Vocabulary, formal

When introducing the current work, avoid informal phrases such as "we looked into", "we looked at", "we saw if". See Formal Vocabulary in appendix A. 

Audience and Purpose Concise Writing 584 Fluid Writing 586 Formal Vocabulary 588 Hedging 590 Nominalizations 594 Respectively 597 Unambiguous Writing 599 Writing Conventions... 

Writing in chemistry requires authors to use more formal vocabulary than they would use in speaking. For example, you could say we cut back on the solvent, but you would write the solvent was decreased (or reduced). ... 

Static models have different uses in different parts of the development life cycle. If we decided to start from scratch in providing software support for a hotel s booking system, our analyst s first deliverable would be a description of how the hotel business works, and a type model would be an essential part of it, formalizing the vocabulary. Later in the life cycle, the objects in the software can be described in the same notation. 

In addition to a narrative, it is useful to have an index of the vocabulary. The glossary s purpose is to link the formal terms back to the real world. Rather than a single monolithic table at the end of the document, the definitions could be introduced as needed in the context of the document structure, together with additional explanation.2... 

It is often helpful to start with an initial informal sketch of the main terms and concepts, drawn as a concept map. It serves as a concrete starting point for capturing the vocabulary used and the relationships between terms (see Figure 14.9). A concept map is simply a graph of labeled nodes and labeled (preferably directed) edges. We do not try to formalize the map or even worry much about distinguishing objects, types, actions, and associations. The concept map can serve as the starting point for the type model and collaborations. 

The notion of supervenience seems fairly suitable for our purposes. Instead of two different vocabularies, we may now talk about two conceptual schemes, A and 5. They share a domain if at least some of the facts described in one of them supervene on the facts described in the other one, i. e. a subset of the 5-facts supervene on the A-facts. This criterion for the intersection of domains is quite congenial to internal realism. It does not demand going outside conceptual schemes. We do not have to assume any mind-independent structure to mediate between them. Rather, the shared domain can be described from inside any of the conceptual schemes. Also, the intuition we want to capture by the idea of sharing a domain is quite like the intuition which is formalized by the notion of supervenience. What we want to capture is that two sets of facts are not really distinct in a way, they pull together. Nevertheless, supervenience captures more. It also captures that one of the two sorts of facts are more basic, the other sort is derivative . But this is no problem, for two reasons. First of all, internal realism has no problem with one... 

Publishers often provide human-readable guidelines for authors (also known as style guides) for document preparation, which sometimes can extend to entire books. Humans are also quite prone to noncompliance or imperfect compliance because they are often busy or perhaps simply readily bored. Guidelines for data preparation, if they exist, are often to be found in optional categories, such as supporting information. If an author deposits data in such a form, how does the publisher know that it is correct A key aspect of XML is that documents (and of course datuments) can be validated. For publishing purposes, validation implies a contract between the author and the publisher, which is machine-enforceable. A schema formalizes the syntax, vocabulary, document structure, and some of the semantics. It comprises a set of machine-based rules to which a datument must conform. If it does not, it is the author s responsibility to edit it until it does. If it conforms, it is assumed that the author has complied with the publisher s requirements. 

Introduction of XML formats was a very important step toward better intercomputer communication, but it is not a miraculous solution to all problems. Not every possible relation is easily expressed in XML (Wang et al. 2005), so specifications usually contain many implicit assumptions that are not properly formalized. The Resource Description Framework (RDF) provides a very powerful yet simple model for this formalization (Manola and Miller 2004). In this framework, any information is transformed to basic units called triplets that are combined to map the available information. This unifying mechanism can be used to express hierarchical vocabularies for domain knowledge description, as in RDF Schema (Brickley and Guha 2004) or its extension, Web Ontology Language (OWL) (Smith et al. 2004), both standardized by the W3C. 

Knowing special facts about your audience makes a difference, often in your choice of words and tone. You wouldn t, after all, use the same level of vocabulary addressing a group of fifth-graders as you would writing to the children s teacher or principal. Similarly, your tone and word choice probably wouldn t be as formal in a letter to a friend as in a letter to the telephone company protesting your most recent bill. 

All the derivations of the Boltzmann equation are based on a number of assumptions and hypotheses, making the analyzes somewhat ad hoc irrespective of the formal mathematical rigor and complexity accomplished. So in this book a heuristic theory, which is physically revealing and equally ad hoc to the more fundamental derivations of the Boltzmann equation, is adopted. It is stressed that the notation used resembles that introduced by Boltzmann [6] and is not strictly in accordance with the formal mathematical methods of classical mechanics. However, some aspects of the formal formulations and vocabulary outlined in sect. 2.2 are incorporated although somewhat based on intuition and empirical reasoning rather than fundamental principles as discussed in sect. 2.3. 

As Pearson noticed [31], the terms hard and soft appear to fill a void in the chemical vocabulary. Indeed, a lot of chemistry can now be rationalized with a coherent language. Both notions have been given a rigorous theoretical basis, where before they merely reflected chemical intuition. However, it is comforting to sec that in the past, the chemists intuition was more than adequate to develop concepts very closely related to the tool-kit we have now. The aim of this section is to show the relation between some other models and the present formalism. 

Fonnal methods involve the use of formal mathematical logic, discrete mathematics and computer languages (including a formalised grammar and vocabulary) to provide evidence that the system is complete and correct with respect to its requirements, and a determination of which code, S/W requirements or S/W architecture satisfy the next higher level of S/W requirements DO-178C. 

The attribute elicitation issue may be considered differently when working with consumers. For instance, should one be interested in consumers spontaneous description, it would seem more pertinent to let the participants use their own terms without any suggestions. This may result in the elicitation of rather obvious attributes, although in past studies the vocabulary used by consumers was found to be rich and diverse (Veinand et al, 2011). On the contrary, providing a list may facilitate description (as in the Check-all-that-apply technique), but it may also bias consumers responses. However, these two options have not been formally compared yet, and ultimately the choice really has to be made with respect to the goals of the study. 

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