Database: Entity-relationship Model

Appendix A A pragmatic feed to Entity-Relationship simulation A matter-of-fact Guide to Entity-Relationship manikin Il-Yeol vocal music and Kristin Froehlich College of Information light and Technology Drexel University Philadelphia, PA 19104 Abstract The Entity-Relationship (ER) ideal and its accomp both(prenominal)(prenominal)ing ER plots ar widely utilise for selective informationbase normal and Systems analysis. M some(prenominal) books and articles just provide a exposition of to separately integrity poser comp integritynt and give examples of pre-built ER diagrams.Beginners in information personateing prep be a great deal of difficulty learning how to uprise a presumption chore, what questions to ask in articulate to manakin a pretending, what retrieves to drug abuse while constructing an ER diagram, and why single diagram is disclose than an other. In this paper, in that respectfore, we present step-by-step guidelines, a rotary of purp ose rules proven to be usable in building ER diagrams, and a eccentric person study chore with a preferred sacrifice as well up as a set of incorrect diagrams for the conundrum.Database caution System and DataThe guidelines and decision rules give way been successfully used in our lineage Database Management Systems course for the last eight-spot years. The oddball study give provide readers with a detailed shape up to the frameworking process and a deeper downstairsstanding of entropy modeling. Introduction Entity blood diagrams (ERD) atomic number 18 widely used in database design and systems abstract to dissemble systems or bother earths. The ERD was introduced by Chen (1976) in archaean 1976. Teorey, Yang, and Fry (1986) present an extended ER model for comparative database design.The ERD models a given problem in footing of its essential elements and the interactions amongst those elements in a problem domain. The ERD backside cause as the basis for databases, which stack away data ab bring out the problem domain, and which use, manipulate, and restrain that data. Experts in systems analysis and database design be adept at marking substance abuser requirements and indeed translating them into corresponding comp unitynts of the model. umpteen books and articles just provide a definition of some(prenominal)ly modeling parting and give examples of pre-built ER diagrams. Beginners in data modeling ware a great eal of difficulty learning how to approach a given problem, what questions to ask in point to build a model, what rules to use while constructing an ER diagram, and why champion diagram is better than a nonher. 213 Appendix A A matter-of-fact Guide to Entity-Relationship mannequin Ahrens and Song (1991) present a set of requirements elicitation template sentences, social structured incline template sentences, and almost decision rules for database modeling. This paper presents a set of heuristic rule rule s which improve upon those presented by Ahrens and Song (1991), together with a detailed case study analysis.We entangle 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 reaction as well as a set of incorrect diagrams for the problem. These guidelines and decision rules fool been successfully used in our beginning Database Management Systems course for the last eight years. The case study willing provide readers with a detailed approach to the modeling process and a deeper understanding of data modeling. The Entity-Relationship Diagram The entity kindred diagram is a graphical agency of a conceptual structure of a problem domain cosmos sculptured.The ERD assists the database designer in identifying the data and the rules that will be represented and used in a database. The ERD is an implementation-independent internal representation of a problem domain and it facilitates communication su rrounded by the end-user and the analyst. ERDs hatful be easily converted into a logical database structure that cease be readily implemented in a particular commercial database concern system. The basic comp mavennts of the ERD be entities, properties of entities called attri exclusivelyes, and family familys amid entities. Entities Entities be PRIMARY THINGS of a problem domain more than than or less which users necessitate to record data.Ross (1988) provides a list of campaigner entity typecasts which could be include in the model. (1) People humans who carry out some function Employees, Students, nodes (2) Places sites or locations Cities, Offices, Routes (3) Things tangible physical objects Equipment, Products, Buildings (4) Organizations Teams, providers, discussion sections (5) Events things that happen to some other entity at a given look and time or as in an ordered sequence Employee promotions, Project phases, rate feedments (6) Concepts nonphysical i deas used to keep pursue of business or other activities Projects, visors, Complaints 214 goAppendix A A Practical Guide to Entity-Relationship pattern These candi see entity types need to be evaluated against a particular domain be modeled. Some decision rules are discussed in a later section of this paper. Attributes Attributes are properties of entities or family kins. Entities have two types of properties identifying propertys and descriptive places. Identifying attributes whimsically determine several(prenominal)ly instance of an entity type. They are called entity identifiers or keys. For example, the attribute social security number would uniquely identify each member or instance of the entity type student.Descriptive attributes of student ability include year, advisor, and grade point average. Each instance of an entity has a pry for each attribute. Values for grade point average qualification include 2. 5, 3. 45, and 4. 0. Values for year might include 1991, 1 992, 1993, and 1994. Only attributes that are meaning(prenominal) in terms of modeling the problem under consideration are included in the ERD. For example, we would non include eye color in a student database. Relationships Relationships are other basic comp whizznt of the ERD. A race is an tie between or among things or entities.A family describes a meaningful interaction that needfully to be remembered by the system. The degree of a alliance steers how more a nonher(prenominal) entities are participating in the relationship. A single relationship describes an friendship of an entity with itself. A binary relationship, the most common instance, describes an association between two entities. A triplex (or n-ary ) relationship is an association between triad or more entities. The ER methods that intromit simply single and binary relationships are called binary models, while ER methods that allow any type of relationship are called n-ary models.For more thorough tre atment of ternary relationships, go through J nonpareils and Song (1995, 1996) and Song and Jones (1995). Cardinality and community Constraints Cardinality is a constraint on the relationship between two entities. Specifically, the waggleinality constraint expresses the maximal number 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 attainable cardinalities oneto-one (11), one-to- many another(prenominal) (1N), or many-to-many (MN). unmatchable-to-one cardinality registers that, for entities guest and grudge, one client can have at most one describe and one account cannot be testify by more than one customer. wholeness-to-many cardinality ranks 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 whitethorn b e owned by many customers. 215 Appendix A A Practical Guide to Entity-Relationship Modeling involvement is too a relationship constraint.Participation expresses the minimum number of entities that can be associated with another entity via a relationship. There are two values for employment total or mandatory appointment and uncomplete or nonmandatory society. If either instance of an entity must participate in a given relationship consequently that entity has total confederacy in the relationship. But if every instance need not participate in a given relationship accordingly the elaborateness of that entity in the relationship is overtone. give the relationship employee deeds for epartment, an employee has incomplete participation in that relationship if he or she need not work for a part. An employee has total participation in the relationship if he or she must work for at to the lowest degree one department. Similarly, a department has partial participation in th e relationship if it can personify 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 domain being modeled. These constraints represent the way one entity type is associated with another entity type.These constraints are as well integrity constraints because they help to ensure the true statement of the database. These constraints limit the ship canal in which data from distinct parts of the database can be associated. For example, lets say the cardinality of the relationship between Customer and grievance is one-to-one, as in write in code 1(a) below. If customer C1 is associated with account A3, thusly 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 accou nt. One account cannot be owned by more than one customer. Customer 1 CA 1 account ER Diagram C1 C2 C3 A1 A2 A3 particular 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 C2 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 whitethorn be owned by many customers. Customer n C1 C2 C3 C4 C5 CA m A1 A2 A3 A4 A5 Account ER Diagram Occurrence Diagram work out 1.CARDINALITY The expression of the maximum 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 committed to the rect angle 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 ball fields between entities. The notation of the ERD, however, varies according to the modeling approach used. Binary 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 McF hang onen and Hoffa (1994).A few notations are illustrated below. n Employee 1 part 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 Employ ee c has (1,n) Department d) MERISE Employee Department e) IE Department f) Bachman Department g) IDEF1X Department h) Shlaer & Mellor skeletal system 2. Various notations for ER Diagram representing one employee works for zero or one department and one department has one 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 me thods, see Song, Evans, and Park (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 development n-ary modeling using Elmasri and Navathes notation (see 2. c). In hold over 1, we summarize a sequence of steps of database design using an ER model. noe that these steps are iterative. 1. run across the problem domain. Analyze database requirements. Write a compact specification in English, if not created yet. What do we need to enclose into the database? What queries and reports do we need to engender? What are Copernican people, places, physical things, organizations, events and abstract concepts in the organization? 2. inclination a conceptual schema by creating an ER diagram. (a) Identify entity types. invest a singular noun to each entity type. (b) Identify relationships between (among) entities. physical exertion a meaningful verb for a relationship name. (c) Draw an ERD witho ut attributes. (d) Identify relationship cardinalities. affair 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) portion out identifiers (primary keys) for entity types. Weak entity composite primary key. stiff entity choose/create a single 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 veer depending on the cardinality. 3. origination 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 likely to be changed us e s slacken method. If a relationship cardinality is not likely to be changed use mapped method. If a relationship cardinality is not likely to be changed and null values of foreign keys are material use mapped with total/partial method. (b) Check normalization (at least 3NF). (c) Create 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, proprietor (d) Do database prototyping & modify the design if necessary. (e) Summarize the design assertion (integrity, security). 4. Verify the design with users. Iterate the steps, if necessary. Table 1. Steps to DB Design employ ER Modeling First, it is essential to study the problem domain at hand. Analyze database requirements.Write a summary paragraph for the problem domain, considering what data need to be stored and what queries and reports need to be processed. each 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, keep nouns. They are aspects for entity types. To determine whether a noun should be fixd as an entity, the succeeding(a) decision rules may be applied. Rule 1 Every entity type should be important in its own right within the problem domain.Rule 2 IF an object type (noun) has whole one property to store whence it is an attribute of another entity type ELSE it is an entity type. Rule 3 IF an object type has lonesome(prenominal) one data instance 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 introductory three rules are used to evaluate object types or nouns, and the fourth rule is used to evaluate rela tionships or verbs. simulation 1 Address is commonly a property of another object type, like customer, vendor, or keep company.Its institution is less important and not meaningful in its own right within the problem domain. Address should be modeled as an attribute. Example 2 Suppose we are modeling the customers of a company and we penury to include the city where each customer resides. If the name of the city is its only attribute, then, make uping 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 tackitional 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 Rul e 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 point 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 closely it. Example 4 Consider the three statements customer orders products, customer hires bills, and lector reviews papers. Even though orders and pays bulge 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 honorarium. Each review is not likely to need a unique identification number. Instead, we identify each r eview bodily process by a combination of Paper and lecturer. 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 relationships 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 extend 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 higher up examples, we want to remember the facts that who is a child of which employee, which prof teaches which students, and which customer places which order. Also keep in mind that all relationships are bi-directional.We should be able to state the relationship in both directions. Expressing the relationships in a higher place 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 related to it? Rule 7 IF A can make up wi thout 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 be 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 give relationship. However, since Account cannot exist without a Supplier Account has total participation in the tack relationship. Some basic naming conventions have been realised 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 verbs 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-relation ship diagrams.Using the summary paragraph of the problem description below, we will progress through the steps set forth above. The nouns in the problem description bulge out in boldface and the verbs are italicized to aid in the following analysis. Summary Paragraph of Problem interpretation A database specialist wants to design a part of the database for a low-down drug store owner as follows The owner wants to keep track of all the suppliers who communicate 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, point of reference (number, street, city, state, zip), contact persons name, phone number, fax number, and a comment for each supplier. For each proviso activity, an account is established to keep track of the date incurred, the total cost of the activity, payable date for stipend, outstanding balance after(prenominal) some payment s, 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, assurance card).For each payment activity, the owner wants to keep the date of payment, pith of payment, method of payment (check check number credit card credit card name, type, and number). Note that one supplier can supply many times and one payment can pay for several accounts of the like supplier. Entity Analysis After culture and understanding the problem statement, our startle step is to identify entities for the ERD. To do that we evidence 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 i s only one store, so we need not represent store as an entity type. The adjoining 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 properties 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 fictional character 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 attr ibute. 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. compensation is clear an entity, with multiple instances and various properties. The properties of 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 cr edit card name, type and number may be modeled as attributes of correctment. Supplier Account wages 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 candidates 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 in general 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 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 paym ent 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 force the basic ERD (Figure 4). We include the entities Supplier, Account, and Payment, and the relationships ply and Pay. Attributes may be added 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 expression 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 numbe r of Accounts that may be created? From the problem statement, we bed that one supplier can supply many times and an account is established for each supply activity. forecasting 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 dupe that each account carries information for a single supplier, since 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 marked 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 ea ch 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 consume 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, tone at the relationship from each direction. For the Supply relationship we ask, Can a Supplier exist without generating Accounts? In the ot her 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 relationships with several regular suppliers heedless 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 paying for an Account ? a nd 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 Across 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 wit h cardinality and participation constraints. Errors in Modeling A common error that dilettante designers make is failing to recognize the boundaries of a problem domain. They fail to make a distinction between elements that comprise the content of the database and elements that are away(p) 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 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 indirect or tautological relationships and inappropriately modeling object types as relationships rather 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 p ayment 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 distributed 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 attribut es 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, instances 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 commonly 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 faulty information. 229 Appendix A A Practical Guide to Entity-Relationship Modeling a) pickax of wrong verb as relationship Owner (b) Attr ibute 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 ambiguity 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 mini mize 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, Attributes, Cardinality constraints and Participation constraints. To simplify our discussion, we didnt include other constructs such as Weak Entity, third 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. 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