start': datetime.datetime(2005, 3, 3, 16, 48, 14).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 3, 16, 52, 41).timestamp()
+    },
+    "1109": {
+      'time_start': datetime.datetime(2005, 3, 6, 11, 3, 13).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 6, 11, 7, 40).timestamp()
+    },
+    "1139": {
+      'time_start': datetime.datetime(2005, 3, 8, 1, 53, 5).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 8, 1, 57, 32).timestamp()
+    },
+    "1278": {
+      'time_start': datetime.datetime(2005, 3, 17, 13, 52, 49).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 17, 13, 57, 16).timestamp()
+    },
+    "1363": {
+      'time_start': datetime.datetime(2005, 3, 23, 1, 13, 6).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 23, 1, 14, 2).timestamp()
+    },
+    "1394": {
+      'time_start': datetime.datetime(2005, 3, 25, 1, 32, 47).timestamp(),
+      'time_end': datetime.datetime(2005, 3, 25, 1, 33, 43).timestamp()
+    }
+}
 
 class Variant(BaseProject):
     '''
@@ -33,4 +72,141 @@ class Variant(BaseProject):
     '''
 
     def check(*args, **kwargs):
-        return []
+        exceptions = {"1363",     # too few anchor points unfortunately
+                      "Read_me.doc",
+                      "Tabl_2.doc",
+                      "Tabl_3.doc"}
+        with ftp_helper.FTPChecker("Variant/Data_Release1/", "ftp.promis.ikd.kiev.ua") as ftp:
+            ftp.exceptions = exceptions
+            # TODO: check that directory exists properly
+            # TODO: any more elegant way? re-yield or smth
+            for v in ftp.check():
+                yield v
+        
+    def fetch(self, daydir):
+        with ftp_helper.FTPChecker("Variant/", "ftp.promis.ikd.kiev.ua") as ftp: 
+            ftp.cwd("telemetry")
+            # TODO: timezone hack
+            Δ = 1111714367 - 1111703568
+
+            with ftp.xopen("var{0}.tm".format(daydir)) as fp:
+                orbit_path = { (t + Δ): pt for t, pt in parsers.telemetry(fp, cartesian=False) }
+
+            time_start = int(sessions_time[daydir]['time_start'])
+            time_end = int(sessions_time[daydir]['time_end'])
+
+            path = [ (y.lon, y.lat, y.alt, t) for t, y, _ in orbit.generate_orbit(orbit_path, time_start, time_end, time_delta = 20) ]
+            line_gen = [ (x, y, t) for x, y, _, t in path ]
+            alt_gen = [ alt for _, _, alt, _ in path ]
+
+            time_start = unix_time.maketime(time_start)
+            time_end = unix_time.maketime(time_end)
+            time_dur = time_end - time_start
+            print("\tSession: [ %s, %s ] (%s)." % (time_start.isoformat(), time_end.isoformat(), str(time_dur)) )
+
+            sess_obj = model.Session.objects.create(time_begin = time_start, time_end = time_end, altitude = alt_gen,
+                geo_line = LineString(*line_gen, srid = 4326), space_project = self.project_obj )
+
+            # read per-channel sampling frequencies
+            component_sf = [['Bx', 0], ['By',0], ['Bz',0], ['Ts',0], ['Te',0], 
+                           ['JF~',0], 
+                           ['FC1~',0], ['FC1=',0], ['FC2~',0], ['FC2=',0], 
+                           ['Jyz~',0], ['Bx~',0], ['Jxz~',0], ['By~',0], 
+                           ['E1~',0], ['E1=',0], ['E2~',0], ['E2=',0], ['E3~',0], ['E3=',0]]
+            ftp.cwd("..")
+            ftp.cwd("Data_Release1/{0}".format(daydir))
+            
+            with ftp.xopen("{0}.txt".format(daydir)) as fp:
+                for line in fp:
+                    if line.rstrip() == "Sampling frequency, Hz":
+                        break
+                idx = 0
+                for line in fp:
+                    if idx >= len(component_sf):
+                        break
+                    if daydir in ["1057", "1071", "1109", "1278", "1394"] and idx == 3:
+                        idx += 2
+                    if len(line.rstrip()) != 0:
+                        component_sf[idx][1] = float(line)
+                    idx += 1
+
+            # Per-channel dicts of filename and JSON name
+            data = {
+                'ΔE1, ΔE2, ΔE3': {
+                    'param': 'Ex, Ey, Ez (three components of electric field HF)',
+                    'comps' : ['E1~', 'E2~', 'E3~']
+                },
+                'Bx~, By~ (not calibrated)': {
+                    'param': 'Bx, By (two components of magnetic field HF)',
+                    'comps' : ['Bx~', 'By~']
+                },
+                'Jxz~, Jyz~ (not calibrated)': {
+                    'param': 'Jxz, Jyz (two components of current density)',
+                    'comps' : ['Jxz~', 'Jyz~'] 
+                },
+                'ΔE1=, ΔE2=, ΔE3=': {
+                    'param': 'E1=, E2=, E3= (three components of electric field LF)',
+                    'comps': ['E1=', 'E2=', 'E3=']
+                },
+                'FC1~, FC2~': {
+                    'param': 'ΔFC~',
+                    'comps': ['FC1~', 'FC2~']
+                },
+                'JF~': {
+                    'param': 'JF~ (current density)',
+                    'comps': ['JF~']
+                },
+                'Bx, By, Bz': {
+                    'param': 'Bx, By, Bz (three components of magnetic field)',
+                    'comps': ['Bx', 'By', 'Bz']
+                },
+                'FC1=, FC2=': {
+                    'param': 'ΔFC=',
+                    'comps': ['FC1=', 'FC2=']
+                }
+            }
+
+            def get_file(name):
+                try:
+                    with ftp.xopen(name) as fp:
+                        return [ float(ln) for ln in fp ]
+                except:
+                    return []
+
+            for chan_name, chan_files in data.items():
+                chan_obj = model.Channel.objects.language('en').filter(name = chan_name)[0]
+                par_obj = model.Parameter.objects.language('en').filter(name = chan_files['param'])[0]
+                list_of_components = [get_file(name) for name in chan_files['comps']]
+
+                if (len(list_of_components) == 0) or (sum(len(x) for x in list_of_components) == 0):
+                    continue
+
+                # All the components of the single channel are suuposed to have the same sampling frequecny
+                # In fact sometimes some fo them appeared to be 0, that is why max is needed here
+                def find_sf(components):
+                    max_sf = 0
+                    for comp_name in components:
+                        for name, sf in component_sf:
+                            if name == comp_name:
+                                max_sf = max(max_sf, sf)
+                                break
+                    #print("components: " + str(components) + " max_sf: " + str(max_sf))        
+                    return max_sf
+
+                sampling_frequency = find_sf(chan_files['comps'])
+                numValues = int(time_dur.total_seconds() * sampling_frequency)
+
+                def catch_idx_error(component, idx):
+                   try:
+                      return component[idx]
+                   except IndexError:
+                      return 0.0
+
+                # We should better not covert a single component into a tuple. Handling this here
+                if len(list_of_components) > 1:
+                    json_data = [tuple([catch_idx_error(component,idx) for component in list_of_components]) for idx in range(numValues)]
+                else:
+                    json_data = [catch_idx_error(list_of_components[0],idx) for idx in range(numValues)]
+
+                doc_obj = model.Document.objects.create(json_data = json_data )
+                meas = model.Measurement.objects.create(session = sess_obj, parameter = par_obj, channel = chan_obj, channel_doc = doc_obj, parameter_doc = doc_obj, sampling_frequency = sampling_frequency, max_frequency = sampling_frequency, min_frequency = sampling_frequency)
diff --git a/backend/promis/export.py b/backend/promis/export.py
index 2ee5ae1..d5f66d7 100644
--- a/backend/promis/export.py
+++ b/backend/promis/export.py
@@ -23,6 +23,7 @@
 import collections
 import math
 import unix_time
+import itertools
 
 # TODO: currently only one data row
 # TODO: do we need this type or can we just have a tuple?
@@ -100,7 +101,7 @@ def ascii_export(table, datalabel="Data", dataunits="units"):
     yield "{:^10} {:^10} {:^6} {:^6} {:^6} {:^15}".format("Date", "UT", "Lat.", "Lon.", "Alt.", datalabel)
     yield "{:^10} {:^10} {:^6} {:^6} {:^6} {:^15}".format("(YYYYDDD)", "(ms)", "(deg.)", "(deg.)", "(km)", "(%s)" % dataunits)
     for row in table:
-        yield "{:>10} {:>10} {:>6.02f} {:>6.02f} {:>6.02f} {:>15.06f}".format(row.date, row.ut, row.lat, row.lon, row.alt, row.data)
+        yield "{:>10} {:>10} {:>6.02f} {:>6.02f} {:>6.02f}".format(row.date, row.ut, row.lat, row.lon, row.alt) + "".join(" {:>15.06f}".format(data_comp) for data_comp in row.data)
 
 def csv_export(table, datalabel="Data", dataunits="units"):
     """
@@ -115,7 +116,7 @@ def csv_export(table, datalabel="Data", dataunits="units"):
     """
     yield '"{}","{}","{}","{}","{}","{}"'.format("Date (YYYYDDD)", "UT (ms)", "Longitude (deg)", "Latitude (deg)", "Altitude (km)", datalabel + "(%s)" % dataunits)
     for row in table:
-        yield ",".join(str(x) for x in [row.date, row.ut, row.lon, row.lat, row.alt, row.data])
+        yield ",".join(str(x) for x in itertools.chain([row.date, row.ut, row.lon, row.lat, row.alt], row.data))
 
 
 
diff --git a/backend/promis/orbit.py b/backend/promis/orbit.py
index 37faa46..44e47aa 100644
--- a/backend/promis/orbit.py
+++ b/backend/promis/orbit.py
@@ -44,12 +44,12 @@ def cord_conv(RX, RY, RZ, **kwargs):
     return OrbitPoint(math.degrees(φ), math.degrees(λ), ρ - _earth_radius)
 
 # Generating an orbit point every 1 second, discarding extra point and filling the gaps
-def generate_orbit(datapoints, orbit_start, orbit_end):
+def generate_orbit(datapoints, orbit_start, orbit_end, time_delta = 0):
     datakeys = datapoints.keys()
     time_start, time_end = min(datakeys), max(datakeys)
     orbit_len = orbit_end - orbit_start
 
-    assert(orbit_end <= time_end and orbit_start >= time_start)
+    assert((orbit_end - time_delta) <= time_end and (orbit_start + time_delta) >= time_start)
 
     # Anchor points from which the curve is deduced
     # anchor[t] is a list of 4 known timepoints: 2 before t + 2 after t if possible
@@ -73,7 +73,7 @@ def generate_orbit(datapoints, orbit_start, orbit_end):
         if i in datakeys:
             anchor[0].append(i)
         i += 1
-
+ 
     # Pass 2: Copying the anchor over as long as no new points are encountered
     # If we do encounter a new point, shift the list to the left and add it
     last_anchor = 0
diff --git a/backend/promis/parsers.py b/backend/promis/parsers.py
index ddc6107..aa63759 100644
--- a/backend/promis/parsers.py
+++ b/backend/promis/parsers.py
@@ -28,9 +28,12 @@
 # TODO: replace ValueErrors with meaningful exception classes when integrating
 # or make something like DataImportError(), whatever
 
-def telemetry(fp):
+def telemetry(fp, cartesian=True):
     """
     Parses the telemetry .txt file used in Potential and possibly some other satellites.
+    If cartesian is true, then the parser looks for RX, RY, RZ sections and converts to
+    geographic coordinates.
+    Otherwise the parser expects V_ALT, V_LAT and V_LONG as ready-to use data. 
 
     Yields time, (time, lon, lat, alt) tuples.
     """
@@ -40,7 +43,8 @@ def telemetry(fp):
     # I'm going with route #2 for now, no particular reason, just think it will be more elegant in code
 
     # Pointers to the current reading positions in the file per section
-    sections_index = { "RX": -1 , "RY": -1, "RZ": -1 }
+    # Yes, Variant's ones have a space before the name. Yush!
+    sections_index = { "RX": -1 , "RY": -1, "RZ": -1 } if cartesian else { " V_LAT": -1, " V_LONG": -1, " V_ALT": -1 }
 
     # Regular expression to match the sections above
     sections_rx = "^@(%s)" % "|".join(sections_index)
@@ -67,8 +71,9 @@ def scan_sect(sect):
             fp.seek(sections_index[sect])
 
             # Read a line, exit the iteration if it's the end of input
+            # Variant doesn't have proper spacing, so stop at new section as well
             ln = fp.readline()
-            if ln.rstrip() == "":
+            if ln.rstrip() == "" or ln[0] == '@':
                 break
 
             # Record the new position
@@ -76,10 +81,14 @@ def scan_sect(sect):
 
             # Try to parse the data
             # NOTE: expected format: <timestamp> <float value(.)> <human readable date>, ignoring the last one
-            m = re.search("^[0-9]* ([0-9.-]*) (2.*)", ln)
+            m = re.search("^([0-9]+) *([0-9.-]+) *(2.*)?", ln)
             if m:
+                # Potential had human readable time at the end and onboard time in first column
+                # Variant seems(!) to have UNIX time in first column and no third one
+                time_mark = unix_time.str_to_utc(m.group(3)) if m.group(3) else int(m.group(1))
+
                 # Yielding a nested tuple e.g. ( "RX", (1, 432.0) ), will be converted to dict
-                yield ( sect, (unix_time.str_to_utc(m.group(2)), float(m.group(1))) )
+                yield ( sect, (time_mark, float(m.group(2))) )
             else:
                 raise ValueError("Input inconsistency detected")
 
@@ -100,7 +109,13 @@ def scan_point():
                 for k,v in nextpoint.items():
                     nextpoint[k] = v[1]
 
-                yield timemark, orbit.cord_conv(**nextpoint)
+                # Convert if the input is cartesian, otherwise just construct a class 
+                if cartesian:
+                    point_value = orbit.cord_conv(**nextpoint)
+                else:
+                    point_value = orbit.OrbitPoint(*nextpoint.values())
+
+                yield timemark,  point_value
         except StopIteration:
             pass
 
diff --git a/frontend/app/components/CesiumMap.js b/frontend/app/components/CesiumMap.js
index c11bf9e..896904e 100644
--- a/frontend/app/components/CesiumMap.js
+++ b/frontend/app/components/CesiumMap.js
@@ -486,7 +486,7 @@ export default class CesiumContainer extends Component {
 
         /* data is [lat, lon, hgt] */
         data.forEach(function(point) { // TODO temporary disabling altitude because it stores time temporarily
-            cartesians.push(Cartesian3.fromDegrees(point[1], point[0], /*point[2] ? point[2] :*/ 250000));
+            cartesians.push(Cartesian3.fromDegrees(point[1], point[0], point[2] ? point[2] *1000 : 250000));
         });
 
         return this.viewer.entities.add({