# Data model specifying system objects and the relationships amongst them (ER diagram)

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1 Data model specifying system objects and the relationships amongst them (ER diagram) Document for activity 5.3 WP 5 TESAF with the support of IGR and UM 1

2 Contents 1 Introduction Spatial database and spatial data GeoSEE data structure Spatial Reference System Spatial Data Types Topology rules Point rules Line rules Polygon rules GeoSEE geodatabase data Data Data description GeoSEE ER Model References

3 1 Introduction The spatial database occupies a central position in the development of the GeoSEE spatial information system. This document deals with the data structure and geodatabase structure and puts together a specification about the characteristics of the types of geographic objects to be included in the database, how the database storing geographic information will be structured, and used. 1.1 Spatial database and spatial data A spatial database system is a database system with additional capabilities for handling spatial data. It offers spatial data types in its data model and query language. The simplest spatial data types are point, line and polygon. They provide a fundamental abstraction for modeling the geometric structure of objects in space, their relationships (l intersect r), properties (area(r)>1000) and operations (intersection (l,r) the part of lying within r). The following spatial database and spatial data descriptions are extracted from the Spatial Data Types for Database Systems book wrote by Schneider in The fundamental properties of spatially-referenced objects can be classifies in non-geometric (non-spatial, thematic) and geometric (spatial) properties. Nongeometric properties describe attribute-based data which are usually expressed by standard alphanumerical data, e.g. the population or name of a city. Geometric properties can be distinguished in metric (locational) and topological features. Metric features describe shape (geometry, structure), location, extent and measurements of spatial objects in a reference system. A reference system is the standardized spatial background into which a set of spatial objects is conceptually embedded, e.g. the Cartesian coordinate system. Each point is attached to a certain reference (coordinate) point. The location of an object indicates the position of the object with regard to the selected reference system. Topological features characterize relationships between spatial objects that refer to statements concerning adjacency, connectivity, inclusion and similar relationships of objects. These relationships are independent from the used reference system and invariant under topological transformation like translation and rotation. The complexity and diversity of spatial data, their occurrence in different contexts, situations and humans different experiences with the treatment of these data, seem to be in charge of the fact that humans intuitively use several different methods to conceptualize space. Data modelling for standard applications relates to data that represent artifacts and that are dominated by business practice, rules and regulations which define how things should be understood and done. Spatial data modelling, spatial database systems, and GIS enable the user to compare the data model and the facilities of the real system with (the user's concepts of) reality. 3

4 A spatial concept is either an informal or formal description of human s understanding of space, objects within space, and relationships between these objects Traditionally, two major groups of spatial concepts are distinguished: entity-oriented concepts (or feature-based), where space is determined by the objects of interest filling space (usually it is referred to vector layer) and space-oriented concepts (position-based), where each point in space is associated with some properties or attributes (usually referred to raster layer). In the following chapter the information about the spatial database (described in this paragraph) will be applied to the GeoSEE geodatabase. 2 GeoSEE data structure This chapter describes the data structure of the GeoSEE geodatabase according to the description about spatial database presented in the paragraph Spatial Reference System Given the large number of PPs involved in the project and the different reference system used by the different countries, data to be added to the spatial database must use the WGS 84 datum (EPSG 4326). 2.2 Spatial Data Types The spatial data formats allowed are: vector data: shapefile (.shp) is a popular geospatial vector data format for geographic information system software; In GeoSEE geodatabase spatial vector data allowed are only: o o o points; lines; polygons. geo raster data (Grid data): ESRI ASCII raster format, Geographic Tagged Image File Format (.tiff+.tfw); 2.3 Topology rules Literally topology means study of places ; it is a geometric field that studies shapes properties and their geometric relationships. Typical topology concepts are adjacency, connectivity, containment, coincidence. Some topology rules govern the relationships between features within a given feature class, while others govern the relationships between features in two different feature classes or subtypes. 4

5 The topology rules for GeoSEE geodatabase are differentiated by type of vector data: Point rules A topology rule for points is: disjoint: points must be spatially separated from other points in the same layer. This ensures that points are not coincident or duplicated within the same layer Line rules Topology rules for lines are: must not overlap: lines must not overlap with lines in the same layer. This ensures that line segment should not be duplicated; must not self-overlap: line feature must not overlap themselves. No coincident segments are accepted. must not self-intersect: line feature must not cross themselves Polygon rules A topology rule for polygon is: must not overlap: interior of polygons must not overlap. The polygons can share edges or vertices, but an area cannot belong to two or more polygons. 5

6 3 GeoSEE geodatabase data This chapter describes the data that will form the geodatabase: what data will be loaded into the geodatabase and their data types. For vector data layers, the paragraph describes the attributes that the layers must have. Were used reports sent to partners for activity 5.1 ( Reports and use cases for Act. 5.1 ) and then reported in System/data requirements and functional specifications to understand which data added to geodatabase. Further help was given by activity 3.3 which lists the databases available from previous projects about geothermal and other Renewable Energy Sources (RES) and from which it is possible to extract information. 3.1 Data The data in the geodatabase are grouped by case-study locations and each location will contain the following five topics: 1. general data: contain information about national boundaries, regional boundaries, roads infrastructures; 2. environmental data: contain information about geology and water sources; 3. geothermal data: contain information about the geographical location of geothermal wells and springs, isotherms at different depths and data about heat flow; 4. RES data: contain information about solar irradiation, forestry and non-forestry biomass production; 5. combination between geothermal and other RES to calculate potential electric energy: a. combination between geothermal and solar source; b. combination between geothermal and biomass source; The spatial data will cover only the region that contains the case-study locations described in activity 4.1 and for which act. 4.2 and 4.3 have been carried out Data description Table 1 describes, for each element listed in paragraph 3.1, its data specifications. In red are described the units of measurement for the different types of data (most of these indicate the units of measure for the energy layers). 6

7 Table 1 Information about geodatabase data. Subject Layer Data format Feature type General data National boundaries Vector Polygon Regional boundaries Vector Polygon Study sites Vector Point/Polygon Road infrastructures Vector Point/ Line/ Polygons Environmental data Geology Vector Polygon Hydrography Vector Point/Line/Polygo n Geothermal data Wells Vector Point Springs Vector Point Maps of temperatures at different depths ( C) Vector or geo raster Polygon Heat flow map (mw/m 2 ) Vector or geo raster Polygon RES data Direct Normal Irradiance (DNI) (kwh/m²) Vector or geo raster Polygon Ground area available for the installation of solar thermal concentrated collectors (m²) (e.g: industrial area from Corine Land Cover 2006 map). Value or vector Polygon Forestry biomass production (kwh/year) Vector or geo raster Polygon Non-forestry biomass production (kwh/year) Vector or geo raster Polygon Potential energy Table 2 describes data reported at point 5 of paragraph 3.1. These data contains the combination of thermal potential energy and electric potential energy of geothermal source and other RES. Table 2 Combination of thermal potential energy and electric potential energy of geothermal source and other RES for geodatabase data. 7

8 Subject Layer Data format Feature type Combination geothermalbiomass Combination of potential thermal and electric energy from geothermal and forestry biomass (GWh/year) Vector or georaster Polygon Combination of potential thermal and electric energy from geothermal and nonforestry biomass (GWh/year) Vector or geo raster Polygon Combination of potential thermal and electric energy from geothermal and forestry and non-forestry biomass (GWh/year) Vector or geo raster Polygon Combination geothermal- solar energy Combination of potential thermal and electric energy from geothermal and solar energy (GWh/year). Vector or geo raster Polygon 8

9 Data attributes. Table 3 describes the mandatories attributes for vector data and Table 4 describes the value that possible geo raster data (if weren t available vector data) must have. Table 3. Mandatories attributes for vector data Layer name Attribute Description Format type National_boundaries NUTS Eurostat s NUTS (Nomenclature of territorial units for statistics) classification code Name Country name Regional_boundaries NUTS2 Eurostat s NUTS2 (Nomenclature of territorial units for statistics) classification code Name Region name (Minor administrative units)_boundaries. Only if the minor administrative unit is fundamental (i.e: for Italian provinces the name of layer is Province_boundaries). NUTS3 Eurostat s NUTS3 (Nomenclature of territorial units for statistics) classification code NUTS2 Eurostat s NUTS2 (Nomenclature of territorial units for statistics) classification code Name Province name Study_site Case-study locations. ID Feature ID Integer/ Name Study site name NUTS2 or NUTS3 Eurostat s NUTS (Nomenclature of territorial units for statistics) classification code Road_infrastructure ID Feature ID Integer/ 9

10 Layer name Attribute Description Format type Type Road type (i.e: highway, state highway, county road) Geology ID Feature ID Integer/ Type Geology type Hydrographic ID Feature ID Integer/ Forestry_biomass ID Feature ID Integer/ Tot_dm_t_y En_EL_GWh Tons of dry matter produced in a year by forestry biomass Potential of thermal energy produced from forestry biomass in GWh NonForestry_biomass ID Feature ID Integer/ Tot_dm_t_y En_EL_GWh Tons of dry matter produced in a year by non-forestry biomass Potential of thermal energy produced from non-forestry biomass in GWh DNI ID Feature ID Integer/ NUTS2 or NUTS3 Eurostat s NUTS (Nomenclature of territorial units for statistics) classification code DNI_kWh_m2 DNI value in kwh/m²/year Ground_solar ID Feature ID Integer/ NUTS2 or NUTS3 Eurostat s NUTS (Nomenclature of territorial units for statistics) classification code 10

11 Layer name Attribute Description Format type Area_m2 Area available on the ground for the installation of concentrated solar power systems (m 2 ) Wells ID Feature ID Integer/ Name or Code National well name or national well code. NUTS2 or NUTS3 Eurostat s NUTS (Nomenclature of territorial units for statistics) classification code Springs ID Feature ID Integer/ Name or Code National spring name or national spring code NUTS2 or NUTS3 Eurostat s NUTS (Nomenclature of territorial units for statistics) classification code T_(temperature)m ID Feature ID Integer/ Temperatures map at different depths (one layer for each depth). For temperature at 1000 m depth the name of layer is T_1000m (temperature)m_c Temperature in C at xxx m depth. Heat_flow ID Feature ID Integer/ HF_mW_m2 Heat flow value in mw/². HF_Forestry ID Feature ID Integer/ Combination between geothermal and forestry biomass HF_TH_GWh Potential thermal energy for geothermal source in 11

12 Layer name Attribute Description Format type energy. HF_EL_GWh Potential electric energy for geothermal source in FB_TH_GWh FB_EL_GWh Potential thermal energy for forestry biomass source in Potential electric energy for forestry biomass source in Sum_TH_GWh Sum of potential thermal energy for forestry biomass source and geothermal in Sum_EL_GWh Sum of potential electric energy for forestry biomass source and geothermal in HF_NonForestry ID Feature ID Integer/ Combination between geothermal and nonforestry biomass energy. HF_TH_GWh HF_EL_GWh Potential thermal energy for geothermal source in Potential electric energy for geothermal source in NFB_TH_GWh Potential thermal energy for non-forestry biomass source in NFB_EL_GWh Potential electric energy for non-forestry biomass source in 12

13 Layer name Attribute Description Format type Sum_TH_GWh Sum of potential thermal energy for non-forestry biomass source and geothermal in Sum_EL_GWh Sum of potential electric energy for non-forestry biomass source and geothermal in HF_Biomass ID Feature ID Integer/ Combination between geothermal and forestry, non-forestry and biomass energy. HF_TH_GWh HF_EL_GWh Potential thermal energy for geothermal source in Potential electric energy for geothermal source in FB_TH_GWh Potential thermal energy for forestry biomass source in FB_EL_GWh Potential electric energy for forestry biomass source in NFB_TH_GWh Potential thermal energy for non-forestry biomass source in NFB_EL_GWh Potential electric energy for non-forestry biomass source in Sum_TH_GWh Sum of potential thermal energy for biomass source and geothermal in 13

14 Layer name Attribute Description Format type Sum_EL_GWh Sum of potential electric energy for biomass source and geothermal in HF_Solar ID Feature ID Integer/ DNI_kWh_m2 DNI value in kwh/m²/year Co_area_m2 S_TH_GWh S_EL_GWh HF_TH_GWh HF_EL_GWh Ground area available for the installation of solar thermal concentrated collectors in m² Potential thermal energy for solar source in Potential electric energy for solar source in Potential thermal energy for geothermal source in Potential electric energy for geothermal source in Sum_TH_GWh Sum of potential thermal energy for solar source and geothermal in Sum_EL_GWh Sum of potential electric energy for solar source and geothermal in 14

15 Table 4 Possible raster layer and their values Raster name Value Description Format type T_(temperature)m Temperatures map at different depths. One layer for each depth. For temperature at 1000 m depth the name of layer is T_1000m. C Temperature at xx meters depth. Integer Heat_flow mw/m² Heat flow in mw/m² Forestry_biomass dm/t/year Tons of dry matter produced in a year by forestry biomass. NonForestry_biomass dm/t/year Tons of dry matter produced in a year by non-forestry biomass DNI kwh/m²/year Direct Normak irradiance value kwh/m²/year. HF_Forestry GWh/year Sum of potential thermal energy from forestry biomass and geothermal sources in HF_NonForestry GWh/year Sum of potential thermal energy from non-forestry biomass and geothermal sources in HF_Biomass_TH GWh/year Sum of potential thermal energy from forestry, nonforestry biomass and geothermal sources in 15

16 Raster name Value Description Format type HF_Biomass_EL GWh/year Sum of potential electric energy from forestry, nonforestry biomass and geothermal sources in 16

17 4 GeoSEE ER Model The E-R model is a conceptual design and it is a detailed, logical representation of the data for a database. The design is independent of all physical considerations. Figure 1 - GeoSEE geodatabase E-R model. 17

18 5 References Schneider, M. (1997). Spatial Data Types for Database Systems Finite Resolution Geometry for Geographic Information Systems. 18

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