Italy/DBSN
DBSN (DataBase di Sintesi Nazionale, "National Summary Database") is a geographic dataset released by IGM (Istituto Geografico Militare, "Italian Military Geographic Institute") containing the most significative territorial informations for thematica analysis and visualizations for Italy. At the official page[1] it's possible to download the data after registering. This page was created, in compliance with the licence, to facilitate access to the resources and an extra repository.
For any further information, it is advisable to consult the official information provided by IGM.
License
DBSN is released under the license Open Data Commons Open Database License (ODbL) ver. 1.0 [2].
The licence is the same used by OpenStreetMap and is compatible for importing on OSM. However it is not entirely clear whether Contributor terms would allow to import them. Quoting from Open Database License/Contributor Terms/Open Issues#Incompatibility_with_ODBL_/_Share_A_Like_Data:
Under section 3, the CTs offer the potential to relicense data in future under another "free and open license", so even if OSM adopted another share a like license in future, it may not be compatible with ODBL just as CC-by-SA isn't compatible with ODBL.
Under section 1, Person A downloads some or all of the OSM data, they make changes to that data and offer it on their own website as required by the ODBL. Person B comes along and wants to import that data into OSM, but they can't incorporate that information back into OSM because they do not have the right to grant OSM the ability to relicense that data in future.
Available area
Data is split by province and was released in multiple steps. On 2023-08-23 all italian territory has been released.
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Abruzzo | - | [1] | [2] | 09/01/2023 |
| Abruzzo | L'Aquila | [3] | [4] | 09/01/2023 |
| Abruzzo | Chieti | [5] | [6] | 09/01/2023 |
| Abruzzo | Pescara | [7] | [8] | 09/01/2023 |
| Abruzzo | Teramo | [9] | [10] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Basilicata | - | [11] | [12] | 09/01/2023 |
| Basilicata | Matera | [13] | [14] | 09/01/2023 |
| Basilicata | Potenza | [15] | [16] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Calabria | - | [17] | [18] | 09/01/2023 |
| Calabria | Catanzaro | [19] | [20] | 09/01/2023 |
| Calabria | Cosenza | [21]/ | [22] | 09/01/2023 |
| Calabria | Crotone | [23] | [24] | 09/01/2023 |
| Calabria | Reggio Calabria | [25] | [26] | 09/01/2023 |
| Calabria | Vibo Valentia | [27] | [28] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Campania | - | [29] | [30] | 09/01/2023 |
| Campania | Avellino | [31] | [32] | 09/01/2023 |
| Campania | Benevento | [33] | [34] | 09/01/2023 |
| Campania | Caserta | [35] | [36] | 09/01/2023 |
| Campania | Napoli | [37] | [38] | 09/01/2023 |
| Campania | Salerno | [39] | [40] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Lazio | - | [41] | [42] | 09/01/2023 |
| Lazio | Frosinone | [43] | [44] | 09/01/2023 |
| Lazio | Latina | [45] | [46] | 09/01/2023 |
| Lazio | Rieti | [47] | [48] | 09/01/2023 |
| Lazio | Roma | [49] | [50] | 09/01/2023 |
| Lazio | Viterbo | [51] | [52] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Marche | - | [53] | [54] | 09/01/2023 |
| Marche | Ancona | [55] | [56] | 09/01/2023 |
| Marche | Ascoli Piceno | [57] | [58] | 09/01/2023 |
| Marche | Fermo | [59] | [60] | 09/01/2023 |
| Marche | Macerata | [61] | [62] | 09/01/2023 |
| Marche | Pesaro e Urbino | [63] | [64] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Molise | - | [65] | [66] | 09/01/2023 |
| Molise | Campobasso | [67] | [68] | 09/01/2023 |
| Molise | Isernia | [69] | [70] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Puglia | - | [71] | [72] | 09/01/2023 |
| Puglia | Bari | [73] | [74] | 09/01/2023 |
| Puglia | Brindisi | [75] | [76] | 09/01/2023 |
| Puglia | Barletta-Andria-Trani | [77] | [78] | 09/01/2023 |
| Puglia | Foggia | [79] | [80] | 09/01/2023 |
| Puglia | Lecce | [81] | [82] | 09/01/2023 |
| Puglia | Taranto | [83] | [84] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Sardegna | - | [85] | [86] | 09/01/2023 |
| Sardegna | Cagliari | [87] | [88] | 09/01/2023 |
| Sardegna | Nuoro | [89] | [90] | 09/01/2023 |
| Sardegna | Oristano | [91] | [92] | 09/01/2023 |
| Sardegna | Sassari | [93] | [94] | 09/01/2023 |
| Sardegna | Sud Sardegna | [95] | [96] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Sicilia | - | [97] | [98] | 09/01/2023 |
| Sicilia | Agrigento | [99] | [100] | 09/01/2023 |
| Sicilia | Caltanissetta | [101] | [102] | 09/01/2023 |
| Sicilia | Catania | [103] | [104] | 09/01/2023 |
| Sicilia | Enna | [105] | [106] | 09/01/2023 |
| Sicilia | Messina | [107] | [108] | 09/01/2023 |
| Sicilia | Palermo | [109] | [110] | 09/01/2023 |
| Sicilia | Ragusa | [111] | [112] | 09/01/2023 |
| Sicilia | Siracusa | [113] | [114] | 09/01/2023 |
| Sicilia | Trapani | [115] | [116] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Toscana | - | [117] | [118] | 09/01/2023 |
| Toscana | Arezzo | [119] | [120] | 09/01/2023 |
| Toscana | Firenze | [121] | [122] | 09/01/2023 |
| Toscana | Grosseto | [123] | [124] | 09/01/2023 |
| Toscana | Livorno | [125] | [126] | 09/01/2023 |
| Toscana | Lucca | [127] | [128] | 09/01/2023 |
| Toscana | Massa-Carrara | [129] | [130] | 09/01/2023 |
| Toscana | Pisa | [131] | [132] | 09/01/2023 |
| Toscana | Pistoia | [133] | [134] | 09/01/2023 |
| Toscana | Prato | [135] | [136] | 09/01/2023 |
| Toscana | Siena | [137] | [138] | 09/01/2023 |
| Region | Province | Link | Link download | Download date |
|---|---|---|---|---|
| Umbria | - | [139] | [140] | 09/01/2023 |
| Umbria | Perugia | [141] | [142] | 09/01/2023 |
| Umbria | Terni | [143] | [144] | 09/01/2023 |
Data model
The data model is documented in the official specification PDF (in italian). Inside it are listed and documented numbers and codes that allow to identify the geographic elements inside the dataset.
Data is divided gerarchically in strato ("layer", ex. "Immobili e antropizzazioni", number 02), tema ("theme", ex. "Edificato", number 02 01) and classe ("class", ex. "Edificio", number 02 01 02, code EDIFC).
Every geographic element has also "attributi" ("attributes", ex. "Tipologia edilizia", number 02 01 02 01, code EDIFC_TY), conceptually similar to OSM tags, which have a "valore" ("value", ex. "edificio tipico", number 03) and can have a "sottovalore" ("subvalue", ex. "nuraghe", number 03 01).
Mapping between DBSN and OSM data models
Incomplete list, contributions are welcome (this table can be edited on Italy/DBSN/Mapping)
| PDF page | Class (classe)
|
Attribute 1 | Attribute 2 | OpenStreetMap | Notes | |||
|---|---|---|---|---|---|---|---|---|
| Code | Code | Value | Code | Value | Italian | English | ||
| Strade / Roads | ||||||||
| 23 | TR_STR | highway=* | Strade | |||||
| 23 | TR_STR | TR_STR_TY | 01 | TR_STR_CF | 01 | highway=motorway | Autostrada | |
| 23 | TR_STR | TR_STR_TY | 01 | TR_STR_CF | 02 | highway=primary | Strada extraurbana principale | |
| 23 | TR_STR | TR_STR_TY | 01 | TR_STR_CF | 03 | highway=secondary | Strada extraurbana secondaria | |
| 23 | TR_STR | TR_STR_TY | 01 | TR_STR_CF | 04 | Maybe highway=tertiary? | Strada urbana di scorrimento | |
| 23 | TR_STR | TR_STR_TY | 01 | TR_STR_CF | 05 | highway=residential | Strada urbana di quartiere | |
| 23 | TR_STR | TR_STR_TY | 01 | TR_STR_CF | 06 | Maybe highway=unclassified? | Strada locale | |
| 27 | TR_STR | TR_STR_TY | 02 | highway=footway | Percorsi pedonali | |||
| 27 | TR_STR | TR_STR_TY | 04 | Key:highway#Link_roads | Svincoli | |||
| Edifici / Buildings | ||||||||
| 68 | EDIFC | building=* | Edifici | |||||
| 71 | EDIFC | EDIFC_USO | 0201 | building=* | Edificio del municipio, tipicamente building=civic ma potrebbe esere in altri tipi di building=*; utile per trovare il municipio in sè (amenity=townhall) | |||
| 71 | EDIFC | EDIFC_USO | 030102 | building=hospital | Edificio dell'ospedale, utile per trovare l'ospedale in sè (amenity=hospital) | |||
| 71 | EDIFC | EDIFC_USO | 0307 | building=fire_station | Edificio della caserma dei Vigili del Fuoco, utile per trovare la sede in sè (amenity=fire_station) | |||
| 69 | EDIFC | EDIFC_TY | 0305 | building=trullo | Trullo | |||
| Aree / Areas | ||||||||
| 284 | PE_UINS | PE_UINS_TY | 01 | landuse=residential | Aree residenziali | |||
| 285 | PE_UINS | PE_UINS_TY | 0301 | amenity=school | Aree scolastiche | |||
| 285 | PE_UINS | PE_UINS_TY | 0302 | amenity=hospital and/or healthcare=hospital | Aree ospedaliere | |||
| 285 | PE_UINS | PE_UINS_TY | 0303 | landuse=cemetery | Cimiteri | |||
| Aree naturali protette / Protected natural areas | ||||||||
| 203 | AR_NAT | leisure=nature_reserve and/or boundary=protected_area | Aree naturali protette | |||||
| 203 | AR_NAT | AR_NAT_TY | 01 | boundary=national_park + protect_class=2 | Parchi nazionali | |||
| 203 | AR_NAT | AR_NAT_TY | 02 | boundary=protected_area + ? | Parchi naturali regionali e interregionali | |||
Working with the data
View the data
The content of the DBSN is distributed via the .zip files listed above. You can directly explore the data from these zips with a GIS tool. For example, to open it in QGIS simply drag the file onto the QGIS window and then click "Add layer".
Working with the data from command line
To filter and elaborate the data firstly you need to extract the zip files.
For example this command extracts the content of AG_dbsn_1d0K3z.zip in the folder AG_unzipped (creating it if it does not exist):
unzip 'AG_dbsn_1d0K3z.zip' -d 'AG_unzipped'
Inside the extracted folder you will find a series of files with metadata and instructions and a folder whose name ends in ".gdb", which contains an ESRI Geodatabase.
Once you know the code of the class to which the objects of interest belong and the values that the attributes they must have, it is possible to filter these elements with GDAL. For example, this command filters the hospitals (class code EDIFC, attribute edifc_uso=030102) present in the province of Agrigento (the folder extracted above), transforms them into WGS84 and saves them in a .geojson file:
ogr2ogr -f 'GeoJSON' -t_srs 'EPSG:4326' -where "EDIFC_USO = '030102'" "AG_ospedali.geojson" "AG_unzipped/Agrigento_dbsn.gdb" "EDIFC"
Working with the data fro mthe code
All libraries based on GDAL (including fiona e GeoPandas) allow to open the file with the driver OpenFileGDB.
Other resources
Code and tools to use the data
- GitHub repository napo/dbsnosmcompare
- GitHub repository Danysan1/dbsn-import
- GitHub repository musuruan/osm_imports
Analysis on data and articles
- "OpenStreetMap conquista anche l’Istituto Geografico Militare" on de.straba.us
- Notebook on dsantini.it