Database: Entity-relationship Model

Appendix A A virtual(a) film to Entity-Relationship moulding A interoperable range to Entity-Relationship imitate Il-Yeol Song and Kristin Froehlich College of Information Science and Technology Drexel University Philadelphia, PA 19104 Abstract The Entity-Relationship (ER) deterrent example and its accomp some(prenominal)ing ER diagrams ar widely utilised for entropybase creation and Systems Analysis. M individually books and articles just domiciliate a definition of each feigninging comp matchless(prenominal)nt and give examples of pre-built ER diagrams.Beginners in info mannequining earn a great deal of difficulty accomplishment how to memory access a given occupation, what questions to ask in pronounce to build a position, what chemical formulas to use while constructing an ER diagram, and why unmatchable diagram is rectify than an new(prenominal). In this paper, on that pointfore, we nonplus step-by-step guidelines, a set of decision rules proven to be recyclable in create ER diagrams, and a case study trouble with a preferred answer as well as a set of incorrect diagrams for the problem.selective informationbase counsel System and DataThe guidelines and decision rules watch been successfully used in our beginning Database forethought Systems course for the last eight years. The case study will bequeath readers with a detailed approach to the modeling process and a deeper taking into custody of data modeling. Introduction Entity family diagrams (ERD) are widely used in database radiation diagram and systems analysis to represent systems or problem universes. The ERD was introduced by subgenus Chen (1976) in early 1976. Teorey, Yang, and Fry (1986) present an extended ER model for relational database design.The ERD models a given problem in terms of its essential elements and the interactions amidst those elements in a problem domain. The ERD tidy sum serve as the basis for databases, which store data intimately the problem domain, and which use, manipulate, and constrain that data. Experts in systems analysis and database design are adept at pick uping user requirements and hence translating them into corresponding comp atomic number 53nts of the model. M all books and articles just provide a definition of each modeling comp star and only(a)nt and give examples of pre-built ER diagrams. Beginners in data modeling have a great eal of difficulty learning how to approach a given problem, what questions to ask in devote to build a model, what rules to use while constructing an ER diagram, and why wizard diagram is better than another. 213 Appendix A A Practical Guide to Entity-Relationship modeling Ahrens and Song (1991) present a set of requirements elicitation pathfinder sentences, structured English template sentences, and some decision rules for database modeling. This paper presents a set of heuristic rules which improve upon those presented by Ahrens and Song (1991), together with a d etailed case study analysis.We accept step-by-step guidelines, a set of decision rules proven to be useful in building ER diagrams, and a case study problem with a preferred answer as well as a set of incorrect diagrams for the problem. These guidelines and decision rules have been successfully used in our beginning Database Management Systems course for the last eight years. The case study will provide readers with a detailed approach to the modeling process and a deeper looking of data modeling. The Entity-Relationship Diagram The entity affinity diagram is a graphical representation of a conceptual structure of a problem domain being modeled.The ERD assists the database designer in identifying the data and the rules that will be be and used in a database. The ERD is an implementation-independent representation of a problem domain and it facilitates communication among the end-user and the analyst. ERDs batch be easily converted into a logical database structure that can be readily implemented in a particular commercial database management system. The fundamental components of the ERD are entities, properties of entities called designates, and familys surrounded by entities. Entities Entities are PRIMARY THINGS of a problem domain about which users need to record data.Ross (1988) provides a list of candidate entity types which could be include in the model. (1) People humans who carry out some function Employees, Students, Customers (2) Places sites or locations Cities, Offices, Routes (3) Things tangible physical objects Equipment, Products, Buildings (4) Organizations Teams, providers, Departments (5) Events things that happen to some other entity at a given date and time or as in an couched sequence Employee promotions, Project phases, delineate honorariums (6) Concepts intangible ideas used to keep track of dividing line or other activities Projects, grudges, Complaints 214 stepsAppendix A A Practical Guide to Entity-Relationship Modeling These candidate entity types need to be evaluated against a particular domain being modeled. almost decision rules are discussed in a later section of this paper. Attributes Attributes are properties of entities or alliances. Entities have two types of properties identifying attributes and descriptive attributes. Identifying attributes alone(predicate)ly determine each lawsuit of an entity type. They are called entity identifiers or keys. For example, the attribute social security matter would uniquely identify each member or instance of the entity type student.Descriptive attributes of student competency include year, advisor, and grade point average. Each instance of an entity has a value for each attribute. value for grade point average might include 2. 5, 3. 45, and 4. 0. Values for year might include 1991, 1992, 1993, and 1994. Only attributes that are meaningful in terms of modeling the problem under consideration are included in the ERD. For example, we would not includ e eye color in a student database. Relationships Relationships are another basic component of the ERD. A relationship is an standoff in the midst of or among things or entities.A relationship describes a meaningful interaction that inevitably to be remembered by the system. The degree of a relationship indicates how numerous another(prenominal) entities are dynamic in the relationship. A unary relationship describes an association of an entity with itself. A binary relationship, the most common instance, describes an association between two entities. A ternary (or n-ary ) relationship is an association between three or more(prenominal) entities. The ER methods that release only unary and binary relationships are called binary models, while ER methods that allow any type of relationship are called n-ary models.For more thorough treatment of ternary relationships, see Jones and Song (1995, 1996) and Song and Jones (1995). Cardinality and Participation Constraints Cardinality is a backwardness on the relationship between two entities. Specifically, the cardinality constraint expresses the level best crook of entities that can be associated with another entity via a relationship. For example, in a binary relationship (a relationship with two participating entities), we can have three possible cardinalities oneto-one (11), one-to-many (1N), or many-to-many (MN).One-to-one cardinality says that, for entities customer and flyer, one customer can have at most one account and one account cannot be owned by more than one customer. One-to-many cardinality says that one customer can have many accounts, but one account cannot be owned by more than one customer. Many-to-many cardinality says that one customer can have many accounts and one account may be owned by many customers. 215 Appendix A A Practical Guide to Entity-Relationship Modeling Participation is withal a relationship constraint.Participation expresses the minimum number of entities that can be ass ociated with another entity via a relationship. There are two values for intimacy entireness or mandatory participation and partial(p) or optional participation. If both instance of an entity must participate in a given relationship then that entity has total participation in the relationship. But if every instance need not participate in a given relationship then the participation of that entity in the relationship is partial. Given the relationship employee whole kit for epartment, an employee has partial participation in that relationship if he or she need not work for a department. An employee has total participation in the relationship if he or she must work for at least one department. Similarly, a department has partial participation in the relationship if it can exist without having any employees. A department has total participation in the relationship if it must have at least one employee. Cardinality and participation constraints are business rules in the problem dom ain being modeled. These constraints represent the way one entity type is associated with another entity type.These constraints are also integrity constraints because they help to ensure the the true of the database. These constraints square up the ways in which data from different parts of the database can be associated. For example, lets say the cardinality of the relationship between Customer and direct is one-to-one, as in human body 1(a) below. If customer C1 is associated with account A3, then C1 cannot be associated with any other accounts and A3 cannot be associated with any other customers. 216 Appendix A A Practical Guide to Entity-Relationship Modeling (a) One to One (11)One customer can have at most one account. One account cannot be owned by more than one customer. Customer 1 CA 1 Account ER Diagram C1 C2 C3 A1 A2 A3 Occurrence Diagram (b) One to Many (1n) One customer can have many accounts. One account cannot be owned by more than one customer. Customer 1 C1 C 2 C3 CA n A1 A2 A3 A4 A5 Account ER Diagram Occurrence Diagram (c) Many to Many (nm) One customer can have many accounts. One account may be owned by many customers. Customer n C1 C2 C3 C4 C5 CA m A1 A2 A3 A4 A5 Account ER Diagram Occurrence Diagram ascertain 1.CARDINALITY The expression of the level best number of entities that can be associated to another entity via a relationship. Occurrence Diagrams show the relationships between occurrences or instances of each entity. 217 Appendix A A Practical Guide to Entity-Relationship Modeling Taxonomy in ER Modeling In an ER model, an entity is represented as a rectangle containing the name of the entity. The names of attributes are enclosed in an oval connected to the rectangle of the entity they describe. Attributes may be omitted from the diagram to avoid cluttering it and also in the early stages of development.Relationships are represented by diamonds between entities. The notation of the ERD, however, varies according to the m odeling approach used. binary star models do not use the diamond to indicate a relationship, do not represent attributes of relationships, and do not allow ternary relationships, that is, relationships between three or more entities. Martin (1989), Bachman (1992), ERWin and IDEF1X (Bruce, 1992) use the binary modeling approach. Most text books use n-ary modeling, including Elmasri and Navathe (1994), Hawryszkiewycz (1991), Teorey (1994), Batini, Ceri and Navathe (1992), and McFadden and Hoffa (1994).A few notations are illustrated below. n Employee 1 Department a) Chen Employee Department b) Teorey n Employee 1 Department c) Elmasri Navathe Employee (0,1) works_for is_worked_for Employee works_for Employee p works_for Employee c has (1,n) Department d) MERISE Employee Department e) IE Department f) Bachman Department g) IDEF1X Department h) Shlaer & Mellor Figure 2. Various notations for ER Diagram representing one employee works for zero or one department and one department has o ne or more employees. 218 Appendix A A Practical Guide to Entity-Relationship ModelingEach diagram in Figure 2 contains two entities employee and department. In diagrams a, b, c, and d, the diamond indicates the relationship between the entities. These diagrams use n-ary modeling. Diagrams e through h are examples of binary modeling. They do not represent the relationship with the diamond shape. Instead, diagrams e, f, and h label the line between the entities with the relationship name. Attributes were not represented in the diagrams for simplicity. The various circles, lines, arrows, and letters on the diagram indicate cardinality and participation constraints.For a more complete treatment of various ER modeling methods, see Song, Evans, and third estate (1995). ER Modeling How does one begin creating an entity relationship diagram? In this paper, we present step-by-step guidelines to build an ERD using n-ary modeling using Elmasri and Navathes notation (see 2. c). In dodge 1, w e summarize a sequence of steps of database design using an ER model. broadside that these steps are iterative. 1. Understand the problem domain. Analyze database requirements. pen a thick specification in English, if not created yet. What do we need to store into the database? What queries and reports do we need to generate? What are grave people, places, physical things, organizations, events and rob concepts in the organization? 2. physique a conceptual schema by creating an ER diagram. (a) Identify entity types. aver a singular noun to each entity type. (b) Identify relationships between (among) entities. Use a meaningful verb for a relationship name. (c) Draw an ERD without attributes. (d) Identify relationship cardinalities. Mapping constraint (11, 1N, NM) Participation constraint (Total, Partial) (e) Assign attributes to entity types and relationship types.Usually attributes come from nouns, adjectives or adverbs. (f) contract identifiers (primary keys) for entity ty pes. Weak entity composite primary key. Regular entity choose/create a whizz attribute primary key. (g) Select the PKs of relationships. If 11, then the PK of either side entity type may be selected. If 1N, then the PK of N-side entity type must be selected. If MN, then a composite PK consisting of PKs of two entity types must be used. If ternary, then a composite PK consisting of the PKs of at least two entity types.The actual PKs selected will vary depending on the cardinality. 3. Design a logical schema. (a) Translate the ERD into a relational schema 219 Appendix A A Practical Guide to Entity-Relationship Modeling If a relationship cardinality is in all likelihood to be changed use s table method. If a relationship cardinality is not probably to be changed use mapped method. If a relationship cardinality is not likely to be changed and unprofitable values of foreign keys are significant use mapped with total/partial method. (b) Check normalization (at least 3NF). (c) Creat e data dictionaries. A schema table One table for each relation created in step (a) Assign a domain type for each attribute. Explain the meaning of attributes, if not intuitive. Note other values such as range, null, PK, FK, indexed, source, possessor (d) Do database prototyping & modify the design if needful. (e) Summarize the design assertion (integrity, security). 4. Verify the design with users. Iterate the steps, if necessary. Table 1. Steps to DB Design using ER Modeling First, it is of the essence(predicate) to study the problem domain at hand. Analyze database requirements.Write a summary separate for the problem domain, considering what data need to be stored and what queries and reports need to be processed. All the information necessary for the identified queries and reports must be included in the summary paragraph. Revise the summary paragraph considering database requirements. Second, from the summary paragraph, find nouns. They are candidates for entity types. To determine whether a noun should be designated as an entity, the hobby decision rules may be applied. ordinance 1 Every entity type should be important in its own right within the problem domain.Rule 2 IF an object type (noun) has only one property to store thus it is an attribute of another entity type ELSE it is an entity type. Rule 3 IF an object type has only one data instance and then do not model as an entity type. Rule 4 IF a relationship needs to have a unique identifier 220 Appendix A A Practical Guide to Entity-Relationship Modeling THEN model it as an entity type. The first three rules are used to evaluate object types or nouns, and the fourth rule is used to evaluate relationships or verbs. Example 1 Address is usually a property of another object type, like customer, vendor, or company.Its existence is less important and not meaningful in its own right within the problem domain. Address should be modeled as an attribute. Example 2 hypothecate we are modeling the customers of a company and we want to include the city where each customer resides. If the name of the city is its only attribute, then, following Rule 2, model city as an attribute not an entity. Similarly, consider the case of modeling employees and their departments. If the only important property of the department is its name, then Rule 2 tells us to model it as an attribute.However, if we need to store additional properties of each department such as projects or total sales, then we should consider modeling it as an entity. Example 3 Consider modeling the activities of a trucking company. Since there is only one instance of the trucking company, then, according to Rule 3, it is not necessary to represent it in our model as an entity. We note that it is not wrong to model this single instance noun as an entity type. We simply do not model it as an entity type at the conceptual level because it does not add any modeling power.We need the fourth rule because one fact can be stated in many different ways in English. In the fourth rule, distinguishing between entities and relationships depends on the function the component plays in the problem domain and how data will be stored about it. Example 4 Consider the three statements customer orders products, customer pays bills, and reviewer reviews papers. Even though orders and pays come to the fore to represent relationships, we model them as entities since each instance would need a unique number for identification in real-world situations.Information would be stored in the database for each order and payment. Each review is not likely to need a unique identification number. Instead, we identify each review activity by a combination of Paper and Reviewer. Thus, by Rule 4, we model reviews as a relationship type. Once entities have been assigned, we proceed to identify relationship types between those entities. Verbs are useful candidates for relationships. The following question is useful for identifying relat ionships What sentences can be constructed of the form Entity Verb Entity? For example, 221Appendix A A Practical Guide to Entity-Relationship Modeling Employee has children (Existence relationship) Professor teaches students (Functional relationship) Customer places order (Event relationship) Note that a relationship is not an action of a flow of data as in data flow diagrams. They are important interactions, between two or more entities, that need to be remembered by the system. In the above examples, we want to remember the facts that who is a child of which employee, which professor teaches which students, and which customer places which order. alike keep in mind that all relationships are bi- oversightal.We should be able to state the relationship in both directions. Expressing the relationships above in the opposite direction yields the following statements Children belong to employee Students are taught by professor Order is placed by customer After an ERD has been built , the following rule can aid in validating the diagram. Rule 5 IF any verb refers to nouns which are not selected as entity types THEN do not model it as a relationship type. If any verb in the ERD fails to follow Rule 5, then consider it again carefully before including it in the diagram.When entities and relationships have been identified, then the cardinality and participation constraints of the relationships can be analyzed. The following rules can help determine the cardinality and participation constraints for a given binary relationship. A B Rule 6 For each A, what is the maximum number of Bs that may be associate to it? Rule 7 IF A can exist without being associated with a B THEN A has partial (optional) participation ELSE A has total (mandatory) participation. 222 Appendix A A Practical Guide to Entity-Relationship Modeling Example 5 Consider the relationship Supplier Supplies Account.For each Supplier, what is the maximum number of Accounts that may be related to it? Lets say that in our problem domain, each Supplier may have many Accounts but each Account may have only one Supplier. By Rule 6, the cardinality constraint for SupplierAccount is 1N or one to many. Figure 1 illustrates the cardinality constraints. Example 6 In determining the participation constraint of Supplier Supplies Account, we follow Rule 7 If Supplier can exist without being associated with Account, THEN Supplier has partial participation, ELSE Supplier has total participation.In our problem domain, Supplier may exist without being associated with Account. Therefore, Supplier has partial participation in the Supply relationship. However, since Account cannot exist without a Supplier Account has total participation in the Supply relationship. Some basic naming conventions have been established to maintain accuracy and consistency in the database and to avoid redundancy. All entity names should be unique. Use singular nouns in the diagram for both entity and attribute names. Use v erbs in the present tense for relationship names. Verbs should be meaningful.For example, avoid verbs like is, has, and do whenever possible. Additionally, well-defined ERDs should satisfy the following basic rules All entities and relationships should be connected. All entity names should be unique. Each entity must have at least one relationship. A relationship cannot be directly connected to another relationship. Every entity must have at least one unique attribute, which serves to identify each instance of that entity. Case Study The following example will illustrate our guidelines for modeling requirements of the problem domain with entity-relationship diagrams.Using the summary paragraph of the problem description below, we will progress through the steps described above. The nouns in the problem description appear in boldface and the verbs are italicized to aid in the following analysis. Summary Paragraph of Problem Description A database specialist wants to design a par t of the database for a small drug store owner as follows The owner wants to keep track of all the providers who interpret anything to the store. For each supplier, the owner assigns a unique supplier number, and wants to keep the 223Appendix A A Practical Guide to Entity-Relationship Modeling company name, target (number, street, city, state, zip), contact persons name, phone number, fax number, and a comment for each supplier. For each supply activity, an account is established to keep track of the date incurred, the total cost of the activity, due date for payment, outstanding balance after some payments, and any special comments related to the account. For each account, the owner may pay at several different times and in different ways (e. g. , cash, check, credit card).For each payment activity, the owner wants to keep the date of payment, amount of payment, method of payment (check check number credit card credit card name, type, and number). Note that one supplier can suppl y many times and one payment can pay for several accounts of the same supplier. Entity Analysis After reading and understanding the problem statement, our first step is to identify entities for the ERD. To do that we examine the nouns in the problem statement. Nouns appear in boldface. We test each noun against our four criteria to determine whether or not it should be included as an entity type.Our first noun is owner. Recall that an entity type has more than one instance and more than one property. Since there is only one instance of owner, we do not model it as an entity type. Similarly, there is only one store, so we need not represent store as an entity type. The attached noun, supplier, can be classified as an entity type. Several properties of supplier are listed in the problem statement. The statement also refers to more than one supplier. Therefore, according to Rules 1, 2, and 3, we model supplier as an entity.For each supplier, the owner wants to store the following prop erties in the database supplier number, company name, contact person, address, phone number, fax number, and comment. Each of these attributes except address has only one property to store so we model them as attributes. Address has its component properties number, city, state, and zip so one might be tempted to model it as an entity type. However, the role of address as a property of supplier supersedes the fact that address has properties of its own. In other words, address itself without supplier is not important in its own right.Therefore, by Rule 1, we model address as an attribute. Account is the next noun. Account has several properties to be stored in the database date incurred, total cost, due date, account balance, and comments and we will store information about numerous accounts. Therefore, we designate account as an entity. Its properties are modeled as attributes of account. Payment is clearly an entity, with multiple instances and various properties. The properties o f payment date of payment, amount of payment, and method of payment, are modeled as its attributes.Cash, check, and credit card appear to be attributes of payment, but actually, they are not attributes themselves, but simply different values for the attribute method of payment. This distinction becomes clearer if we think about 224 Appendix A A Practical Guide to Entity-Relationship Modeling storing data in the database. For each payment, one of the values cash, check, or credit card will be stored in the location containing data about the method of payment. Check number and credit card name, type and number may be modeled as attributes of Payment. Supplier Account Payment Figure 3. Entities to be included in the ERD.Relationship Analysis Our analysis of nouns in the problem statement has produced three entities Supplier, Account, and Payment (Figure 3). Keep these entities in mind as we identify relationships between them. Lets examine the verbs in the problem statement as candidat es for relationships in the diagram. Verbs appear in italics. Of the verbs in the problem statement keep track, assigns, supply, established, and pay, only supply and pay are possible candidates for relationships between the entities account, supplier, and payment. Keep track and keep appear several times in the problem statement.These terms refer, not to a relationship between entities, but generally to storing data in the database. In other words, they are used to describe the problem domain, not an interaction that needs to be remembered by the system. Therefore, we do not model them as relationships. Established, in the statement an account is established, is an activity performed by the owner or the system itself. Similarly, owner assigns a unique supplier number reflects an activity by the owner. These two verbs do not represent relationships between any of our three entities. Thus, we are left(p) with the verbs supply and pay.A supplier performs a supply activity. The result of a supply activity is an account. Therefore, a good candidate for the relationship between supplier and account is supply. Stated in both directions, the relationship is Supplier supplies account and account is supplied by supplier. Rule 4 states that if a relationship needs to have a unique identifier, then model it as an entity. Each supply activity is unique, so we may be tempted to model supply as an entity. However, the data for each activity is stored using the entity account, so it is not necessary to create another entity which stores the same information.Each payment credits an account so pay is the relationship between payment and account. Expressing the relationship pay in both directions, we can say account is paid by payment and payment pays account. 225 Appendix A A Practical Guide to Entity-Relationship Modeling Now we can draw the basic ERD (Figure 4). We include the entities Supplier, Account, and Payment, and the relationships Supply and Pay. Attributes may be a dded to the diagram at this point or omitted to avoid clutter. Supplier Supply Account Pay Payment Figure 4. ERD without attributes and constraintsAnalysis of Cardinality and Participation Constraints In order to identify the cardinality and participation constraints of each relationship in the ERD, we follow Rules 6 and 7 looking at the relationship first from the point of view of one entity and then from the other entity. In our ERD above, to determine the cardinality constraint of the relationship Supply, we begin by asking, For each Supplier, what is the maximum number of Accounts that may be created? From the problem statement, we know that one supplier can supply many times and an account is established for each supply activity.Viewing the relationship in the other direction, we ask, What is the maximum number of Suppliers for which each Account may contain information? From the problem statement we can assume that each account carries information for a single supplier, sinc e accounts are established for individual supply activities. Thus, for each supplier, there may be many accounts and each account may have only one supplier. The relationship Supplier Supplies Account is a one-to-many relationship. The diagram is attach with a 1 on the side of the relationship Supply nearer to Supplier, and an N (for many) on the side nearer to Account (see Figure 5).To identify the cardinality of the relationship Payment Pays Account, we look at the relationship from both directions. We ask, What is the maximum number of Payments we can accept for each Account? The answer is clearly stated in the problem statement For each account, the owner may pay at several different times and in different ways. From the opposite direction, For each Payment, what is the maximum number of Accounts for which it may pay? Again, we find the answer in the problem statement One payment can pay for several accounts of the same supplier. In sum, each account 226Appendix A A Practical Guide to Entity-Relationship Modeling may receive many payments and each payment may pay for many accounts. Therefore, the relationship Payment Pays Account is many-to-many. This time, we mark our diagram with an M on one side of the relationship Pay and an N on the other side. (Note that the use of M or N is completely arbitrary. ) We go through a similar process to determine the participation constraint of each relationship, looking at the relationship from each direction. For the Supply relationship we ask, Can a Supplier exist without generating Accounts? In the other direction, Can an Account exist without having Suppliers supply merchandise? The answers to these questions are not explicit in the problem statement. In a real world situation, the database designers would clarify questions like these with the owner. In this case, we will make assumptions from what we understand about the problem domain. Suppliers are generally fairly stable entities. A company maintains relati onships with several regular suppliers regardless of whether they have outstanding accounts. On the other hand, an account is only created when a supplier supplies merchandise.Since suppliers can exist without having current accounts, Supplier has partial participation in the Supply relationship. Accounts, however, depend on suppliers for their existence. Thus, Account has total participation in the Supply relationship. To determine the participation of the entities Payment and Account in the Pay relationship, we ask, Can a Payment exist without salaried for an Account ? and Can an Account exist without receiving Payments against it? A payment which pays for nothing is absurd. It cannot exist without an account. An account, however, may exist without receiving payments against it.Therefore, Payment has total participation and Account has partial participation in the relationship Pay. In representing the cardinality and participation constraints described above in our ERD, we will employ Elmasri and Navathes (1994) notation. If an entity has partial participation in the relationship, then a single line is drawn on the line between that entity and the relationship. A double line indicates total participation. The cardinality constraint is represented by Look crosswise convention, while participation constraint is represented by Look Here convention.Figure 5 illustrates the final ERD with cardinality and participation constraints. 227 Appendix A A Practical Guide to Entity-Relationship Modeling 1 Supplier Supply N Account M Pay N Payment Figure 5. ERD with cardinality and participation constraints. Errors in Modeling A common error that novice designers make is failing to recognize the boundaries of a problem domain. They fail to make a distinction between elements that comprise the national of the database and elements that are outside the scope of the database. For example, in the problem statement bove, a novice might want to model the verbs keep track or assigns or established as relationships (see Figure 6(a)). These verbs refer to implementing the database and not to its content. Keep track refers to storing data in the database, established refers to adding an instance of an entity to the database, and assigns refers to giving a value to an attribute of an entity. In deciding which elements to model, it is valuable to keep in mind the real world situation. Novice designers also frequently confuse entities with their attributes or properties, as in Figure 6(b).Occasionally, if properties are complex and play a significant role in the problem domain, then they may be modeled as entities. more(prenominal) often, however, properties of an entity should be modeled as attributes. In our problem statement, a novice user may decide to model address, a property of the entity supplier, as an entity. Modeling Address follows Rules 2 and 3 about identifying entities it has more than one property and it has more than one occurrence. However, address does not follow Rule1 in that it is not important in its own right.The role of address in the database is more accurate as an attribute of supplier, than as an entity with its own relationships. Other errors are modeling substantiating or redundant relationships and inappropriately modeling object types as relationships sooner than as entities. Given our problem statement, one may be tempted to model the relationship Payment Pays Supplier as in Figure 6(c) or Supplier Pays Account as in Figure 6(d) rather than Payment Pays Account. Figure 6(c) represents the association between payment and account indirectly. This indirect relationship can only exist after we have all the direct 228Appendix A A Practical Guide to Entity-Relationship Modeling relationships as in Figure 5. In this case, the indirect relationship simply becomes redundant. Without the direct relationships, the indirect relationship cannot be added, because it cannot explain how a particular payment is distribu ted to multiple accounts. Figure 6(d) represents the relationship Pay rather than the entity Payment. In either of these two cases, it is difficult to explicitly represent the fact that one payment can pay for several accounts of the same supplier. We can only tell implicitly by reading the check number for the various payments.If the payment is made in cash, there is no way to identify that it paid for more than one account. If the representation used in Figure 6(d) is used, then the attributes related to payments date of payment, amount of payment, and method of payment, are now attributes of the relationship Pay. This representation can add unnecessary complexity to the model. Ordinarily, a relationship is uniquely represented by the identifiers of one or more of the entities which participate in it. If the relationship includes a time-dependent attribute like date of payment, then that attribute must also be included in the primary key for that relationship.Additionally, instanc es of date of payment and amount of payment will require redundant representation because they will have to be included for each account covered by a payment. Finally, in business practice, each payment activity usually requires a unique identifier. Therefore, following Rule 4, it is more appropriate to model payment as an entity than as a relationship. As an entity, the representation is more straightforward and less likely to include redundant or inaccurate information. 229 Appendix A A Practical Guide to Entity-Relationship Modeling a) Selection of wrong verb as relationship possessor (b) Attribute as entity Supplier Located_at Address Keeps_track Payment (c) Indirect relationship Payment Pays Supplier Establishes Account (d) Payment as relationship instead of entity Establishes Supplier Pays Account Figure 6. Errors in ERD Modeling. Limitations of Guidelines and Rules Two limitations of our guidelines are that they dont account for incomplete requirements analysis or for ambigu ity in the problem description. If the problem description is incomplete, then the resulting analysis based on this approach will also be incomplete.We assume that the analysis is complete. If the problem specification is modified, the analysis and resulting ERD should be modified as well. In English, one concept can be represented in many different ways. For example, we can say that customer orders products or customer places an order to buy products. Order is used 230 Appendix A A Practical Guide to Entity-Relationship Modeling as a verb in the first sentence and as a noun in the second. We minimize this problem by adopting Rule 4, which states that if a verb needs to have a unique identifier, we model it as an entity type rather than a relationship type.Conclusion We have discussed a set of decision rules which are useful in building ERDs and have illustrated the application of these rules using a single example. ERD constructs discussed here include Entities, Relationships, Attr ibutes, Cardinality constraints and Participation constraints. To simplify our discussion, we didnt include other constructs such as Weak Entity, Ternary Relationship, and Generalization/ Specialization. Our rules are heuristics which we have found useful for most cases to build ERDs in the early stages of analysis.However, these rules may need some refinement in some problem domains and the rules should be adapted to the problem domain under consideration. References Ahrens, J. and Song, I. Y. (1991). EER Data Modeling Aids for Novice Database Designers. Proceedings of the 2nd International Conferences of the Information Resources Management, Memphis, TN, May 19-22, 1991, pp. 99-114. Bachman (1992). Bachman Analyst, Bachman Information Systems Incorporated. Batini, C. , Ceri, S. , and Navathe, S. (1992). Conceptual Database Design An EntityRelationship Approach, Redwood City, CA Benjamin/Cummings Publishing Company, Inc.Bruce, T. (1992). Designing Quality Databases with IDEF1X Info rmation Models. New York, New York Dorset House Publishing. Chen, P. P. (1976). The Entity Relationship Model Toward a Unified View of Data. ACM Transactions on Database Systems, 1 1, pp. 9-36. 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