Download Design of Knowledge Management (KM) Basin-level Application Systems Theme-database

Design of Knowledge Management (KM) Basin-level Application
Systems Theme-database
HAN Suhua, LEI Xiaohui, TIAN Yu
Department of Water Resources Research, China Institute of Water Resources Research and
Hydropower Research, P.R.China, 100044
[email protected]
Abstract: Theme-database is one part of KM valley-level basic platform composition, and the most
basic work of the system construction. Through systematic classification theme-database sorts out water
cycle simulation analysis and constructs relative information, builds basic information platforms, and
also provides the necessary data conversion interface to knowledge management (KM) basin-level
applications. In this paper, the development and design of theme-database is introduced.
Keywords: database, design principles, settle Organization
Knowledge Management (KM) basin-level application system is the core of GEF Basin River project,
is the heart of the Haihe River Basin water resources and water environment management , ET
Management , strategic research, and provides data storage, exchange, operational support, analysis and
forecasting and other information services to different stages of project implementation.
Theme-Databases are important component of KM basin-level basic platform. Through systematic
classification theme-database sorts out water cycle simulating analysis and constructs relative
information, builds basic information platforms, and also provides the necessary data conversion
interface to knowledge management (KM) basin-level applications, and ultimately to achieve 1) Basic
data and observational data acquisition and primary processing 2) storage basin business management
and the core model results of the analysis functions. In view of the importance of theme data capabilities
and objectives, which are introduced in details in development. This paper will have a description in
detail.
1 Design Principles
Determining database design principle is the core of database design, premise and key to success or
failure of the system and also an important factor of the measurement of the system. The basic principles
of database design are as follows:
• Comprehensive and accurate, structural integrity of clarity
Comprehensive and accurate, and the structure is clear: field type, length should accurately reflect the
needs of business processes, and the field type, length used should meet current and future business
needs. Strictly set the restricting conditions for the database integrity to check whether the data in the
database meet the semantics of the definition of conditions, including entity integrity, referential
integrity and user-defined integrity.
• Good expansibility
To meet the continuous development of information resources and information systems and changing
needs, the database should have good expansibility. Database’s expansibility reflects on the expansibility
of storage space and database structure.
• Relation consistent
Should accurately state the relation between the different data tables. In the system, relations limited to
one-to-one and one-to-several. Several to several relations1 not designed in tables.
• Standardization
Follow the database design specifications and various related standards.
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• Loose coupling
Among the various sub-systems should follow the principle of loose coupling, and do not set a
mandatory constraint relation. The link between subsystems can be set through re-entering, queries,
procedures, etc. Relation fields among subsystems are redundantly stored.
• Ensure efficiency, appropriate redundancy
In order to ensure efficiency and to save software costs (rather than hardware costs), appropriate
redundancy in the database is acceptable.
2 Data requirements analysis
The decision support on integrated management of water resources and water environment refers to the
data of socio-economy, graphics, images, hydrology, meteorology, water resources utilization.
According to the information sources and use, they will be divided into common categories of
information and special categories of information; the common categories of information is shared with
other systems, including information such as graphics, images, socio-economical, hydrological,
meteorological, water quality and other information; specific type of information is used for water
resources management and water environment management which also includes two categories, namely,
the original monitoring, statistics and water resources, water environment management results data. The
amount of water information in monitoring information includes precipitation, surface water
(including inter-basin water transfer), groundwater, the total quantity of water and other water resources
(including industrial water, sewage treatment and reuse, seawater utilization), etc.; water quality
monitoring information mainly refers to rivers, reservoirs, lakes, water quality status and grading,
wastewater emissions and classification of major pollutants in year period, the dry season and wet
period.
Outcome data are comprehensive assessment of water resources and optimizing the outcome of
configuration information mainly of the forms of text, charts, thematic maps such as: 1) water resources,
water environment predict data; 2) configuration management data of water resources, including water
resource prediction, planning results, development and utilization of water resources, etc.; 3) water
function zoning data; and so on.
3 Sort out data
Theme-database will focus on the themes of water resources, water environment and water resources water environment integrated management to do organizations and storage of data. Its emphasis is to do
water resources data analysis and emphasizes on establishment of a shared database among various
application systems.
In view of the data needs theme-database will involve a substantial number. Sort out data is the most
basic. Since one of the aims of knowledge management (KM) basin-level application development is to
provide a whole Haihe River basin information exchange and sharing platform to users, therefore, KM
basin-level application system Data sort out range includes basin, sub-basins (sub-basin of Zhangweinan
canal) the integrated management of water resources and water environment, knowledge management
(KM) data, the outcome of river coding system, GEF Haihe River Basin project’s IWEMPs, strategic
studies, thematic studies and the data for and from ET remote sensing monitoring system.
Theme database is composed by basic database, monitoring database, theme bases and meta-databases.
Basic database is composed by spatial database, spatial-attribute database and socio-economic databases,
while monitoring database is composed by water resources, water environment and meteorological
databases, and theme database is composed by water resources management, water environment
management, integrated management of water resources and water environment, Remote sensing
monitoring of ET management, administration, license management, model base. The metabase is
composed by space, properties, themes, data service and so on.
According to the information category, theme databases can be divided into attribute databases and
spatial databases. Bases on different sectors and themes of simulated level of water recycling ,attribute
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database are divided into several sub-databases including the binary WEP model database,
multi-objective analysis (DAMOS) database, planning configuration (ROWAS) database, water quality
simulation analysis of a database groundwater simulation analysis database; spatial database includes
administrative division, water districts, river network, surface reservoirs, water conservancy, water units,
sub-basins, contour maps with other electronic component.
According to the principles of database design, the status of currently available data, needs of the
system’s sustainable development, taking into account the data separability, completeness and rationality,
the database information is divided into the following categories:
*The class of basic elements
Such data stores the most basic physical quantities of system configuration, such as: the information of
the administrative districts within the system, water district, station, groundwater observation wells,
irrigation, emergency water sources, lakes, rivers, water ports, channels, reservoirs, etc. This part data is
the base of the other class in database.
*Network relational data class
Such data stores various channels relation in system memory. Such as the relation between upstream and
downstream surface water systems, external water transfer between the water supply, drainage systems,
etc. This part of data describes all the hydraulic connection in the study area to configure.
*Baseline survey data class
Baseline survey data mainly store the data of actual observation and statistical analysis and data from
the water sector based on actual situation.
Including socio-economic baseline; transpiration evaporation of the baseline (rural ET, urban ET);
production, living, and ecological water consumption baseline; agricultural groundwater extraction
baseline; pollutant emissions into the river baseline; into the Bo Sea, or exit the water release, water
quality baseline (COD , total ammonia nitrogen, etc.).
*Basic data class
Basic data class mainly store long series of data after calculation. A long series of rainfall data,
evaporation and so on.
*Spatial database
Spatial data is mainly available for the GIS, and the basic spatial characteristics of data include
The basic electronic charts: Administrative Division (national, provincial boundaries, local community,
county), the natural partition (the scope of watershed and river systems), all levels water resource zoning
charts (2 zone, three zones, etc.); water function zoning charts; water environmental function zoning
charts, etc., reservoirs and lakes, rivers, water conservancy projects, measure stations, etc., so as to
reflect various water quantity data’s spatial distribution characteristics and trends based on the above
charts. There is also theme chart data based on the original data, basic data and the result data.
Theme Information: Digital Elevation Model DEM (1km, 30m resolution, etc.); hydro-geological map;
soil distribution map; land use map; river network water system information; vegetation cover
information.
*Model data class
The system will put model’s various constraints and objective functions in the database. When calling
the model, according to different research needs, the user can select model or module from the model
base.
*Result data class
Result data class store the result data from model class or module simulation, as well as the further
statistical analysis of result data. These results data can be provided to the KM valley level application
system for the Haihe River basin’s integrated management of water resources and water environment, as
well as to provide data for rational allocation of water resources.
4 Data Organization
According to the different nature of data and information in the system database, and in order to
facilitate the classification of the data and database maintenance, data tables designed should be to
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classified and coded. The classification number is composed of six numbers, and all the specific
meaning of the data bits is as follows:
Table 3-9 Data Sheet Classification coding Method
meaning
seat
valu
e
1
0
basic elements
1
binary WEP Models
2
groundwater model
5
rational allocation model (ROWAS)
6
Multi-program analysis model (DAMOS)
7
water quality model
8
General Information
G
GIS Information
Z
database management information table
2 to 3
4 to 6
2 classification. Custom content by the model. For example: 01: model
input data; 02: Output: 03: that model calculation results; 04 statistical
analysis and so on.
said the order code
In order to facilitate database management queries make the following convention on the database table
name: table prefix unified as "WR_" means water resources information.
Table 3-10 provides a database table suffix
Module
basic elements
Binary WEP Models
Groundwater
Rational allocation (ROWAS)
Multi-program analysis (DAMOS)
General Information
GIS Information
Database management information table
Suffix
_B
_E
_G
_W
_D
_T
comply with the provisions of GIS
Data dictionary is an important part of the database for storing relative information of database,
including: a database information of all objects in the database, such as tables, views, clusters, and
indexes and so on. Column default values, the integrity of restricting information, user name, users and
its roles and permissions granted and other information.
Theme database has a complete data dictionary which provides a database table name, logo, table
numbers, and all the features of the table. At the same time use data dictionary to build the theme
database.
5 Data Sharing
Data sharing is to integrate the various types of data, and based on the need of business data sources, to
define the scope of shared data of KM and the binary model, define the scope of data needed by the dual
model and the various sources of data, and define data generated from the binary model for other
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applications.
Data Dictionary for model dynamic management required data and shared data boundaries, manage the
data exchanged boundaries between KM and binary.
Two ways of Data sharing are subscription / distribution and condition queries.
Subscribe / Release: Through KM information service interface to define the subscribe theme, and then
based on the situation of all applications on the use of shared data, we assign different themes to the
corresponding application system. When the data of shared database updates, KM sends the data to the
appropriate binary model system.
Binary model system and the application system put the data for sharing in the Schema document using
the prescribed form to form a data update XML documents, using the data exchange subsystem to send a
document to a shared subsystem to do data update operation. Subject database data update completes,
the system will make an analysis on data differences, if the system find data has been updated, then send
this message to the various application systems to facilitate the timely start the corresponding data
processing.
Fund Project:
The paper supported by Natural Sciences Foundation of China 50721006 50879091 , the National
Basic Research Program of China (2006CB403408),and the GEF-Haihe KM Application System
Development in the Haihe Basin (HW7-17)
（
，
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Author: Han Suhua: senior engineer, major of water resources engineering, mainly engaged in research
of development of water resources system. Email: [email protected].
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