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2.8: Key Points in Chapter Two

  • Page ID
    73580
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    • How does a “design questions” or “dimensional” perspective on the design of organizing systems complement the familiar use of categories like library and museum?

      A dimensional perspective makes it easier to translate between category- and discipline-specific vocabularies so that people from different disciplines can have mutually intelligible discussions about their organizing activities.

      (See “Introduction”)

    • Why is the question “What is a thing?” so fundamental and challenging?

      In different situations, the same “thing” can be treated as a unique item, one of many equivalent members of a broad category, or a component of an item rather than as an item on its own.

      (See “What Is Being Organized?”)

    • How are organizing systems for physical resources and those for digital resources fundamentally different?

      A single physical resource can only be in one place at a time, and interactions with it are constrained by its size, location, and other properties. In contrast, digital copies and surrogates can exist in many places at once and enable searching, sorting, and other interactions with an efficiency and scale impossible for tangible things.

      (See “What Is Being Organized?”)

    • Why is it challenging to decide on the unit of organization for information content?

      When the resources being organized consist of information content, deciding on the unit of organization is challenging because it might be necessary to look beyond physical properties and consider conceptual or intellectual equivalence.

      (See “What Is Being Organized?”)

    • What is the essential purpose of any organizing system?

      Almost by definition, the essential purpose of any organizing system is to describe or arrange resources so they can be located and accessed later. The organizing principles needed to achieve this goal depend on the types of resources or domains being organized, and in the personal, social, or institutional setting in which organization takes place.

      (See “Why Is It Being Organized?”)

    • What are the primary purposes for the organizing systems in libraries, museums, and archives?

      Libraries, museums, and archives are often classified as memory institutions to emphasize their primary emphasis on resource preservation.

      (See “Why Is It Being Organized?”)

    • What kinds of documents are businesses and governmental agencies required to keep?

      Businesses and governmental agencies are usually required by law to keep records of financial transactions, decision-making, personnel matters, and other information essential to business continuity, compliance with regulations and legal procedures, and transparency.

      (See “Why Is It Being Organized?”)

    • What is the value created if interaction traces can be turned into interaction resources?

      If a system can turn its interaction traces into interaction resources, additional value can be created by analyzing these resources to enhance the interactions, to suggest new ones, or make predictions about how individual users or groups of them will behave.

      (See “Why Is It Being Organized?”)

    • Why is efficiency too narrow a measure for evaluating organizing systems?

      Resources are always organized in ways that are designed to allocate value for some people (e.g., the owners of the resources, or the most frequent users of them) and not for others.

      (See “Why Is It Being Organized?”)

    • What lessons from applied behavioral economics about how people make decisions have implications for the design of organizing systems?

      Subtle differences in resource arrangement, the number and framing of choices, and default values can have substantial effects on the decisions people make.

      (See “Why Is It Being Organized?”)

    • Why might merchants or firms differ in the extent or granularity of their product descriptions?

      Different merchants or firms might make different decisions about the extent or granularity of description when they assign SKUs because of differences in suppliers, targeted customers, or other business strategies.

      (See “How Much Is It Being Organized?”)

    • What are some of the potential downsides to automated resource description?

      A detailed description produced by sensors or computers can seem more accurate or authoritative than a simpler one created by a human observer, even if the latter would be more useful for the intended purposes. Detailed transaction data can be used to violate privacy and civil rights.

      (See “How Much Is It Being Organized?”)

    • How does the number of resources in a collection affect the amount of resource description and organization required?

      Organizing more resources requires more descriptions to distinguish any particular resource from the rest, and more constraining organizing principles. Similar resources need to be grouped or classified to emphasize the most important distinctions among the complete set of resources in the collection.

      (See “How Much Is It Being Organized?”)

    • How is organizing “on the way in” different from organizing “on the way out”?

      We can contrast organization imposed on resources “on the way in” when they are created or made part of a collection with “on the way out” organization imposed when an interaction with resources takes place.

      (See “When Is It Being Organized?”)

    • Why do digital resources created by automated processes exhibit a high degree of organization and structure?

      Digital resources created by automated processes generally exhibit a high degree of organization and structure because they are generated automatically in conformance with data or document schemas.

      (See “When Is It Being Organized?”)

    • What kinds of organizing systems would be impossible to create without the use of massive computational power?

      The vast size of the web and the even greater size of the “deep” or invisible web makes it impossible to imagine today that it could be organized by anything other than the massive computational power of search engine providers like Google and Microsoft. Likewise, data mining, predictive analytics, recommendation systems, and many other application areas that involve computational modeling and classification simply could not be done any other way.

      (See “How (or by Whom) Is It Organized?”)


    This page titled 2.8: Key Points in Chapter Two is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Robert J. Glushko via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.