1 The Discipline of Organizing

To organize is to create capabilities by intentionally imposing order and structure.

Organizing is such a common activity that we often do it without thinking much about it. We organize shoes in our closet, books on our book shelves, spices in our kitchen, receipts and records in tax preparation folders, and people on business projects and sports teams. Quite a few of us have jobs that involve specific types of organizing tasks. We might even have been explicitly trained to perform them by following specialized disciplinary practices. We might learn to do these tasks very well, but even then we often do not reflect on the similarity of the organizing tasks we do and those done by others, or on the similarity of those we do at work and those we do at home. We take for granted and as givens the concepts and methods used in the Organizing System we work with most often.

The goal of this book is to help readers become more self-conscious about what it means to organize resources of any type and about the principles by which the resources are organized. In particular, this book introduces the concept of an Organizing System: an intentionally arranged collection of resources and the interactions they support. The book analyzes the design decisions that go into any systematic organization of resources and the design patterns for the interactions that make use of the resources, as follows:

We organize physical things. Each of us organizes many kinds of things in our livesour books on bookshelves; printed financial records in folders and filing cabinets; clothes in dressers and closets; cooking and eating utensils in kitchen drawers and cabinets. Public libraries organize printed books, periodicals, maps, CDs, DVDs, and maybe some old record albums. Research libraries also organize rare manuscripts, pamphlets, musical scores, and many other kinds of printed information. Museums organize paintings, sculptures, and other artifacts of cultural, historical, or scientific value. Stores and suppliers organize their goods for sale to consumers and to each other. Sports leagues organize players into teams, and the teams organize players by position or role.

We organize information about physical things. Each of us organizes information about things: when we inventory the contents of our house for insurance purposes, when we sell our unwanted stuff on eBay, or when we rate a restaurant on Yelp. Library card catalogs, and their online replacements, tell us what books a library’s collection contains and where to find them. Sensors and RFID tags track the movement of goodseven library booksthrough supply chains, and the movement (or lack of movement) of cars on highways.

We organize digital things. Each of us organizes personal digital informationemail, documents, ebooks, MP3 and video files, appointments, contactson our computers, smartphone, ebook readers, or in “the cloud,through information services that use Internet protocols. Large research libraries organize digital journals and books, computer programs, government and scientific datasets, databases, and many other kinds of digital information. Companies organize their digital business records and customer information in enterprise applications, content repositories, and databases. Hospitals and medical clinics maintain and exchange electronic health records and digital X-rays and scans.

We organize information about digital things. Digital library catalogs, web portals, and aggregation websites organize links to other digital resources. Web search engines use content and link analysis along with relevance ratings, to organize the billions of web pages competing for our attention. Web-based services, data feeds and other information resources can be interconnected and choreographed to carry out information-intensive business processes, or aggregated and analyzed to enable prediction and personalization of information services.

Let us take a closer look at these four different types or contexts of organizing. We contrasted “organizing things” with “organizing information.” At first glance it might seem that organizing physical things like books, compact discs, machine parts, or cooking utensils has an entirely different character than organizing intangible digital things. We often arrange physical things according to their shapes, sizes, material of manufacture, or other intrinsic and visible properties: for example, we might arrange our shirts in the clothes closet by style and color, and we might organize our music collection by separating the old vinyl albums from the CDs. We might arrange books on bookshelves by their sizes, putting all the big, heavy picture books on the bottom shelf. Organization for clothes and information artifacts in tangible formats that is based on visible properties does not seem much like how you store and organize digital books on your Kindle or arrange digital music on your music player. Arranging, storing, and accessing X-rays printed on film might appear to have little in common with these activities when the X-rays are in digital form.

It is hardly surprising that organizing things and organizing information sometimes do not differ much when information is represented in a tangible way. The era of ubiquitous digital information of the last decade or two is just a blip in time compared with the more than ten thousand years of human experience with information carved in stone, etched in clay, or printed with ink on papyrus, parchment, or paper. These tangible information artifacts have deeply embedded the notion of information as a physical thing in culture, language, and methods of information design and organization. This perspective toward tangible information artifacts is especially prominent in rare book collections where books are revered as physical objects with a focus on their distinctive binding, calligraphy, and typesetting.

Nevertheless, at other times there are substantial differences in how we organize things and how we organize information, even when the latter is in physical form. We more often organize our “information things” according to what they are about rather than on the basis of their visible properties. At home we sort our CDs by artist or genre; we keep cookbooks separate from travel books, and fiction books apart from reference books. Libraries employ subject-based classification schemes that have a few hundred thousand distinct categories.

Likewise, there are times when we pay little attention to the visible properties of tangible things when we organize them and instead arrange them according to functional or task properties. We keep screwdrivers, pliers, a hammer, a saw, a drill, and a level in a toolbox or together on a workbench, even though they have few visual properties in common. We are not organizing them because of what we see about them, but because of what we know about to use them. The task-based organization of the tools has some similarity to the subject-based organization of the library.

We also contrasted “organizing things” with “organizing information about things.” This difference seems clear if we consider the traditional library card catalog, whose printed cards describe the books on library shelves. When the things and the information about them are both in physical format, it is easy to see that the former is a primary resource and the latter a surrogate or associated resource that describes or relates to it.

Most of the hundreds of definitions of information treat it as an idea that swirls around equally hard-to-define terms like “data,” “knowledge,” and “communication.” Moreover, these intellectual and ideological perspectives on information coexist with more mundane uses of the term, as when we ask a station agent: “Can you give me some information about the train schedule?

An abstract view of information as an intangible thing is the intellectual foundation for both modern information science and the information economy and society. Nevertheless, the abstract view of information often conflicts with the much older idea that information is a tangible thing that naturally arose when information was inextricably encoded in material formats. We often blur the sense of “information as content” with the sense of “information as container,” and we too easily treat the number of stored bits on a computer or in “the cloud” as a measure of information content or value.

Geoff Nunberg has eloquently explained in Farewell to the Information Age that information is “a collection of notions, rather than a single coherent concept.Michael Buckland’s oft-cited essay Information as Thing argues against the notion that information is inherently intangible and instead defines it more broadly and provocatively based on function. A resource that can be learned from or serve as evidence is “information-as-thing,” a definition that treats the tangible objects in museum or personal collections as information.[1]

When it comes to “organizing information about digital things” the contrast is much less clear. When you search for a book using a search engine, first you get the catalog description of the book, and often the book itself is just a click away. When the things and the information about them are both digital, the contrast we posed is not as sharp as when one or both of them is in a physical format. And while we used X-rayson film or in digital formatas examples of things we might organize, when a physician studies an X-ray, is it not being used as information about the subject of the X-ray, namely, the patient? And when businesspeople make marketing and pricing decisions by analyzing digital information about what and when people buy, we can think of this as organizing customers into categories, or as organizing customer information.

These differences and relationships between “physical things” and “digital things” have long been discussed and debated by philosophers, linguists, psychologists, and others. (See the sidebars, What Is Information? and The Distinction between Data and Information.)

The distinctions among organizing physical things, organizing digital things, or organizing information about physical or digital things are challenging to describe because many of the words we might use are as overloaded with multiple meanings as “information” itself. For example, the library science perspective often uses presentation or implementation properties in definitions of “document,” using the term to refer only to traditional physical forms. In contrast, the informatics or computer science perspective takes an abstract view of “document” to refer to any self-contained unit of information, separating a document’s content from its presentation or container.[2]

The most abstract definition of “document,” presented in What is a Document? follows from Buckland’s “information as thing” idea. Because it can be studied to provide evidence, an antelope is both “information as thing” and also a “document” when it is in a zoo, even though it is just an animal when it is running wild on the plains of Africa. However, in 2015 the United States Supreme Court rejected this expansive definition in a case that hinged on whether a fish could be viewed as a document.[3]

Astute readers might have noticed that we included sensor data as “information about physical things” and data feeds as “information about digital things.” Many textbooks in the information science and knowledge management fields distinguish data and information in a more precise way. To them, data sits at the bottom of an Information Hierarchy, Knowledge Pyramid, or DIKW Hierarchy in which Data is transformed into Information, which is transformed into Knowledge, which is then transformed into Wisdom.

In this framework, data are raw or elementary observations about properties of objects, events, and their environment. Data becomes information when it is aggregated, processed, analyzed, formatted, and organized to add meaning and context so it can be used to answer questions. This processing can include calculation, inference, or refinement operations on the data. For example, measurements of temperature, precipitation, and wind speed are data. When combined and summarized, a set of data becomes statistical information about the weather on a particular day. When collected over a period of months or years, these datasets become information about the climate of the location where they were collected.

The Discipline of Organizing does not make this sharp contrast between data and information in the Hierarchy/Pyramid. People who read this book are likely to be aspiring or practicing professionals in information-intensive industries where information and data are often treated as synonyms to mean the content of a database or data-managing application. A distinction between data and information might be useful in theory, but not in these applied settings.

The distinction between data and information is also being blurred by the expansion in the scope of the definition of data in the emerging career field of data science. Indeed, a popular introductory text eliminates information entirely from the Hierarchy/Pyramid with its title, Discovering knowledge in data: an introduction to data mining.[4]

Similar definitional variation occurs with “author” or “creator.” When we say that “Herman Melville is the author of Moby Dick(Melville 1851) the meaning of “author” does not depend on whether we have a printed copy or an ebook in mind, but what counts as authorship varies a great deal across academic disciplines. Furthermore, different standards for describing resources disagree in the precision with which they identify the person(s) or organization(s) primarily responsible for creating the intellectual content of the resource, People who are serious about music description rightly criticize streaming services and online stores that have only a single “artist” field because this fails to distinguish the composer, conductor, orchestra, and other people with distinct roles in creating the music.

If we allow the concept of information to be anything we can studyto be “anything that informsthe concept becomes unbounded. Our goal in this book is to bridge the intellectual gulf that separates the many disciplines that share the goal of organizing but differ in what they organize. This requires us to focus on situations where information exists because of intentional acts to create or organize. (See the sidebar, The Discipline of Organizing)

A discipline is an integrated field of study in which there is some level of agreement about the issues and problems that deserve study, how they are interrelated, how they should be studied, and how findings or theories about the issues and problems should be evaluated. A framework is a set of concepts that provide the basic structure for understanding a domain, enabling a common vocabulary for different explanatory theories.

Organizing is a fundamental issue in many disciplines, most notably library and information science, computer science, systems analysis, informatics, law, economics, and business. However, these disciplines have only limited agreement in how they approach problems of organizing and what they seek as their solutions. For example, library and information science has traditionally studied organizing from a public sector bibliographic perspective, paying careful attention to user requirements for access and preservation, and offering prescriptive methods and solutions.[5]

In contrast, computer science and informatics tend to study organizing in the context of information-intensive business applications with a focus on process efficiency, system architecture, and implementation. The disciplines of management and industrial organization deal with the organization of human, material, and information resources in contexts shaped by commercial, competitive, and regulatory forces.

This book presents a more abstract framework for issues and problems of organizing that emphasizes the common concepts and goals of the disciplines that study them. Our framework proposes that every system of organization involves a collection of resources, and we can treat physical things, digital things, and information about such things as resources. Every system of organization involves a choice of properties or principles used to describe and arrange the resources, and ways of supporting interactions with the resources. By comparing and contrasting how these activities take place in different contexts and domains, we can identify patterns of organizing and see that Organizing Systems often follow a common life cycle. We can create a discipline of organizing in a disciplined way.

Many of the foundational topics for a discipline of organizing have traditionally been presented from the perspective of the library sector and taught as “library and information science.” These include bibliographic description, classification, naming, authority control, curation, and information standards. In recent decades these foundations have been built on and extended by computer science, cognitive science, informatics, and other new fields to include more private sector and non-bibliographic contexts, multimedia and social media, and new information-intensive applications and service systems enabled by mobile, pervasive, and scientific computing. The latest additions to the discipline of organizing are coming from data science and machine learning, introducing considerations of speed and scale that arise when massive computational power and new statistical techniques are harnessed to organize and act on information.

The new methods and tools of data science and machine learning let us organize more information, to do it faster, and to make predictions based on what people have clicked on, bought, or said. But this is not the first time that new ideas and technologies have challenged how people organized and interacted with resources. Fifty years ago, searchable online catalogs radically changed how people used libraries. The web, invented less than thirty years ago so that scientists could share technical reports, is now an essential part of many human activities. It is important not to view the latest new thing as changing everything, because new things will continue to come, and these technology breakthroughs still depend on and complement the organizing work done by people. Data science will not replace human organizers, any more than any other science has replaced humans. (See sidebar, Data Science and the Discipline of Organizing).

This is why we need to take a transdisciplinary view that lets us emphasize what the different disciplines have in common and how they fit together rather than what distinguishes them. Resource selection, organizing, interaction design, and maintenance are taught in every discipline, but these concepts go by different names. A vocabulary for discussing common organizing challenges and issues that might be otherwise obscured by narrow disciplinary perspectives helps us understand existing systems of organizing better while also suggesting how to invent new ones by making different design choices.

  1. (Nunberg 1996, 2011). (Buckland 1991). See also (Bates 2005).

  2. (Glushko and McGrath 2005).

  3. (Buckland 1997). The idea that an antelope could be a document was first proposed in (Briet 1951).

    A commercial fisherman in Florida was found with fish in his catch below the legal size limit. An inspector ordered him to return to port and hand the fish over to the authorities; when he dumped them overboard instead, he was charged with violating the Sarbanes-Oxley Act, a law drafted in response to high-profile white-collar crimes such as the Enron scandal. The law imposes harsh penalties for destroying “any record, document, or tangible object” to impede a federal investigation. The fisherman argued that the law should only apply to written documents, but the United States government contended that because the fish were “tangible objects” whose presence on the boat served as the only documentation of the allegedly illegal fishing, there was no practical difference between a fish and a document in this case. The Supreme Court ruled in favor of the fisherman, finding that “tangible object” must be interpreted in the context of “record” and “document” and, as such, only applies to an object “used to record or preserve information.” The fact that a fish is tangible evidence in this case does not make it a document.

    (Buckland 1991).

    (Liptak 2014). Brief for the United States in Opposition, Yates v. United States. SCOTUSblog, March 14, 2014. http://www.scotusblog.com/case-files/cases/yates-v-united-states/

    For the complete history of the case, see: http://www.scotusblog.com/case-files/cases/yates-v-united-states/.

    See also the related Sarbanes-Oxley Act endnote.[link to footnote]

  4. The DIKW hierarchy seems to have been inspired by The Rock, A Pageant Play (Eliot 1934) by the poet T S Eliot, whose opening chorus contains these lines:

    Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?

    Most people credit Ackoff’s From Data to Wisdom (Ackoff 1989) as the first articulation of the hierarchy in an information science and systems context. The hierarchy is mentioned in nearly twenty textbooks, but their close analysis by (Rowley 2007) reveals only partial agreement on the definitions and relationships among the four key concepts. The hierarchy has been criticized as lacking in philosophical rigor (Fricke 2009) and for ignoring the context-specificity of how knowledge is learned and applied (Jennex 2009). (Larose 2014)

  5. We can continue the debate in the previous paragraphs and the sidebar, What Is Information? by pointing out that in both common and professional usage, “bibliographic” activities involve describing and organizing information resources of the kinds that might be found in a library. But noted information scientist Patrick Wilson argued for a much broader expanse of the bibliographic universe, suggesting that “it includes manuscripts as well as printed books, bills of lading and street signs as well as personal letters, inscriptions on stone as well as phonograph recordings of speeches, and most notably, memorized texts in human heads and texts stored up in the memories of machines(Wilson 1968, p. 12).

  6. Siegel’s Predictive Analytics: The Power to Predict who will Click, Buy, Lie or Die(Siegel 2013) is written for a non-technical audience and enthusiastically describes over 100 applications. The Master Algorithm (Domingos 2015) shares Siegel’s enthusiasm but is far more technical; the book attempts to explain and compare the five “tribes” of machine learning: the symbolists, connectionists, evolutionaries, Bayesians, and analogizers. The title of Chris Anderson’s provocative article in Wired Magazine (Anderson, 2008) is self-explanatory: “The end of theory: The data deluge makes the scientific method obsolete.

    Difference in kind or difference in degree” is an important issue in legal contexts and more generally arises whenever there is a disagreement about whether some difference or change is strict and categorical or whether it is incremental. We introduce it here so that readers can think critically about the socio-business-technical changes that might come about as a result of new methods and technologies for organizing and analyzing data. We believe that data science is on its way to becoming an important part of the organizing tool box. But everyone needs to remember that humans own the tool box, and that they design and build the tools.


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