CN108228747A - Data genetic connection visualized graphs system in data improvement - Google Patents
Data genetic connection visualized graphs system in data improvement Download PDFInfo
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Abstract
The present invention provides the data genetic connection visualized graphs system during a kind of data are administered, and including information node, also includes with lower module：Stream compression circuit：Refer to the path of the stream compression；Extract at least one of polices node, cleaning rule node, transformation rule node, loading rule node and processing regular node node；The extraction polices node is used to illustrate how data extract；The cleaning rule node is used to represent the screening criteria of the data during the stream compression；The transformation rule node is used to represent the variation standard of the data during the stream compression；The loading rule node is used to illustrate how data are put in storage；The processing regular node is used to represent the data filing or destruction.The present invention is by the genetic connections of different levels, and the understanding data that can be will be apparent that migrate circulation, and the management of assessment, data for data value provides foundation.
Description
Technical field
The present invention relates to enterprise's portrait field, the data genetic connection visualized graphs system in particularly a kind of data improvement
System.
Background technology
In human society, genetic connection refers to the interpersonal relationships generated by marriage or fertility.Such as parent and child
Relationship, siblings' relationship and other kinships derived from therefrom.It is the inborn inherent relationship of people,
Human society is just existing at the beginning of generating, and is a kind of social relationships formed earliest.
In the current big data epoch, data burst increases, and magnanimity, various types of data are quickly generating.
The data information of these bulky complex is merged by marriage, converts transformation, circulation circulation, and generate new data, pooled
The ocean of data.
The generations of data, processing fusion, circulation circulation, it is natural between data to form a kind of relationship to final extinction.
We use for reference a kind of relationship similar in human society to express this relationship between data, and the referred to as blood relationship of data is closed
System.Different from the genetic connection in human society, the genetic connection of data further comprises some distinctive features：
1. belongingness.In general, specifically tissue or individual, data have belongingness to specific attribution data.
2. polyphyly.Same data can have multiple sources（Multiple fathers）.One data generation can be multiple numbers
According to what is generated by processing, and this process can be multiple.
3. trackability.The genetic connection of data embodies the life cycle of data, embodies data from generating extinction
Whole process, have trackability.
Hierarchy.The genetic connection of data has levels.The description to data such as classification, conclusion, summary to data
Information forms new data, and different degrees of description information forms the level of data.
How the visualization of data genetic connection is become everybody and compare focus of attention.
One is disclosed in sohu.com《Have relationship by blood between data-data must not administer the genetic connection that is ignorant of and comb
Method》（Network address is http://www.sohu.com/a/161142366_99934777）, disclose a kind of data genetic connection
Visual presentation system, within the system, including information node, stream compression circuit, cleaning rule node, transformation rule section
Regular node is destroyed in point and data filing, can clearly show data genetic connection.On the one hand the invention lacks for each
The setting of kind rule so that the judgement of cleaning, conversion and destruction is susceptible to problem, and still further aspect lacks the extraction to data
The description of method and loading strategy easily makes the visualized graphs of data genetic connection generate deviation.
Invention content
To solve the above-mentioned problems, the data genetic connection visualized graphs system in being administered the present invention provides a kind of data
For system by the genetic connection of different levels, the understanding data that can be will be apparent that migrate circulation, are assessment, the data of data value
Management provide foundation.Detailed rule is set, data are preferably combed with facilitating.
The specific technical solution of the present invention is as follows：
The present invention proposes the data genetic connection visualized graphs system during a kind of data are administered, and including information node, also wraps
Containing with lower module：
Stream compression circuit：Refer to the path of the stream compression；
Extract polices node, cleaning rule node, transformation rule node, transformation rule node, processing regular node and loading rule
Then at least one of node node；
The extraction polices node is used to illustrate how data extract；
The cleaning rule node is used to represent the screening criteria of the data during the stream compression；
The transformation rule node is used to represent the variation standard of the data during the stream compression；
The loading rule node is used to illustrate how data are put in storage；
The processing regular node is used to represent the data filing or destruction.
Preferably, described information node is used to show the owner of data and data hierarchical information or end message.
In said program preferably, described information node includes host node, data flow egress and data inflow section
At least one of point.
In said program preferably, the host node is located at the center of the visualized graphs, is the visualization
The core node of figure.
In said program preferably, the data flow ingress is the father node of the host node, represents that data are come
Source includes at least one data flow ingress in the visualized graphs.
In said program preferably, the data flow egress is the child node of the host node, represents data
Whereabouts includes at least one data flow egress in the visualized graphs.
In said program preferably, terminal node is a kind of special data flow egress, and mark data is not
It circulates down again.
In said program preferably, the stream compression circuit is come out from the data flow ingress toward the main section
Point convergence, and flow out toward the data flow egress and spread from the host node.
In said program preferably, the data spread circuit table and reveal direction, data update magnitude and data more
The information of at least one dimension in the new frequency.
In said program preferably, in the visualized graphs, the data update magnitude passes through the thick of lines
It is thin to show.
In said program preferably, in the visualized graphs, length that the data update frequency passes through lines
It spends to show.
In said program preferably, described collect is divided into full dose extraction and increment extraction.
In said program preferably, the cleaning refers to data receiving according to the requirement of data to filter access
The process of data.
In said program preferably, the cleaning rule node is located on the stream compression circuit, described in expression
Data standard described in data fit on stream compression circuit can continue circulation and go down.
In said program preferably, the conversion refers to data to need to carry out specially treated to meet demand data
The process of the requirement of side.
In said program preferably, the transformation rule node is located on the stream compression circuit, represents data
Circulate the variation or transformation occurred in the process.
In said program preferably, the transformation rule is included according to total score, and practical scoring is converted to what is specified
Divide system.
In said program preferably, the loading is divided into full dose loading and step increment method.
In said program preferably, the loading rule includes the following contents：
1）Paging full dose extracts data, and step increment method is realized according to the period of loading policy definition；
2）Comparison loading data and target data still do not update target data according to the update of the loading strategy decision of configuration.
In said program preferably, the processing refers to the mistake data filing or destruction according to processing rule
Journey.
In said program preferably, the processing rule refers to, according to enterprise requirements setting processing condition, work as data
After meeting the treatment conditions, which is handled.
Data genetic connection visualized graphs system in data improvement proposed by the present invention, is to utilize computer graphics
And image processing techniques, it converts the data into figure or image is shown on the screen, and carry out the theory of interaction process, side
Method and technology.Visually meaning is to transmit signal fasterly, and image intuitively shows data and its relationship
Come, user is facilitated to inquire into, essence is explored, pinpoints the problems.
Description of the drawings
Fig. 1 is a preferred embodiment of the data genetic connection visualized graphs system during data according to the invention are administered
Visualization model schematic diagram.
Fig. 2 is the structural data genetic connection of enterprise's portrait system according to the invention based on multi objective dimensional model
An embodiment hierarchical chart.
Fig. 3 is the file server data blood relationship of enterprise's portrait system according to the invention based on multi objective dimensional model
The hierarchical chart of one embodiment of relationship.
Specific embodiment
Embodiment 1
Visualization from technological concept, is using computer graphics and image processing techniques, converts the data into figure
Or image is shown on the screen, and carries out the theory of interaction process, methods and techniques.Visual meaning is rapid fast
Signal is transmitted promptly, and image intuitively shows data and its relationship, and user is facilitated to inquire into, explore essence, finds to ask
Topic.
For the genetic connection of data, visualization is particularly important.Only by visualizing, what genetic connection can be just apparent from
Show in front of the user.
According to the characteristics of data genetic connection, we devise the genetic connection visualized graphs of data.
According to the difference of performance meaning, the visualized graphs of genetic connection include 5 kinds of visualized elements, are distributed in figure
Different location.As shown in Figure 1, visualized elements include father node 100, data flow egress 101 and the data in information node
Node 102 is flowed into, stream compression circuit 110 is further included, extracts polices node 120, cleaning rule node 130, transformation rule section
Point 140, loading rule node 150 and processing regular node 160.
1st, information node
Information node is used for showing the owner of data and data hierarchical information or end message.According to genetic connection level not
Together, data information different from.There was only the information of the owner in owner's level, other levels then include owner information and
Data hierarchy information or end message, such as the genetic connection of the interfield of relational database, the description information of the node is just
It is：Owner's database tables of data data fields.
There are three types of types for information node：Host node 100, data flow egress 101 and data flow into node 102.
There are one host nodes 100, is the core node of visualized graphs positioned at the centre of whole figure.Figure is shown
Genetic connection be exactly this node genetic connection, other genetic connections unrelated with this node do not show on figure, with
Ensure the simple, clear of figure.
Data flow ingress 101 can have multiple, be the father node of host node, data source be represented, positioned at whole figure
Left side.
Data flow egress 102 can also have multiple, be the child node of host node, the whereabouts of data represented, positioned at entire
The right side of figure.Data flow egress includes a kind of special node, i.e., terminal node, terminal node 103 are a kind of special
Data flow egress represents that data no longer circulate down, and this data are generally used to visualize.
2nd, stream compression circuit 110
What stream compression circuit showed is the circulation path of data, is from left to right circulated.Stream compression circuit is flowed into from data and is saved
The convergence of dealing host node is pointed out, and is flowed out from host node toward the diffusion of data flow egress.
Stream compression circuit is demonstrated by the information of three dimensions, is direction, data update magnitude, data update frequency respectively
It is secondary.
The manifestation mode in direction, does not do special design, and acquiescence from left to right circulates；
The magnitude of data update is showed by the thickness of lines.Lines are thicker to represent that data magnitude is bigger, and lines get over detailed rules and regulations table
Registration is smaller according to magnitude.
The frequency of data update is showed using the length of lines middle conductor.Line segment is shorter to represent that the update frequency is higher, line
Duan Yuechang represents the newer frequency the end of month, and a solid line then represents only to circulate primary.
3rd, polices node 120 is extracted
Polices node is extracted for illustrating data are how to extract.The extraction of data is divided into full dose extraction and increment extraction.
Strategy is extracted to be represented with a circle for indicating capitalization " E " on visualized graphs.Check specific extraction
Policing action is also very simple, and mouse is moved on the circle for indicating capitalization " E ", then can automatic Display extraction strategy.
4th, cleaning rule node 130
Cleaning rule node is used for showing the screening criteria during stream compression.A large amount of data distribution in different places,
Requirement of each place to the quality of data is different, and data receiving can filter access according to oneself requirement to data
Data, these requirements just form data standard, and do data cleansing according to these standards.
Cleaning rule might have a variety of.Such as requirement cannot be null value, require to meet certain form.In visualized graphs
On, cleaning rule is represented with a circle for indicating capitalization " C ", various rules is simplified expression, to ensure figure
Succinctly, clearly.Check that the operation of Rule content is also very simple, mouse is moved on the circle for indicating capitalization " C ", then can be certainly
Dynamic displaying standard schedule list.
In on stream compression circuit, representing the data fit to circulate on the circuit, these are marked the simple pattern bit of cleaning rule
Standard could continue circulation and go down.
5th, transformation rule node 140
Transformation rule node is similar to cleaning rule node in the form of expression, the circle table for indicating bigger alphabetical " T " with one
Show.On stream compression circuit, for showing the variation occurred during stream compression, transformation.
The data come out from data providing, it is sometimes necessary to demand data side can be just linked by carrying out specially treated, this
Kind processing may be fairly simple, such as：Only intercept first four of source data.May also be extremely complex, it is special to need to use
Formula.In terms of visualization, in order to ensure the succinct, clear of figure, simple processing has been done.Check that data have passed through those conversions
Rule is also very simple, and mouse is moved on the circle for indicating capitalization " T ", then can automatic Display transformation rule inventory.
6th, loading rule node 150
Polices node is loaded for illustrating data are how to be put in storage.The loading of data is divided into full dose loading and step increment method.
Loading strategy is represented on visualized graphs with a circle for indicating capitalization " L ".Check specific loading
Policing action is also very simple, and mouse is moved on the circle for indicating capitalization " L ", then can automatic Display loading strategy.
7th, regular node 160 is handled
Data have life cycle, and when data no longer have use value, his life just finishes either filing or straight
Outbound is ruined.
It is extremely difficult to judge whether data are also equipped with use value, needs to design some conditions, when these conditions are met
After, it is considered as data and is not having use value, can file or destroy.
On visualized graphs, we devise a circle for indicating capitalization " R ", for simple expression data
Filing and destruction rule.Mouse is moved on the circle for indicating capitalization " R ", then can automatic Display filing and to destroy rule clear
It is single.
Embodiment 2
The visualization of genetic connection is a more complicated process, can be referred to currently without molding visualized graphs, I
This genetic connection visualized graphs component for designing, the genetic connections of data can be clearly expressed, to the data of tissue
It administers helpful.
The effect of data genetic connection, to sum up having following aspects：
1. data are traced to the source
It traces to the source, refers to seeking foundation, source.The data that we analyze and process, possible source is very extensive, there is government
Data have the data of internet, there is the data obtained by data trade from third party, also owned data.It is different
The data in source, the quality of data is irregular, is also not quite similar on the result influence of analyzing and processing.When data are abnormal, I
Need to track abnormal the reason of occurring, risk control in appropriate level.
The genetic connection of data embodies the ins and outs of data, us can be helped to track the source of data, tracks data
Processing procedure.On the genetic connection visualized graphs of data, the left side of host node is exactly data source node, very clearly,
It is very clear.Data have passed through those conversions and can also be found out from visualized graphs, the analysis to abnormal data producing cause
It is very useful.
2. assess data value
The value of data is very important in data trade field, is related to the price of data.Data value is assessed,
Require foundation.Data genetic connection can provide foundation in terms of several to the assessment of data value：
1）, data audient.On genetic connection figure, the data flow egress on the right represents audient, that is, demand data side, data
Party in request's more multilist shows that data value is bigger；
2）, data update magnitude.In data genetic connection figure, the lines of stream compression circuit are thicker, represent the amount of data update
Grade is bigger, has reacted the size of data value to a certain extent；
3）, the data update frequency.Data update is more frequent, represents that data are more fresh and alive, value is higher.On genetic connection figure, number
Line segment according to circulation circuit is shorter, and update is more frequent.
3. data quality accessment
From the genetic connection figure of data, it may be convenient to see the standard schedule of data cleansing, this inventory has reacted logarithm
According to the requirement of quality.
4. data filing, the reference destroyed
If data, without audient, data just lose the value used.From the genetic connection figure of data, rightmost does not have
There is back end, it is possible to go whether the data representated by assessment host node will file or destroy.
Embodiment 3
Cleaning rule is as follows：
1. judging whether there is Chinese character in content, if there is Chinese character, true is returned, otherwise returns to false；
2. judging whether content is integer, if it is integer, true is returned, otherwise returns to false；
3. judging whether content is percentage, if it is percentage, true is returned, otherwise returns to false；
4. if Json character strings are not [] and unserializing success, true is returned, otherwise returns to false；
5. judge that content whether by entering the Character segmentation of ginseng, if the Character segmentation by entering ginseng, returns to true, otherwise returns
false；
6. judging numerical value whether in specified value domain, if in specified value domain, true is returned, otherwise returns to false；
7. registered permanent residence classification verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
8. personnel's Employment verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
9. labour capacity classification check, if value returns to TRUE in the range of code value and otherwise returns to false；
10. family relationship classification check, if value returns to TRUE in the range of code value and otherwise returns to false；
11. health status classification check, if value returns to TRUE in the range of code value and otherwise returns to false；
12. organization's coding checkout, if value returns to TRUE in the range of code value and otherwise returns to false；
13. power classification verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
14. political affiliation code check, if value returns to TRUE in the range of code value and otherwise returns to false；
15. academic code check, if value returns to TRUE in the range of code value and otherwise returns to false；
16. types of identity documents verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
17. accounting profession technical qualification type checking, if value returns to TRUE in the range of code value and otherwise returns to false；
18. Unit code verification is made a report on, if value returns to TRUE in the range of code value and otherwise returns to false；
19. administrative penalty current state verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
20. grain index verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
21. degree of breaking one's promise verifies, if value returns to TRUE in the range of code value and otherwise returns to false；
If return is TRUE, data receiver is sent the data to, if it is false to return, by the data mistake
Filter, is not sent to data receiving.
Embodiment 4
Transformation rule is as follows：
1st, the Chinese and number in character string are detached, returns to the character string of specified type；
2nd, number is converted into currency style, returns to the number of currency style；
3rd, text repeats to show multiple, returns to text repeatedly；
4th, the blank character at removal character string both ends, if becoming empty or null, returns to null, otherwise returns to former character string；
5th, clear character string if former character string is ended up with clear character string, removes this ending, after being then back to removal
Character string, otherwise return to original character string；
6th, conversion time character string is specified format, returns to the character string of specified format；
7th, value type is converted into percentage, returns to the percentage of specified digit；
8th, by value type（Comprising, e, E）Standard attribute is converted into, returns to the number of standard attribute；
9th, null will be converted to for null value in database table；
10th, the character string is directly taken if character string is digit strings, if the data that scientific notation mode records
It needs to be converted to corresponding data character string；
11st, gender information is obtained according to ID card No., returns to the gender information after obtaining；
12nd, date of birth information is obtained according to ID card No., returns to the date of birth information after obtaining；
13rd, according to total score, practical scoring is converted to point system specified.
Embodiment 5
The loading rule includes as follows：
1st, paging full dose extracts data, and step increment method is realized according to the period of loading policy definition；
2nd, comparison loading data and target data still do not update target data according to the update of the loading strategy decision of configuration.
Embodiment 6
As shown in Fig. 2, the hierarchical structure of structural data genetic connection being stored in database of description, is most typical
A kind of hierarchical structure of genetic connection.For different types of data, the hierarchical structure of genetic connection has fine distinction.
In general, data, which all belong to some tissue or someone, data, the owner.Data are in different institutes
It circulates, merge between the person of having, form a kind of relationship connected between the owner by data, be the one of data genetic connection
Kind, top layer is in hierarchical structure.This relationship has clearly showed supplier and the demander of data.
Database, table and field are the storage organizations of data.Different types of data have different storage organizations.Storage
The structures shape hierarchical structure of genetic connection.So some difference of the genetic connection hierarchical structure of different types of data.Example
Such as, for the data stored with file server, the hierarchical structure of genetic connection is as shown in Figure 3.
The genetic connection of different levels data embodies different meanings.Owner's level embodies the provider of data
And party in request, other levels then embody the ins and outs of data.By the genetic connection of different levels, can will be apparent that
Understand data migrates circulation, and the management of assessment, data for data value provides foundation.
For a better understanding of the present invention, it is described in detail above in association with specific embodiments of the present invention, but is not
Limitation of the present invention.Any simple modification made to the above embodiment of every technical spirit according to the present invention, still belongs to
In the range of technical solution of the present invention.In this specification the highlights of each of the examples are it is different from other embodiments it
Locate, the same or similar part cross-reference between each embodiment.For system embodiment, due to itself and method
Embodiment corresponds to substantially, so description is fairly simple, the relevent part can refer to the partial explaination of embodiments of method.
Claims (10)
1. a kind of data genetic connection visualized graphs system in data improvement, including information node, which is characterized in that also wrap
Containing with lower module：
Stream compression circuit：Refer to the path of the stream compression；
It extracts at least one in polices node, cleaning rule node, transformation rule node, loading rule node and processing regular node
Kind node；
The extraction polices node is used to illustrate how data extract；
The cleaning rule node is used to represent the screening criteria of the data during the stream compression；
The transformation rule node is used to represent the variation standard of the data during the stream compression；
The loading rule node is used to illustrate how data are put in storage；
The processing regular node is used to represent the data filing or destruction.
2. the data genetic connection visualized graphs system in data improvement according to claim 1, it is characterised in that：Institute
Information node is stated for showing the owner of data and data hierarchical information or end message.
3. the data genetic connection visualized graphs system in data improvement according to claim 2, it is characterised in that：Institute
It states information node and includes at least one of host node, data flow egress and data inflow node.
4. the data genetic connection visualized graphs system in data improvement according to claim 3, it is characterised in that：Institute
The center that host node is located at the visualized graphs is stated, is the core node of the visualized graphs.
5. the data genetic connection visualized graphs system in data improvement according to claim 4, it is characterised in that：Institute
The father node that data flow ingress is the host node is stated, data source is represented, includes at least one in the visualized graphs
A data flow ingress.
6. the data genetic connection visualized graphs system in data improvement according to claim 5, it is characterised in that：Institute
The child node that data flow egress is the host node is stated, the whereabouts of data is represented, includes at least in the visualized graphs
One data flow egress.
7. the data genetic connection visualized graphs system in data improvement according to claim 6, it is characterised in that：Eventually
End node is a kind of special data flow egress, and mark data no longer circulates down.
8. the data genetic connection visualized graphs system in data improvement according to claim 6, it is characterised in that：Institute
It states stream compression circuit out to converge toward the host node from the data flow ingress, and is flowed out from the host node toward described
Data flow egress is spread.
9. the data genetic connection visualized graphs system in data improvement according to claim 8, it is characterised in that：Institute
It states data and spreads the information that circuit table reveals at least one dimension in direction, data update magnitude and the data update frequency.
10. the data genetic connection visualized graphs system in data improvement according to claim 9, it is characterised in that：
In the visualized graphs, the data update magnitude is showed by the thickness of lines.
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