# Title: [[{ Knowledge architectures structures and semantics]]
## Metadata
- `Tags:` [[Knowledge]] - [[Knowledge Work]] - [[Knowledge Economy]]
- `Author:` [[@Denise Bedford]]
- `Notable Authors:`
- `General Subject:` [[knowledge management]]
- `Specific Subject:` [[Knowledge Architecture]]
- `ISBN:` 978-0-367-21944-4
- `ISBN:` 978-0-367-21943-7
- `DOI:`
- `Publish Date:` 2020-12-30
- `Reviewed Date:` 2021-04-25
## Citation
```latex
@book{bedfordKnowledgeArchitecturesStructures2020,
title = {Knowledge Architectures: Structures and Semantics},
shorttitle = {Knowledge Architectures},
author = {Bedford, Denise},
year = {2020},
edition = {First},
publisher = {{Routledge Taylor \& Francis Ltd}},
address = {{New York City}},
abstract = {"Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support twenty-first century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on forty years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution, and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past twenty years, the book explains that end users now expect designs and behaviours that are much closer to the way they think, work and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design and search system architecture and engineering"--},
annotation = {ZSCC: 0000000},
file = {/Users/bryanjenks/Zotero/storage/MSZTLM4T/Bedford_2020_Knowledge architectures.pdf},
isbn = {978-0-367-21944-4 978-0-367-21943-7},
keywords = {📖️,architecture,knowledge}
}
```
## Notes:
### First Meeting: Architecting Knowledge
#### Link
https://util.brimstor.me/hedge/UjP3R3deSuW02wsEQlz0tQ?both
#### Agenda
| Topic | Person(s) | Mins. |
| ---------------------- | ---------- | ----- |
| Intro to Bookclub | Bri & Ryan | ~10m |
| General Discussion | Everyone! | ~10m |
| Chapter 1 Presentation | Bri | ~10m |
| General Discussion | Everyone! | ~10m |
| Chapter 2 Presentation | Ryan | ~10m |
| General Discussion | Everyone! | ~10m+ |
#### Introduction
#### Chapter 1
- Is the document the knowledge or is it the mind processing the information that is the knowledge.
##### Bedford's 16 principles about knowledge:
###### Costs:
- Knowledge is abundant, not scarce(1);therefore noncompetitive(5).
- Knowledge is an experience good(2) & a public good(4).
- But there are costs associated with getting it(6).
###### Traits
- Knowledge is open(8) & transparent(10).
- Knowledge is also extensible(3), collaborative(9), & interactive(11).
###### life & death
- Knowledge is a dynamic and continuously changing asset(14) with an infinite useful life(15).
- But embedded(13), therefore it is perishable and transitory(12).
###### Discussion: *(all points below paraphrased)*
- **Bri's Critiques:**
- High emphasis on "Western" understanding of knowledge disregarding indiginous (Hypercapitalist) perspectives/approaches
- Death by Lists
- **Daniel Borek:**
- "Knowledge is the state of the world"
- **Christian Fratta:**
- "I am not sure I could explain the authors differentiation between knowlege and information"
- **Lee Herman:**
- "Catalog of properties"
- **Avani Wildani:**
- (chat) — There is some confusion between “knowledge is always one-shot transient” and “permanent and always useful”, I agree.
- **Cat:**
- (chat) — One thing that I was considering was the way in which humans have depended on collective knowledge and cultural evolution for basic survival, and being confused by knowledge being both a public good and having free-rider problems (acc to the book at least) - if something is a public good, isn’t free-riding not an issue because it is (supposedly) openly accessible?
- **Nick Wolf:**
- "What was the first bie of knowledge information that was written down that did not need human mediation " and "You can't experience (know) a rollercoaster without actually riding it"
#### Chapter 2
- Topic is much more focused on Capital(tm)
- What is knowledge, really?
- What kinds of knowledge exist?
- (What does this mean for knowledge architectures and knowledge management?)
- Coffee!! ☕☕☕
##### 5 types of knowledge through "Latte art skills" ☕️
###### Human
- How to make the cappuccino (Skills)
- Whether you like a cappuccino over a cortado
###### Explicit
- Photo of your latest rosetta on the 'gram
- Grandmother's cappuccino recipe
###### Cultural
- Market appreciation of quality coffee & latte art
- Family values of coffee culture
###### Procedural
- Thinking about how to use latte art to show coffee competence at the cafe
###### Relational
- Exchanges of photos of latte art as a way of increasing the value of latte art in culture
- Learning to make cappuccinos with your grandmother
##### Critiques:
- Evidence?
- Overlap in the 5 defined categories
- "How is procedural not a form of Human knowledge"
- Pragmatics?
- Not satisfied with answers given
- "What does this mean for Knowledge Architecture and Knowledge Management"
- WIIFM (What's in it for me)
##### Accolades:
- Good framing
#### Discussion *(all points below paraphrased)* :
- **Oshyan Greene:**
- "Recording experiential knowledge"
- "Is there even a data structure to represent that, that could then be imported back into a brain interface"
- (Chat)"Relational" is interesting. Is that knowledge, or simply process around knowledge?
- **SkepticMystic:**
- Different characteristics of knowledge assets:
- Transferability
- Capturability
- Tangibility
- Each of these will have some overlap, and probably correlate with one another
- **Daniel Borek:**
- (chat) "Relational" is interesting. Is that knowledge, or simply process around knowledge?
- **Lee Herman:**
- this stage of the book is the 20 blind men touching the elephant metaphor
- **Ryan Murphy:**
- [Ackoff’s original essay on DIKW](https://faculty.ung.edu/kmelton/Documents/DataWisdom.pdf)
- **Mediapthic:**
- "Context as a driver of information density"
- **Nick Wolf:**
- "Context as a driver of information density"
- **Bri Watson:**
- Looking through my notes in obsidian and a prof mentioned the flow of DIKA before:
- **DIKA**: data -> information -> knowledge -> action
- "it's not about the factual correctness of the name, its about something to identify someone. 'Fuzzy details'"
- Talked about what knowledge/information/data was. Take the data point 17 degrees.
- Where is 17 degrees? Not much in oven, refreshing drink temp, bad news in arctic. 17 degrees Celsius in Vancouver = nice autumn day.
- **Nick Wolf:** And 17 degrees means a different temperature depending on your unit of measure.
- **Avani Wildani:**
- "Tangentially, there is an implicit assumption in both this and the previous chapter that data always adds information instead of noise that is bothering me." (chat)
- In transfer learning, a machine learning method of learning from “others”’s experience, there is an idea of ‘negative transfer’, where you actually learn things that hurt you because the experience doesn’t match.
### Second Meeting: Architecting Knowledge
#### Agenda
| Topic | Person(s) | Mins. |
|------------------------ |------------ |------- |
| Chapter 3&4 Presentation | Bri | ~15m |
| General Discussion | Everyone! | ~45m |
- **[Zoom Meeting Link](https://ubc.zoom.us/j/63461170210?pwd=ZjdiRGZrTlIyM1FGcDNjeWN0ZVZHUT09)**
- Meeting ID: 634 6117 0210
- Passcode: 850473
- **[Community Notes Document Link](https://util.brimstor.me/hedge/yVCH-g4hR56wm3iVDrfcLA)**
#### Chapter 3 - Knowledge architecture and design
&
#### Chapter 4 - Knowledge architecture reference model
- **ALL** the lists
- The knowledge architecture landscape doesnt work anymore.
- "drinking from a firehose" v.s. your neighborhood weekly newspaper
- The sheer volume of new input is now highly unmanageable
- are the "cake" layers mutually exclusive yet also interlinked?
- They affect each other and tie into each other but the graphic of them stacked may indicate a hierarchy but for this explanation they may be better suited towards a network graph with edges with grater width for dependence rather than a stacked layered pie chart
#### Discussion
- Ryan: Design Happens in Cycles
- Bri: *Design Ruins Everything* (Mike Montero) --comparing Architecture to knowledge architecture
- Discussion of the ['Death Ray Skyscraper'](https://www.businessinsider.com/death-ray-skyscraper-is-wreaking-havoc-on-london-for-a-few-totally-insane-reasons-2015-7)
- Ryan: Is there a similar example in knowledge arcitecture?
- Bryan: The "Feed" (social media feed, tech feed, news feed etc). The answer to complexity is not more complexity, we need more **simplicity**
- Ryan brought up Tiago Forte and how he built off of specific older models and ideas and built something new, unsure if Bedford is there or will get there
- Discussion around how having a "workflow" for specific things and how it can help assauge the overwheming nature of the feed
- Ryan: Can "Just in time manufacturing" be applied to knoweldge work?
- Another example: it doesn't make sense to grow rosemary from scratch just to make one meal—that would take years
- Bryan: You need a skillful and sharp approach when doing something specific like a phd or such
- Ryan: Talking about knowledge work and how he isn't as focused as we might suspect — we're all driven by short term proximate responsibilities but there should be some way of using lessons learned from one field or research and applying it to another
Have we learned anything from this book so far?
- Ryan: yes, seeing gaps, and places for contributions and places the field can be improved
- Bri: yes, Bedford is talking arou
- Bryan: Yes, learning aways about AGILE/SCRUM
### Third Second Meeting: Architecting Knowledge
#### Agenda
| Topic | Person(s) | Mins. |
|------------------------ |------------ |------- |
| Chapter 5&6 Presentation | Ryan | ~15m |
| General Discussion | Everyone! | ~45m |
- **[Zoom Meeting Link](https://ubc.zoom.us/j/63461170210?pwd=ZjdiRGZrTlIyM1FGcDNjeWN0ZVZHUT09)**
- Meeting ID: 634 6117 0210
- Passcode: 850473
- **[Community Notes Document Link](https://util.brimstor.me/hedge/ia2q_M35TBu5ojbFR0PkTw)**
#### Notes
- Getting closer to usability
##### Chapter 5 KNOWLEDGE ARCHITECTURE SEGMENTS
**Read this chapter as segemented, read it for the things that are the most interesting to you**
Two questions:
1. How does an organization interact with knowledge?
2. What are the functions that serve those interactions?
- The essential ~~segments~~ layers of K.A.
###### 1. KNOWLEDGE CONSUMABILITY LAYER
- Just because they exist doesn't mean they are available to create value wherever value is needed
- Tacit knowledge (unless you are working with someone who knows something...you don't have access to what is in their head):
- Available to the individual who holds it
- How available is tacit knowledge to others?
- How do we make tacit knowledge more widely available?
- Create a physical representation
- The challenge is to design mechanisms that allow individuals to explain and share their knowledge.
###### 2. KNOWLEDGE ACCESSIBILITY LAYER
- Just because knowledge assets are available does not mean they are accessible
- How do we find and discover the knowledge that is available (Search, Discovery, Indexing)
###### 3. KNOWLEDGE AVAILABILITY LAYER
###### Questions
The challenges face in designing for knowledge preservation and conservation are:
1. Maintaining the focus on the knowledge assets rather than the packaging
2. Acting for the long term, and
3. Ensuring that preservation and conservation are undertaken for **availability and access rather than lockdown and storage**
###### Discussion
*all points below paraphrased*
- LH: content is a loaded word.. think about how things are packaged? Look at knowledge content regardless of format and packaging...a very tricky concept
- BSJ: Chapter seems simlar to a SQL database. Q's of how to cut through noise...how do you pin down originality with a idea? how do you pin down originality with all of the iterations, copies, forgeries? (NFT's an interesting technology to apply to digital space to enforce a referenceable certificate of authenticity and ownership)
- RM: it feels like in the modern world, with all of the tech and we have available that this kind of loss shouldn't be anymore. We shouldn't see a library burned down and lose all this content but I'm being idealistic.
- BW: SSD (solid state drives) cannot be used in digital archiving as they will lose data to the air with lack of electrical current
- RM: Different concepts of seeking and discovering
- berrypicking:
- browsing: going through things in an indexing
- grazing and satisficing (combination of satisfaction and sufficing, "better to get it done than to have it perfect")
- LH: "Curating indexing" "indexing as a means of retreival" ...goes even further when you get into physical objects and, and metadata level access to things that you can't really fully digitize or that it's not practical to have in the object.
- Image tagging with Machine learning
- OCR (Optical Character Recognition)
- Full text search (could leverage AI)
- RM: We can only hold 5 things in our heads at time, and things get a little muddled when we have more than that
##### Chapter 6 KNOWLEDGE OBJECT MODELING
AKA: *What are the models of the knowledge assets you need available, accessible, and consumable?*
Searching for knowledge assets must support several activities and tasks, including.
1. Defining the sources that must be searchable;
2. Identifying and defining appropriate search capabilities,
3. Assessing current search capabilities against
4. Designing and architectures; appropriate index structures
5. Designing indexing updating and rebuilding practices; and
6. Designing search logging and feedback capabilities
- BSJ: Interative improvements to your system
- Giving diff attributes of the class different behaviors can lead to usability that can enhance consumption and and access.
- We can have a recipe in a cookbook that isn't OCRed or even photographed but one that is OCRed or typed out or photographeed is far more useful
- The question is "what are the assets in these different domains"
Mini Workshop!
0. Choose several knowledge assets to use in this exercise
1. Deconstruct or reverse engineer the knowledge asset
2. Construct the object model
3. Desk check the Object model against instances
4. Associate existing knowledge assets to Object models
5. Begin the Object model transformation process
The idea is to actually look at the kinds of knowledge that you using and the containers you're keeping your daily life in(?), and then deconstruct them and build out an object model to see how they're useful.
The idea would be to choose several knowledge assets, pic kout a couple of different things that maybe you use today or yesterday, and then deconstruct them in order to figure out what **IS** the actual asset at the center of the kernel. Ask yourself "what class of object is this, what are the kinds of attributes or specifications or behaviors that these assets might have, how do they relate to others?" Then find a couple of examples of what you think that might be, and see if it fits—by doing this you might find insights in enhancing the availability access and consume ability of your, your knowledge and your own.
- Bri can make 🍞️ with their eyes closed right after waking up. Like a crazy person 👀️
## Summary of key points:
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## Context:
==(How this article relates to other work in the field; how it ties in with key issues and findings by others, including yourself)==
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## Significance:
==(to the field; in relation to your own work)==
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## Important Figures and/or Tables:
==(brief description; page number)==
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## Cited References
==to follow up on (cite those obviously related to your topic AND any papers frequently cited by others because those works may well prove to be essential as you develop your own work):==
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## Other Comments:
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