Requirements Analysis and Conceptual Data Modeling
Toby Teorey , ... H.V. Jagadish , in Database Modeling and Design (Fifth Edition), 2011
Ternary Relationships
Define ternary relationships carefully. We define a ternary relationship among three entities only when the concept cannot be represented by several binary relationships among those entities. For example, let us assume there is some association among entities Technician, Project, and Notebook. If each technician can be working on any of several projects and using the same notebooks on each project, then three many-to-many binary relationships can be defined (see Figure 4.2(a) for the ER model and Figure 4.2(c) for UML). If, however, each technician is constrained to use exactly one notebook for each project and that notebook belongs to only one technician, then a one-to-one-to-one ternary relationship should be defined (see Figure 4.2(b) for the ER model and Figure 4.2(d) for UML). The approach to take in ER modeling is to first attempt to express the associations in terms of binary relationships; if this is impossible because of the constraints of the associations, try to express them in terms of a ternary relationship.
Figure 4.2. Comparison of binary and ternary relationships: (a) binary relationships, (b) different meaning using a ternary relationship, (c) binary associations, and (d) different meaning using a ternary association.
The meaning of connectivity for ternary relationships is important. Figure 4.2(b) shows that for a given pair of instances of Technician and Project, there is only one corresponding instance of Notebook; for a given pair of instances of Technician and Notebook, there is only one corresponding instance of Project; and for a given pair of instances of Project and Notebook, there is only one instance of Technician. In general, we know by our definition of ternary relationships that if a relationship among three entities can only be expressed by a functional dependency involving the keys of all three entities, then it cannot be expressed using only binary relationships, which only apply to associations between two entities. Object-oriented design provides arguably a better way to model this situation (Muller, 1999).
Toby Teorey , ... H.V. Jagadish , in Database Modeling and Design (Fifth Edition), 2011
Degree of a Relationship
The degree of a relationship is the number of entities associated in the relationship. Binary and ternary relationships are special cases where the degree is 2 and 3, respectively. An n-ary relationship is the general form for any degree n. The notation for degree is illustrated in Figure 2.3. The binary relationship, an association between two entities, is by far the most common type in the natural world. In fact, many modeling systems use only this type. In Figure 2.3 we see many examples of the association of two entities in different ways: Department and Division, Department and Employee, Employee and Project, and so on. A binary recursive relationship (e.g., "manages" in Figure 2.3) relates a particular Employee to another Employee by management. It is called recursive because the entity relates only to another instance of its own type. The binary recursive relationship construct is a diamond with both connections to the same entity.
A ternary relationship is an association among three entities. This type of relationship is required when binary relationships are not sufficient to accurately describe the semantics of the association. The ternary relationship construct is a single diamond connected to three entities as shown in Figure 2.3. Sometimes a relationship is mistakenly modeled as ternary when it could be decomposed into two or three equivalent binary relationships. When this occurs, the ternary relationship should be eliminated to achieve both simplicity and semantic purity. Ternary relationships are discussed in greater detail in the "Ternary Relationships" section below and in Chapter 5.
An entity may be involved in any number of relationships, and each relationship may be of any degree. Furthermore, two entities may have any number of binary relationships between them, and so on for any n entities (see n-ary relationships defined in the "General n-ary Relationships" section below).
Toby Teorey , ... H.V. Jagadish , in Database Modeling and Design (Fifth Edition), 2011
Ternary and n-ary Relationships
An n-ary relationship has (n + 1) possible variations of connectivity: all n sides with connectivity "one"; (n − 1) sides with connectivity "one" and one side with connectivity "many"; (n − 2) sides with connectivity "one" and two sides with "many"; and so on until all sides are "many."
The four possible varieties of a ternary relationship are shown in Figure 5.5 for the ER model and Figure 5.6 for UML. All variations are transformed by creating an SQL table containing the primary keys of all entities; however, in each case the meaning of the keys is different. When all three relationships are "one" (Figure 5.5a), the resulting SQL table consists of three possible distinct keys. This represents the fact that there are three functional dependencies (FDs) that are needed to describe this relationship. The optionality constraint is not used here because all n entities must participate in every instance of the relationship to satisfy the FD constraints. (See Chapter 6 for more discussion of functional dependencies.)
In general, the number of entities with connectivity "one" determines the lower bound on the number of FDs. Thus, in Figure 5.5(b), which is one-to-one-to-many, there are two FDs; in Figure 5.5(c), which is one-to-many-to-many, there is only one FD. When all relationships are "many" (Figure 5.5d), the relationship table is all one composite key unless the relationship has its own attributes. In that case, the key is the composite of all three keys from the three associated entities.
Foreign key constraints on delete and update for ternary relationships transformed to SQL tables must always be cascade because each entry in the SQL table depends on the current value of, or existence of, the referenced primary key.
The multiple-context relational approach generated by the empirical research
Susie Andretta , in Ways of Experiencing Information Literacy, 2012
The multiple-context outcome space of information literacy
According to Edwards (2006: 62) the outcome space presents a picture of the relationship between the categories of description. Marton and Booth argue that this relationship is hierarchical because it demonstrates the progressive complexity 'in which the different ways of experiencing the phenomenon in question can be defined as subsets of the component parts and relationships within more inclusive or complex ways of seeing the phenomenon' (1997: 125). In this study the hierarchy of the outcome space generated by the final stage of the research consists of an incremental progression of the experience of information literacy in personal, information provision, academic and information education contexts. This hierarchy, shown in Table 4.4, operates in the following ways. First, the hierarchical order is illustrated by the type of relationship that characterises the categories of description, where complexity increases from binary to ternary (horizontal headings). Second, the hierarchy operates in terms of the nature of the information goal, where complexity increases from everyday information goals to right or wrong answers to the open-ended question (left-hand side headings). And third, the hierarchy is shown by the progression from passive to active information literacy (right-hand side headings).
Table 4.4. The multiple-context outcome space of information literacy
Binary relationship
Ternary relationship
Open-ended question
Information Education context – Information Literacy as Education
Active IL (fosters independent learning in users)
Academic context – Information Literacy as Lifelong Learning
Right or wrong answer
Information Provision context – Information Literacy as Provision
Passive IL (satisfies the information needs of the users)
Every day information goals
Personal context – Information Literacy as Functional Literacy
The binary relationship characterises Functional Literacy and Lifelong Learning, while the two professional categories of information literacy, Provision and Education, are characterised by the ternary relationship. In the case of the binary relationship the hierarchical order is determined by the type of information goal. For example, when information literacy is seen as Functional Literacy, the students' information goal is based on the need to find solutions to everyday problems. Information literacy as Lifelong Learning describes the dynamics between the students and the open-ended (and therefore complex) information goals situated in an academic context. It is the difference between the open-ended nature of the information goal in an academic scenario and the type of information goal associated with the everyday world of Functional Literacy that determines variation in the way information literacy is interpreted, establishing the hierarchical order between these two categories.
When the ternary relationship is examined then the passive and the active approaches to information literacy are the criteria determining the variation in the positioning of the information professional, the user and the information, and the hierarchical order between the categories of Provision and Education. The focal point in Provision is the information professional who practices information literacy to mediate the interaction between the user and the information, while the user plays a peripheral role of recipient of information (characterised by a right or wrong answer) found by the information professional. By contrast, in Education the user is positioned at the centre of the ternary relationship engaging with both information and educator directly, and therefore experiencing information literacy as the foundation of independent learning, or the ability to deal with open-ended questions. The implications of the ternary hierarchy are that in the Provision category information literacy is experienced by the user as a passive recipient and by the information professional as an active provision of information to satisfy the users' needs. Whereas in the Education category information literacy is experienced by the active learner (satisfying her own information needs) while the educator facilitates the learners' development or enhancement of their independent learning attitudes.
When the categories of description are analysed together, the following hierarchical order applies. Functional Literacy remains the first category in the hierarchy because of its association with everyday information goals. Provision becomes the second category in the hierarchy because it illustrates an increased complexity in the way information literacy is experienced through the expansion of the relationship from binary (person-information) to ternary (users, information professional and information). In this case, information literacy is employed by the information professional, although variation of this experience is generated by two types of users involved in the relationship: knowledge-expert users who are specific in their enquiries to the provider, and users who are unsure of the information they want and who are vague in the way they articulate their enquiries. As a result, the way the provider uses information literacy varies from finding 'quality' information that satisfies the short-term and focused queries from private users to active elicitation of the users information needs in public and educational sectors. Lifelong Learning is third in the hierarchy because it reflects the relationship between the students and open-ended, complex information goals, like reviewing a body of literature. Education remains the fourth and highest category because the ternary relationship reflects the user-centred interaction with open-ended information goals. Here variation occurs at two levels as the students play two different roles in this ternary relationship. In their professional role, as educator, they encourage learners to find information independently, although this role is inspired by the students' awareness of independent learning and is not fully integrated in their professional awareness or practice. The students also play a learner's role in this relationship as students of AIR and this experience raises their awareness of information literacy education from a learner's perspective.
Toby Teorey , ... H.V. Jagadish , in Database Modeling and Design (Fifth Edition), 2011
Publisher Summary
The Unified Modeling Language (UML) is a graphical language for communicating design specifications for software, currently very popular for communicating design specifications for software and, in particular, for logical database designs via class diagrams. The object-oriented software development community created UML to meet the special needs of describing object-oriented software design. UML has grown into a standard for the design of digital systems in general. The similarity between UML and the entity–relationship (ER) model is shown through some common examples in this chapter, including ternary relationships and generalization. UML activity diagrams are used to specify the activities and flow of control in processes. There are a number of different types of UML diagrams serving various purposes. The class and the activity diagram types are particularly useful for discussing database design issues. UML class diagrams capture the structural aspects found in database schemas. UML activity diagrams facilitate discussion on the dynamic processes involved in database design. This chapter is an overview of the syntax and semantics of the UML class and activity diagram constructs used in this book. These same concepts are useful for planning, documenting, discussing and implementing databases. UML activity diagrams are similar in purpose to flow charts. Processes are partitioned into constituent activities along with control flow specifications. This chapter is organized into three main sections. The first section presents class diagram notation, along with examples. The next section covers activity diagram notation, along with illustrative examples. Finally, the last section concludes with a few tips for UML usage.
Salvatore T. March , in Encyclopedia of Information Systems, 2003
II.B.1. Relationship Degree
A relationship associating instances of the same entity, e.g., prerequisite is termed a unary or recursive relationship. It is said to have a degree of 1. A relationship associating instances of two different entities, e.g., reporting is termed a binary relationship (degree 2). A relationship associating instances of three entities, e.g., sale is termed a ternary relationship (degree 3). Generally a relationship associating instances of N entities is termed an N-ary relationship (degree N). The original ER model supports N-ary relationships. The binary relationship models restrict relationships to at most binary. The implications of this restriction are discussed below.
It is often important to distinguish the "roles" played by the entities in a relationship, particularly when a relationship associates instances of the same entity or when it is not clear from the entities themselves. In the relationship prerequisite, for example, it is crucial to distinguish which instance of Course plays the role "has-prerequisite" and which plays the role "is-prerequisite-for." Specifying that the courses Computer Science 101 and Mathematics 220 participate in the relationship named "prerequisite" is not very useful until the roles are specified. Typically this specification utilizes one role or the other to form a sentence: "Computer Science 101 has-prerequisite Mathematics 220" or "Mathematics 220 is-prerequisite-for Computer Science 101." In the relationship reporting, the roles of Employee and Department are clear, Employee instances "report-to" Department instances or Department instances "are the reporting units for" Employee instances.
Frederick N. Springsteel , in Encyclopedia of Information Systems, 2003
III.B. Links in the Network Become "sets" in the DDL
To avoid confusion between the DBTG name for a link, set, and ordinary sets, we shall refer to links as DBTG-sets. Consider again the two links O.SUPPLIER and O.ITEM among the record-types SUPPLIER, ITEM, and OFFER (Figure 6) of the previous section. These links derived from the ternary relationshipSUPPLIES described earlier. The "owner" record of each link is the "one" object, the actual record at the arrow's head in a link occurrence, and the "members" are the "many" records on the other (origin) end of the link's arrow. For example, as the supplier "Best Supplies" is linked to the several prices that it offers for items, the linked list of owner and members (prices) is considered one DBTG-set: a set occurrence of the DBTG-set O.SUPPLIER. (Conventionally, the name of a set may include its owner's name.) The items that "Best" supplies—say brushes, rotors and combs—may have various prices linked to each item, depending on what price the other suppliers offer them for. But, in the DBTG-set O.ITEM, the owner record of the rotor that Best supplies has a unique (member record) price that is also a member in the DBTG-set O.SUPPLIER and is thus linked to owner-record "Best." It is precisely the intersection of the DBTG-sets at common price member-records, like "$5.00," that actualizes in the DBTG DDL the ternary association SUPPLIES. This actualization makes it possible to "navigate" from the owner of one set, "Best Supplies," to the common member price ($5.00) and thence to this member's other owner, rotor, in the other DBTG-set. Note that the set occurrence diagram of Fig. 7 contains six price records, each involved in exactly two set occurrences. (There are also six set occurrences implied by Figure 7, one for each owner record of the two DBTG-Sets: O.ITEM and O.SUPPLIER.)
Figure 7. The set occurrences for the two SUPPLIES links.
The above two sets can be described in DBTG DDL briefly, without going into all of its low-level technical details, as follows:
To complete the DDL for Figure 7, we need to declare two more record-types, EMP and DEPT, and three DBTG-sets: WORKS_IN, MANAGES and USED_BY:
V. Kantabutra , in Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology, 2015
2 Introducing ILE for Health Care Applications
The best way to think of ILE is that it is a direct, straightforward implementation of the E/R model. There are differences and extensions, but we can deal with those as they come up.
As can be concluded from the previous discussion, the relational model favors relatively simple data models, even when these models are not necessarily as realistic as one would like. As an example, consider a relational model from a database for JMTZ Bee Healthcare, Inc., of a relationship between a provider (a doctor in this case) and a patient, shown in Figure 14.1 (Jin, 2000).
Figure 14.1. A partial E/R diagram showing the provider-patient relationship in a relational database for JMTZ Healthcare, Inc.
Suppose that we want to model the fact that a relationship between a provider and a patient comprises a set of visits. There are database models for the patient-provider relationship where the two people are related by a "visit" relationship. In such a representation, each visit is a separate relationship, and there is nothing that really binds all the visits of one patient to the same provider together.
In ILE, we can easily model both individual visits and the longer-term relationship between a provider and a patient. The most natural way to do this is shown in Figure 14.2.
Figure 14.2. A possible provider-patient relationship in ILE.
This can be easily implemented in ILE as a ternary relationship, where the roles are patient, provider, and visits. The third role, visits, is actually a set or an array. In relational databases, arrays are usually not permitted. For example, MySQL does not permit array data types. Workarounds are necessary; for example, see MySQL 5.7 reference manual, section 11.1 (n.d.). Oracle, which has some features that are beyond those of plain Relational databases, does have an array data type called ARRAY, and a variant of that data type called VARRAY (see the definition of ARRAY, in the Oracle database system, n.d.), but the elements don't appear to be full-fledged entities that can be conveniently linked in relationships as individuals or first-class citizens of the database.
As another example to use in comparing the various kinds of databases, we can look at prescriptions. In JMTZ's relational database, a prescription is an entity with two binary relationships, as shown in Figure 14.3.
Figure 14.3. Representing the Prescription relationship for JMTZ Healthcare, in an E/R diagram meant for implementation as a relational database
One of these relationships is with an invoice, and the other with one or more medicines. An invoice may have 0, 1, or more prescriptions.
The relational data model used by JMTZ allows for relationships with arbitrary arity. However, many designers of relational databases favor binary relationships because in a binary relationship, entities can be linked directly, without an extra table representing the relationship, and also because joins can be expensive, especially joins of more than two tables. Even query optimization can take considerable time. If this situation were to be modeled using a graph database or a pure OODB, then the type of relationships used would most likely be binary because only binary relationships are natively supported.
ILE, as opposed to these other database schemes, comfortably and natively supports relationships of practically any finite arity. Figure 14.4 shows how we can model a prescription in ILE as a relationship of arity 4.
Figure 14.4. The Prescription relationship in ILE.
In section 5 of this chapter, we will discuss, among other things, how such relationships are implemented in ILE using relationship objects that securely link the various entities playing the roles in each relationship so that navigation from the entities playing one set of roles to the entities playing another set of roles is direct and efficient.
Susie Andretta , in Ways of Experiencing Information Literacy, 2012
Conclusion
The book offers a unique interpretation of the relational approach that generates a multiple-context outcome space of information literacy, where the description of the experience of information literacy, that is its conceptualisation and practice, needs to take into account the learners' interpretation of the context in which the information literacy experience occurs. The following inferences can be made from this multiple-context relational approach. In contrast with previous relational studies which developed a single-context outcome space underpinned by the binary person-information relationship, the multiple-context outcome space combines the binary relationship with the ternary relationship that reflects a three-way professional interaction, shown in this study as user–librarian–information (Provision) or librarian–user–information (Education). Through the combined use of binary and ternary relationships the multiple-context outcome space enables the experience of information literacy to be examined from a wider perspective, which takes into account the view of the user as a learner in addition to the views of the provider or the educator. In other words, the postgraduate students investigated in this study experience information literacy as learners, studying for the MA, and as librarians, who are professionally associated with delivery information literacy programmes. This makes the outcome space of this research better suited than those of previous studies to inform future relational investigations examining the ways in which information literacy is conceptualised and practised in an educational setting.
The book also proposes that in this multiple-context outcome space complex dynamics exist within and between the categories of description, and this enables the examination of a broader impact of the information literacy experience on the learner. These dynamics are defined as transformation, where the conceptualisation or practice of information literacy in one category may affect the conceptualisation or practice of information literacy in the same category, and transfer where the conceptualisation or practice of information literacy in one category may affect the conceptualisation or practice of information literacy in a different category. As we have seen in Chapter 4, the students who participated in this study carried out two research tasks and this turned out to be significant because it established the spatial awareness of 'before' and 'after' the experience of information literacy generated by these tasks. The completion of the two reviews gave the students an opportunity to reflect on how the information literacy practices involved in the first review (normally for the AIR proposal) influenced the information literacy practices employed to complete the second review (for the dissertation). Moving from the first to the second review generated instances of transformation and transfer. Transformation affects the first three categories of information literacy, Functional Literacy, Lifelong Learning and Provision. Transformation within the category of Lifelong Learning for example, shows that the changes from information literacy practices underpinning the review lead to a greater understanding of the role of the literature review in establishing the direction of the investigation (S_4; S_11) and promote a greater ability to deal with the unpredictability of real-world research (S_21), or with the uncertainty of the information 'void' (S_6). In Provision, transformation is described by some students as improved elicitation of the users' information needs (S_11; S_16; S_6; S_17). On the other hand, transfer from Lifelong Learning to Provision reflects the changes in the students' professional conceptualisation and practice of information literacy. An example of this change is shown by student 21 who began to question the assumption that librarians 'need to know the answer' to fulfil the users' information needs, stressing instead the importance of employing information literacy practices that can find 'any' answer. This view offers a clear example of what Fazey and Marton (2002) describe as 'mastering the process of variation', where this student begins to focus on the process of finding an answer that varies depending on the nature of the query. From the point of view of the information literacy educator the multiple-context relational approach offers the following benefits. First, it enables one to identify which conceptualisation and practice are associated with the experience of information literacy and tailor the support accordingly. Second, this relational approach provides the means by which the educator may encourage a particular experience of information literacy to expand the students' conceptualisation and/or practice in one category, or from one category to another.
In conclusion, this book makes a significant contribution to the relational approach for the following reasons. First, the multiple-context outcome space offers a wider interpretation of information literacy than the one generated by the relational approaches used in previous studies. This is because the conceptualisation and practice of information literacy proposed by the multiple-context outcome space relate to different contexts, types of information relationship and nature of the information goal. In other words, variation in this study is not based on the different aspects of information literacy that are associated with one context, but is generated by different information literacy experiences that are related by the students to the personal, the academic and the information professional contexts. For example, the Functional Literacy category describes different conceptualisations and practices of information literacy compared with the Lifelong Learning category because its everyday activities, such as looking for accommodation or booking a holiday, do not appear to the students to require the same levels of reflection and evaluation that are needed to address the open-ended questions found in Lifelong Learning, such as reviewing the literature for an unfamiliar topic. Second, the multiple-context outcome space generates complex patterns of interaction between the conceptualisations and practices of information literacy within and across the categories of description. In this study the impact of these interactions is described in terms of transformation and transfer. As we have seen at the beginning of this chapter, previous relational studies have explored transformation that occurs as a result of the information literacy experience. However, these studies cannot examine transfer, which by definition applies to the changes that occur across two categories of description that relate to different contexts. This suggests that in addition to providing a wider interpretation of information literacy, the multiple-context approach offers a more comprehensive way of measuring the impact of information literacy than a single-context approach and could be employed to assess the impact of other learning conditions.
Inevitably, some of the areas touched on by this investigation, such as the significance of personal disposition towards information and the development of librarians into educators, reach beyond the scope of this study and must remain topics for future research. But it is to be hoped that this multiple-context outcome space will be found productive by the diverse audiences identified at the beginning of this book. For example, educators could use this outcome space to explore different experiences of information literacy or of learning, with students from other academic disciplines or with communities operating outside the higher education sector. Supporting this view is the proposition that the relational approach to information literacy (or the relationship between person and information) describes the act of learning, and this necessarily complements the content learned. In addition, the 'how to apply the relational framework' approach presented in this book targets researchers and doctoral students who wish to investigate people's relationships with information and the impact that these have on the outcome of learning. And finally, the effective information literacy practices used to review the literature identified by the students who participated in this study may prove useful to postgraduate students who are embarking on similar research projects. In this wider context the research outlined in this book will have met its goal if it can form a small but significant step in furthering the debate on the way learners experience information literacy and on the suitability of the relational approach in examining these experiences.
BERTHOLD DAUM , in Modeling Business Objects with XML Schema, 2003
2.5.1 AOM Basics
The main components in AOM for describing the structure of an information model are assets and arcs. Unlike the various flavors of Entity Relationship Modeling, AOM does not distinguish between entities and relationships (or between classes and associations as UML does). Assets are not the same as entities, and arcs are not the same as relationships. AOM uses assets and arcs more in the way the Resource Description Framework (RDF) uses nodes and arcs. The classical entities and relationships are both represented in AOM as assets. Or, to be precise, AOM treats everything—even entities—as relationships. Let's see how this works.
Take for example a classical entity type, Customer. Let's say this entity type is related to entity type Person by an is_a relationship, and with entity type Account by a has relationship. So the classical model would have three entity types: Customer, Person, and Account, and two relationship types: is_a and has.
However, we could interpret this situation quite differently. We could see Customer as a binary relationship that relates an account to a person. If we also want to include the fact that a customer resides at a given address, then Customer becomes a ternary relationship between Person, Account, and Address. In fact, a relationship might relate any number of items to each other. Generally, we allow n-ary relationships.
Do we also have 1-ary (unary) relationships? Of course we have. Take for example a bicycle. A bicycle can be seen as a binary relationship because it relates the front wheel and the back wheel to each other. What about a monocycle? Obviously, a monocycle represents a unary relationship. That might sound like one hand clapping, but mathematically it is perfectly correct.
Let's put this all together and look at a first example. What was said for the monocycle applies in the model in Figure 2.4 to OrderItem. OrderItem is a unary relationship referring to CD. The binary relationship orders relates the two relationships Customer and OrderItem to each other. Finally, the binary relationship receives relates the relationships orders and Shop to each other.
Figure 2.4. Simple model for a music shop. Note that arcs do not represent a relationship but simply connect an asset with other assets that play a role in the context of the first asset. Arcs can be decorated with role names.
Modeling this example in a classical modeling method would give us some trouble because in classic theory it is not clear if orders is a relationship or an entity. If we decided for a relationship orders, we would have trouble with relationship receives, as this relationship would now relate an entity (Shop) with another relationship (orders)—a concept that is not supported in classical modeling methods.
In classical ERM, if we decided for an entity, we would first have to reify the act of ordering into an entity Order. (To reify means to make into a thing.) Then we would have to invent additional relationships to relate Order to Customer and CD. The model gets bigger. Unfortunately, these scenarios where we would have to treat relationships as entities are not uncommon. In modern business scenarios, any business relationship manifests itself sooner or later as a business document and, alas, becomes an entity.
So far, we have not discussed how to represent the end nodes of our graph: Person, CD, Account, Address, and Shop. Shouldn't we represent these assets differently—as entities? I think not. These assets are always potential relationships. For example, if we add an asset Department to Shop, then Shop becomes a unary relationship. As long as Department is not added, Shop is, well, a 0-ary relationship. If this sounds a bit uncommon, consider that the concept of zero was uncommon itself until the number zero was invented only some time ago in Arabia. The advantage is that with this concept, a given model is easier to extend. When we want to add Department to Shop, we just connect it with an arc, but we do not have to convert Shop from an entity into a relationship.
AOM's concept of using relationships over relationships is based on Bernhard Thalheim's Higher Order Entity Relationship Modeling (HERM) [Thalheim-2000], although Thalheim still differentiates between entities and relationships. In this respect AOM is closer to the relational approach, where both entities and relationships are represented as tables. It was E. F. Codd, the father of relational algebra, who stated that there is no reason to distinguish between entity type and relationship type [Codd1991]). Consequently, relational database schemata translate nicely into AOM.
The following sections will introduce AOM's language elements in a more formal way.
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When it comes to gluing two surfaces, choosing the right adhesive type can be tricky. Here in the US, Gorilla Glue and Liquid Nails are the two best options. But who wins the race between Gorilla Glue vs. Liquid Nail?
Turns out, both of their expertise is in different fields. If you want a strong wooden bond, Gorilla Glue will work perfectly for you. On the other hand, Liquid Nail churns out great results when working with varying materials. Liquid Nails provide a strong adhesive layer, which feels like rubber after application.
Today, we will see which brand is better for construction and other suited projects. We have included a comparison chart, so you don't have to read the whole thing to get your answer.
Contents
1 Liquid Nails Vs. Gorilla Glue Comparison Chart
2 Liquid Nails: What makes them special?
2.1 Project type
2.2 Curing time and peeling
2.3 Longevity
3 Gorilla Glue: What makes it special?
3.1 Curing time
3.2 Project type
3.3 Longevity of adhesive
4 Gorilla Glue vs. Liquid Nails: Head to Head
4.1 Curing time
4.2 Toxic gas release
4.3 Removal from the skin
4.4 Strength and durability
4.5 FAQs
4.5.1 Is Gorilla Glue better than liquid nails?
4.5.2 Is Liquid Nails stronger than wood glue?
4.5.3 What is Liquid Nails good for?
4.5.4 Can I use Gorilla Glue instead of Liquid Nails?
4.5.5 What is the strongest no nails adhesive?
5 End Note
Liquid Nails Vs. Gorilla Glue Comparison Chart
In a hurry? Check out the comparison chart to find out your best answer.
Features
Liquid Nails
Gorilla Glue
Working surface
Works perfectly on Similar surfaces, but also work on varying ones
Good for varying material surfaces
Project type
Indoors
Outdoors
Curing time
About 15-20 mins
About 30 mins
Structure after curing
Rubber texture
Hardens after curing
Peel strength
Doesn't resist pressure that much
Doesn't peel off easy
Longevity
Will last 2 years on surfaces
Won't break until you open the bond
Liquid Nails: What makes them special?
Liquid Nails is an industry-leading product when it comes to joining materials. Having a high-strength internal adhesive bond, liquid nails can work their way through plastic, metal, wood, and so on. If you are a professional or a DIY guy, liquid nails' multipurpose feature will do you wonders. Now, you can reach places where traditional nails and hammers can't reach. Turns out, liquid nails work on almost anything, starting from house molding to all the way stones.
Project type
Working with similar materials just got easier with liquid nails. It provides a fast and permanent, and water-resistive bond, which lasts for years to come. You can work on any outdoor projects like brick veneer, concrete, ceramic, etc. If you are a professional construction worker, liquid nails will help you in projects where normal nails won't do you any good.
Curing time and peeling
With a curing time of 15 mins, liquid nails can finish a project fast and easily. Unlike other glue types, liquid nails will give you better results in outdoor conditions where rain can come anytime. Its peeling strength, resistance to any sort of pulling after a perfect adjustment.
Longevity
Liquid nails have tough longevity of 2 years or more. It also depends on the temperature and humidity. If the temperature is similar to a desert, chances are the glue will last for more than just two years.
Pros
Adjusts to a high-temperature environment
Perfect adjustment for any surface
Will last for years to come
Works on both dry and wet surfaces
Cons
The cleanup process is hard
Removing it from the skin needs oil
Gorilla Glue: What makes it special?
Gorilla glue is another top-notch product for joining any material. However, it works great for any indoor project, especially wooden surfaces. If you have a broken wooden broomstick or a table, just add some gorilla glue and wallah. Gorilla glue is now possible to get the perfect joining of metals, stones, foam, etc. Turns out, you need just 30 mins to attach any indoor material at hand.
Curing time
The curing time of gorilla glue is about 30 minutes. Add some Gorilla Glue adhesives and tie the whole thing up. After the curing, the bond will stay tight even after applying pressure. Suppose your wooden table is broken, what will you do? Well, add home gorilla glue and start using the table like it never broke.
Project type
No matter what type of indoor projects you have, Gorilla glue will do them all. It can work on wood, stones, metals, ceramic, etc., with picture-perfect results. But for outdoor works, the rising temperature and moisture can degrade the glue joint. You should use gorilla glue in projects where the environment is constant.
Longevity of adhesive
With 2-years of minimal usage time, gorilla glue has one of the best adhesive longevity. However, too much moisture and heat can dampen the joint, causing it to break easily. If you are working on surfaces other than wood, chances are gorilla glue can't withstand too much pressure.
Gorilla Glue vs. Liquid Nails: Head to Head
Though Gorilla glue and liquid glue are top in their game, only one is the true winner. Well, not technically. Both of them have their uses. When you want a solution for indoor work, gorilla glue is the way to go. On the other hand, Liquid glue works great in surface variations like wood to metal or metal to stone adjustment. Here are some differences between Liquid Nails and Gorilla Glue,
Curing time
The Liquid Nails need about 15 mins to cure, whereas gorilla glue takes 30-40 mins. A faster curing time will ensure faster work in both DIY and professional projects. However, the quick drying time comes at the cost of low resilience for dissimilar objects.
Toxic gas release
Being a solvent-based adhesive, liquid nails releases a toxic gas that can harm your body. Gorilla glue doesn't have anything toxic and is harmless to use. Rule of the thumb, don't touch liquid nails with your bare hands.
Removal from the skin
Both the liquid nail and gorilla glue will stick to your hands. But for how long? Well, to remove Liquid nail or Gorilla Glue, you need petroleum jelly or oil. However, Gorilla glue will come off easier than Liquid nails.
Strength and durability
Liquid nails are great for surface variations, whereas Gorilla glue works on the same surface materials. For example, Gorilla glue works better from wood to wood, rubber to rubber, and so on. The strength of gorilla glue decreases when the project involves more than surface type.
However, liquid glue withstands any surface type you have. Both of them are durable, where Gorilla glue is weaker compared to Liquid nails. You can expect Gorilla glue or Liquid Nails bond to last for 2 years at least.
FAQs
Is Gorilla Glue better than liquid nails?
Gorilla Glue and liquid nails have different uses. Gorilla glue works great for similar surface types, whereas liquid nails can go both ways. If you are working with wooden surfaces, liquid nails won't do you any good. So, which adhesive is better depends on where you are using it.
Is Liquid Nails stronger than wood glue?
Liquid nails are stronger than wood glue, but only for wood-to-wood attachments. When the project includes surface variation, try using liquid nails instead. You will end up with a better adjustment for the project.
What is Liquid Nails good for?
Liquid Nails is good for metals, plastics, rubber, and so on. You can use it on wooden surfaces as well, but the bonds may break. Additionally, Liquid nails can handle any outdoor project, starting from ceramics to stone adjustment.
Can I use Gorilla Glue instead of Liquid Nails?
You can use gorilla glue instead of liquid nails, but the bond can't withstand high temperatures. If you live in places where there is high heat, use liquid nails instead. This is the only reason liquid nails are the best option for outdoor projects.
What is the strongest no nails adhesive?
The strongest no nail adhesive is the Loctite PL Fast Grab Premium and the DELO MONOPOX VE403728. Both of them can resist high temperature and pressure for the strongest bond possible in no nails.
End Note
Getting to a complete conclusion isn't easy, especially when you have the two best glue types. For us, Liquid nails have a better option, ending up on our shelves. However, woodworkers should prefer Gorilla glue as it has a better wood-to-wood bond.
Then again, liquid nails produce a toxic gas while drying. You need to be careful about that as well. This is all for today. Have a good day.
On Design with Justyna Green brings you insightful conversations with the arts & design's most inspiring figures - from designers to architects, editors to creative directors and everybody in between. If you want to know what inspires them, how they work and how they see the world, this is the podcast for you. Listen to the On Design podcast now on Apple Podcasts, Spotify and Google Play.
Architect Arthur Mamou-Mani is this week's podcast guest. Arthur specialises in digital fabrication led architecture and some of his recent projects you'll be familiar with include Galaxia - the Burning Man temple from 2018 and Conifera - last year's COS installation at the Milan Design Week.
In our conversation, we discuss Arthur's practice, parametric architecture, his FabPub 3D printing and laser cutting facilities in East London which are available to all and we also get personal, chatting about what it's like to get married at the Burning Man and overcome depression.
HIGHLIGHTS & TIMESTAMPS
00:05
I want to look at interesting, meaningful things, I want to highlight them, I want to show how they're linked to nature and how nature is really an artistic venture of slight adaptations and parameters that create beautiful things.
06:15
When you walk in a forest and you see really interesting patterns you don't ask 'who designed' it – who cares? And if you were to ask you realise it's the cells and the DNA and the bee that comes etc. There are so many parameters to the creation of the beautiful things.
09:00
There was a big revolution called RepRapp, it was a British doctor Adrian Boyer, he started wanting to replicate a machine, to self-replicate a machine and so he did RepRapp as a machine which can print components of itself, which is a very exciting concept.
12:57
Burning Man is a prototype of a city of the future, that's what really excited us.
14:06
Design career is a lifelong thing, it's not just one project that makes or breaks it. Design is not only a concept – design is delivery, its spreadsheets, funds, entrepreneurship and it's team work.
26:58
We used terms 'designed by' and that in its essence I find weird because it's not true. This term 'designed by someone' is an inhibitor, it turns the ego switch on.
32:20
Even the movement of 3d printing – somehow when you send information in the form of general code in segments you end up with textures that are reminiscent of nature, because on a very local level the material finds its own equilibrium, similar to what Gaudi was doing with chain models. So once you start letting go of imposing anything on machine, on the Earth, then you start having a natural approach and the material will start to express itself.
About this author
Cite: On Design. "Arthur Mamou-Mani on Parametric Architecture" 21 Mar 2020. ArchDaily. Accessed . <https://www.archdaily.com/936029/arthur-mamou-mani-on-parametric-architecture> ISSN 0719-8884
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Misplacing your Volkswagen car key is frustrating enough, but what happens if you lose it permanently? You have no other option than to seek a replacement, but if you've never been in this position before, you may not have a clue how to get a new key. It turns out there are a few ways to do it.
Whether you're stranded somewhere or you lost your key at home, you need to get a VW key replacement as soon as possible. Here's a look at how to get a new key as soon as possible.
Write Down Your VIN Number
The first thing you need to do is jot down your vehicle's VIN number. Depending on the model of Volkswagen you own, the VIN may be in one of a few places. Most likely, it's located with the other VW dashboard symbols on the driver's side. It may also be on the door jam or on one of the rear wheels.
If you're having trouble locating it on the vehicle and your purchase documentation is long gone, you can find it on your insurance policy. The VIN is 17 characters long and consists of both letters and numbers. Make sure you write it down correctly, as this is an important detail when getting a new key from a locksmith.
Call a Locksmith
If you need quick access to your car and a new key right away, calling a locksmith is your best bet. Not only can a locksmith get into your vehicle, he or she can also help with a replacement key. If you own an older model Volkswagen, the locksmith will have to decode the locks in order to make a new key.
If you own a newer model, a locksmith can cut a new key based on a code for your car, and this requires your VIN number. Even if you have a key fob, getting a replacement from a locksmith is possible by allowing him or her to access the onboard computer for your vehicle. Make sure the locksmith has the ability to do this before hiring.
Get a New Key from Your Dealership
Another option is going to your Volkswagen dealership to get a new key. If you opt for this approach, you have to take a few things with you, including proof of ownership and your driver's license. Call in advance and ask if they require anything else.
Keep in mind your dealer has to order a replacement, so you won't have access to your vehicle right away. It may take two to three days. The dealer also needs the VIN number to place the order. Once the replacement arrives, they will have to program the computer so the replacement works if you have a newer model VW.
Understand the Cost
Unfortunately, getting a VW key replacement is going to cost you some money. If your car uses a fob, a replacement can be rather expensive. Expect to pay as much as $350. You may also have to factor in the cost of getting your car towed.
If you use a locksmith route, you have to pay for the service along with the key itself. Make sure you ask for a quote. Some locksmiths take advantage of people who are desperate and charge unreasonable amounts. However you get a new key, make sure to get a spare key made so this doesn't happen again.
Look for Keys Online
If you want to avoid paying hundreds of dollars for a new key, check for an online provider is an option. Many key dealers advertise their services on sites like eBay or Amazon. Keep in mind that replacing an older key is much easier. Some of these dealers can't handle newer keys or fobs.
However, with a little digging, you may be able to find someone who has the equipment and knowledge to make a new programmed key. If so, these sources may charge less than a locksmith or a dealership. Make sure you have the VIN and ask if they need any other VW engine specifications.
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