Next-Gen E-Learning Ideas

Knowledge Base with 3D Graphical Environment for Learning, Distributed Collaboration and Critical Thinking

Jan-2010 MacArthur Foundation Proposal +

Supporting Mockup Diagrams + More...

Richard Creamer 2to32minus1@gmail. com

Copyright © 2010-2013 Richard Creamer

All Rights Reserved

1 Copyright © Richard Creamer 2010 - 2013 – All Rights Reserved

Why I’m publishing this slide deck

I am currently in the middle of a job search (have any openings?) and want to place the ideas in this slide deck in the public domain prior to accepting a new position so that any IP contained herein is ‘clean’ as well as in the hope that I can find developers who would like to help me form an open source project to evolve and implement the ideas presented.

I believe that with the right tweaks, these ideas can form the bulk of an ideal MOOC platform of the future.

Also, this isn’t just about online/MOOC Education - I feel that there are also many potential applications for these ideas in both traditional Education as well as the Commercial sector.

By the way, most of these ideas were previously publicly published on my personal website in January, 2010 and remained online for about two years as an unofficial supplement to a 300-word-limit proposal I submitted to a MacArthur Foundation RFP in January, 2010 with a ‘Reinvent Learning’ theme. (This proposal is included in this slide deck.)

The bulk of the brainstorming which went into the mockup diagrams was done in about a 2-week period in January-2010.

Richard Creamer

October 22, 2013

PS: This deck was necessarily assembled in a hurry and as a result, is incomplete, has errors, and some redundancies.

PPS: Some of the foundational ideas are derived from the W3C’s Semantic Web standards.

PPPS: I can remove the copyright notices at any time - they are included now only as a preliminary precaution.


- Begin Intro Slides -


Preface Overview

• There are many important problems in Education.

• Many of these problems, perhaps the most important problems, remain unrecognized or ignored.

• Hint: There are much more effective and expedient ways to present the material in many textbooks and videos.

• This under-development slide deck presents ideas which I hope uniquely integrate the following:

• Knowledge representation and carefully-designed graphical visualization

• Learning

• Long-term memory retention of learned material

• Collaboration and discourse

• Computational argumentation

• More

• A large node-edge graph and the integrated use of novel metadata coupled with new UI components, underlie the presented approach.

• Most of the UIs for this project are either graphical, or new forms of instrumented, multi-layer hypermedia.

• Important: The architecture described in this deck enables, via metadata, any form of external information, URI, highly-specialized learning apps, and even 3D immersive environments to be associated with, and launched from, any node in the graph.

• Most of these ideas were developed in Jan-2010 while developing a proposal for a MacArthur Foundation RFP.

• This technology has many important applications beyond Education.

Goals

• Understanding: Provide technology which ensures a deep, cohesive, cross-disciplinary understanding of topic materials.

• Difficult Learners: Rapidly resolve students’ confusion on any topic, statement, problem, equation, symbol, etc.

• Time Efficiency: Enable substantially more time-efficient learning learn more in less time learn more

• Retained Knowledge: Solve the Forgetting Curve problem and develop efficient ways to graphically review, refresh, and maintain all salient knowledge from current and prior courses throughout one’s education and career.

• Collaboration: Greatly improve upon today’s poorly-indexed, disorganized, repetitive, non-scalable discussion thread models.

• Non-Technical Subjects: Develop technology allowing many non-technical subjects, such as History, to be effectively taught and tested/graded in online environments.

• UI/UX Presentation Components: Develop new, more powerful, UI components which can be instrumented to support new and existing types of hypermedia (in multiple layers).

• Community Contribution: Enable community voting on, and contributions to, problem sets, curriculum, and explanatory materials. 4 Copyright © Richard Creamer 2010 - 2013 – All Rights Reserved

http://en.wikipedia.org/wiki/Forgetting_curve

Projected Benefits

Projected/Anticipated Benefits*

• Double the amount of knowledge taught and assimilated in typical online (and traditional) courses.

• Deepen the level of students' understanding of course materials, concepts, how they fit together, and are applied.

• Dramatically reduce the time often spent by students resolving their confusion on difficult concepts such as mathematical formula notation and conventions.

• Effectively solve the 'forgetting curve' problem. Initial thoughts:

• Create a UI component which visualizes a complete, highly-minified sub-graph visualizing a complete subject in a single view where the nodes are just tiny dots

• Color-code portions of this course-holistic sub-graph view according to a student’s mastery level of each course vicinity.

• Employ a scheduler to queue/revisit each vicinity and test a student’s level of mastery until a high level of recall has been demonstrated the last n times.

• Perhaps on an annual basis, re-activate the above steps to sample and refresh accordingly, course knowledge and keep it from fading over time.

• This same UI component could also be used by students to review/prepare for tests and final exams.

• Develop more efficient and precise curriculum authoring and curation tools.

• Develop more effective presentation UX paradigms.

• Develop a common foundational data model on which to base all:

• Knowledge

• Curriculum

• Metadata:

• Statement provenance

• Interactive visualization component UX behavior

• Content curation

• And more

• Problem sets and problem solutions

• Collaboration/discourse/voting

• Embed critical thinking, statement provenance, points of contention, and precise, scalable, distributed collaboration into MOOC platforms.

• Integration of arbitrary, external topic-specific apps so that the best instructional tools can be utilized at any point.

• This project can be implemented in an evolutionary manner.

• A coherent, phased project plan could be designed to gradually incorporate various aspects of this project, so this path need not be ‘disruptive.’

• And more...

*These are big claims, but my 20+ years of developing software and novel, effective user interfaces suggests to me that they are, in fact, achievable.


http://en.wikipedia.org/wiki/Forgetting_curve

Introduction

• In the long term, express all knowledge as a node-edge graph using a 4-tuple graph data model [ subject, predicate, object, uuid ] called Quads.

• This graph will include not only knowledge and concept-related data, but also novel types of useful metadata including:

• Provenance, UX behavior, permissions, vote tallies, links to related materials, and the expansion predicate vocabularies available to a node/edge.

• Typically, only one or two small, interactive salient subsets of this graph will be viewable at a once, usually via special-purpose knowledge viewers.

• Even though a large node-edge graph underlies the knowledge, over-cluttered conventional visualizations of this graph will never be seen by students.

• Courses will be defined as paths through this knowledge graph and pause points (‘vicinities’) corresponding to curriculum chapters/sections/sidebars.

• Each vicinity may be viewed at user-controllable level-of-detail settings: Low, Medium, and High, and branches may be interactively expanded/collapsed.

• Vicinities will be rendered differently for different grade levels (driven by metadata). E.g., a 5th grader may see factoring differently than a 10th grader.

• This large underlying graph will drive multiple types of higher-level, interactive graphical UI components. These multi-layer UI components include:

• Slide Deck Viewer

• An advanced slide deck viewer which can be ‘instrumented’ to link to arbitrary graph vicinities, external hypermedia, animations, and more

• Much of the narration and ‘scribbling’ in video lectures could be built into such a hypermedia component, again, via underlying graph metadata.

• Knowledge Graph Viewers

• Several highly interactive knowledge graph viewers which allows users to efficiently control the amount and type of information displayed as well as to explore ad hoc branches in the graph as-needed, for example, in order to learn more about a side topic often found in a different textbook.

• Unlike traditional graph visualization, these viewers:

• Will not overwhelm users with too much information - too many nodes and crossing edges

• Will not simply display ‘pixels’ but rather, each node, edge, and node ‘grouping element’ will be interactive objects

• Both 2D and 3D (including immersive 3D environment) viewers are anticipated.

• Computer Screen Viewer (and Video Viewer)

• A tool which allows a recording of a computer’s screen to be displayed, but which also supports interactive (id, dx, dy, dt) hot spots so that students can pause the viewer and overlay other viewers in order to explore supplementary/explanatory materials related to the in-view screen as well as make notes and sharable bookmarks.

• Argument Diagram Viewer

• An argument diagram viewer visually groups related graph statements (Quads) together to form premises which may then be linked into a formal, complete, discussion- and voting-enabled argument. All statements, premises (and their provenance) may be viewed, voted on, have adjacent vote tallies, and in general, be precisely critiqued in a collaborative environment.

• Distributed Collaboration Environment

• This component is similar to the Argument Diagram Viewer except that ad hoc sub-graphs, not necessarily part of a formal argument, may be viewed, discussed, and voted on (at the individual Quad level).

• Storyboard Viewer

• An advanced storyboard component will be developed which can be used to visually represent story-like subjects such as History which have timelines, scenes, actors, relationships and more. Storyboards might also offer a good way to portray temporally-varying data and processes such as chemical, political, and assembly/repair processes.

• Tools

• Finally, efficient content authoring and curation tools will be developed. This would include revisioning, metadata authoring, grading, etc.

Note: I feel this direction has great potential and that a phased, evolutionary approach to implementing these ideas both in MOOCs and classrooms is possible.


Comments

Time Efficiency

• In today’s multi-disciplinary, lifelong learning world, both students and adults need to learn more skills/courses and even new careers.

• But we still need to have a life and spend time with our children!

Therefore, we need to reduce the time needed to learn new subjects.

• Too much of students’ time is unnecessarily wasted (a traditionally unrecognized area of potential improvement):

• Text books are too verbose and disconnected (students must take lengthy tangents to learn related topics in other books).

• Many university texts almost appear to have intentionally been made difficult to read.

• Videos take too long to view, have low information density, and are just ‘pixels’ and audio narrative - not interactive, multi-layer hypermedia, but they do have their place. (Some people learn best from different presentation types than others.)

• Many MOOC courses give difficult assignments without enough preparatory, illustrative examples. (Compare w/any Calculus book.)

• For the most part, MOOC curriculum lecture slides rarely take advantage of even ordinary hypermedia such as lecturer pen scribbling, let alone the new, advanced hypermedia which would be possible with new presentation technologies. This:

• Adds to the time it takes a student to understand a slide

• Does not provide the deeper understanding and linkage to other related materials which advance hypermedia could provide

• MOOC forums have very little organization and are poorly indexed making it difficult for students to navigate and find answers to their questions or find threads they have previously visited.

• Student collaboration on MOOCs, based primarily upon forums, is cumbersome and slow because it is linear, unstructured text.

Retained Knowledge

• Textbooks contain a lot of material. If each page contains 10 units of knowledge and there are 500 pages in the book, then 5,000 units of knowledge are contained in the book. (A hypothetical, illustrative example which probably underestimates the fact count by 5x-10x.)

• Think about what your brain actually retains after completing a course in, say, Algebra. Do you remember:

• Every word on every page? No, of course not.

• 5,000 things? No, of course not.

• What your brain does store is a small collection of concepts, techniques, and knowledge of when and how to apply those techniques.

• And even for engineers who use Algebra throughout their careers, this concise subset of retained knowledge is quite sufficient!

• The brain distills those 500 pages of text into a small, concise subset of relevant material, logically organized as a network.

This suggests that it may be possible to condense and formulate curriculum into a form more akin to how it is stored in the brain.


Comments

Knowledge Representation

• The W3C’s Semantic Web has a fundamental data type called an RDF Triple: [subject, predicate, object], for example: (see slide 18 for more details)

• [ rick, WeightInKg, 88.1826 ] (after his mid-day snack;-)

• The above RDF statement states that ‘rick’ weighs 88 Kg.

• ‘rick’ is the subject, ‘WeightInKg’ is the predicate (analogous to an attribute), and 88.1826 is the object (analogous to an attribute value).

• ‘WeightInKg’ is the predicate and is similar to an attribute/property.

• The three elements in actual RDF triples are URIs (like URLs) - globally unique IDs (‘object’ can also be a string literal, also see slide 18).

• Since each tuple element is globally unique, ambiguity can be completely avoided. Think about how many different meanings exist for ‘thread.’

• An RDF triple is a ‘statement’ and collections of triples can be visualized as a node-edge graph/diagram.

• Except for the smallest graphs, simple/naive visualization of such a graph is usually not effective.

• Sometimes, you want to know information related to a statement called ‘metadata’ (see Provenance below).

• To do this, you need to write a ‘statement about a statement’ formally called ‘reification.’ (also see slide 27)

• With reification, anyone can state anything about anything. This is a very powerful capability supporting explanations, contention, uncertainty, etc.

• The W3C provides a way to do reification, but a perhaps simpler way is to create 4-tuples (Quads): [ subject, predicate, object, uuid ].

• With this simple foundational data structure, arbitrarily complex node-edge graphs may be defined (networks).

• This graph structure can encode any type of information: curriculum, problem sets, solution sets, multimedia, arguments, permissions, etc.

• Not only can knowledge be represented in such a graph, but also any type of associated metadata (data about the data):

• Provenance

• Who or which entity made the statement?

• For what moment or time span is this statement valid (e.g., temporal data such as city population or temperature)?

• If the statement was a data measurement in a scientific experiment, what was the experiment ID, date-time, equipment, and uncertainty?

• If the statement was made by a politician, what special interests groups which benefit from this statement contributed to this politician’s campaign?

• If the statement was someone’s opinion/vote in an online student forum, what were the vote tallies? On which statements?

• Contention - Show all perspectives on issues

• Clearly/graphically display any individuals or groups who disagree with any statement.

• With which specific statements do they disagree, and on what basis (links to additional statements and their provenance)?

• Visualization - Graphical knowledge graph browser visualization/UX hints/behavior (explained later)

• More - Additional metadata can be specified such as geolocation, associated statements (as in argument diagrams).

• So, knowledge, its metadata, its visualization, interrelationships between the data, permissions for content curation, collaboration, voting, external Web links, problem set aggregation, problem solutions, solution explanations, and more can all be integrated into a single data model and network.


- End Intro Slides -


Begin January-2010 MacArthur Foundation Proposal

Theme: ‘Reinvent Learning’

(Converted to 5-slide slide deck)


Knowledge Base with 3D Graphical Environment for Learning, Distributed

Collaboration and Critical Thinking

Richard Creamer [email protected]

Copyright © Richard Creamer 2010 - All Rights Reserved


Brief Project Description

Perform the R&D necessary to create a unique educational knowledge base enabling students, world-wide, to graphically explore most subjects, grades 4-16. The included 3D graphical environment will also enable distributed student groups to collaboratively view, compose, discuss, critique, and vote on: topics, arguments and premises, ideas and thought processes.


Primary Goals

• Graphical Knowledge Exploration: Provide all children with a free, multilingual, complementary/supplementary educational knowledge repository enabling them to view and explore knowledge in the form of intuitive graphical diagrams (enhanced mathematical node-edge directed graphs). Graph nodes may contain text, charts, multimedia, HTML documents, etc. as well as virtual 3D environments and other graphs/diagrams. Students will be able to “jump into” many types of node content. Unlimited levels of supplementary/explanatory information such as Why, ExplainFurther, ExplainDifferently, BasedUpon, and RealWorldUses will be able to be associated with facts/statements and interactively navigated.

• Collaborative Critical Thinking: Enable distributed student groups to collaboratively discuss, critique, and vote on: topics, arguments and premises, ideas and thought processes--all from within the 3D graphical environment. Argument premises will be clearly linked to their supportive facts in the same view. This will enable students to critically discuss/chat and vote on the validity and merit of any fact or premise. As a result, students will learn to judge the logical strength of arguments while collaborating on a variety of socially-relevant topics such as Global Warming.


Details • Data Model: For many reasons, the data model for this project will likely be based

on the W3C Semantic Web’s RDF "triple" format.

• Knowledge Base Content: The goal is to motivate scholars from around the world to contribute to the knowledge base’s content, in parallel.

• Rationale for Graphical Visualization:

• Clear, concise, relational depiction of knowledge, its categorization, and its provenance.

• Efficient, selective navigation and display of information.

• Ability to avoid disruptive context switches when browsing multiple side topics.

• Graphical knowledge representation has been shown to improve student knowledge retention.

• Provides skeletal framework/context for organizing/assimilating knowledge gained in coursework.

• Expertise: Multiple expert academics/consultants will be engaged during this project.

• Example preliminary diagrams: tinyurl.com/DMLExamples (Note: this link no longer valid)


http://tinyurl.com/DMLExamples

http://tinyurl.com/DMLExamples

Knowledge Base with 3D Graphical Environment for Learning, Distributed

Collaboration and Critical Thinking


Copyright © Richard Creamer 2010 - All Rights Reserved


End January-2010 MacArthur Foundation Proposal

Note: Since this proposal was submitted, I believe that grades K-3 could also partially benefit from this approach.


Begin Preliminary Illustrative Diagram Screenshots and Explanations


Preface - A hastily-prepared primer for understanding the diagrams to follow -

Briefly: • First, this document is very under-developed and preliminary. Much refinement, evolution, and elaboration on benefits and motivations has yet to be developed. • What is not included are more recent ideas such as:

• The utility for Storyboard applications (similar to how movies are initially planned) for converting subjects such as History into a graphical, interactive, electronic format. • Various ways in which traditional slide decks may be augmented and ‘instrumented’ to become a much more effective form of ‘hypermedia’.

• All knowledge can be represented as a large, single network of statements, which in turn can be modeled as a node-edge graph. • Courses are simply paths through this network graph with stopping points along the way for viewing the local vicinity. • These local vicinities could, in general, represent a chapter/section/sidebar in a traditional text book. • Unlike a text book, if a math symbol or concept is not explained, the graph network will always include links/branches to other vicinities where these things are defined, recursively, if necessary. • Ultimately, a child may navigate all the way back to fundamental axioms of a Greek mathematician when exploring a side topic/area of confusion. • In most of the following static screenshot mockups, please realize that the amount of information in view at any time will be completely controlled by the viewer/student. The reader of this slide deck may feel these diagrams are too cluttered, but that is only because they have been substantially ‘expanded’ to illustratively show what branches may be available to be viewed. • I anticipate offering students the ability to set the level of detail in ‘vicinities’ to Low, Medium, and High, and allow them to toggle back-and-forth as desired. • To make a graphical learning experience as effective as possible, I have/will develop several advanced User Experience techniques to make the navigation of this graph very intuitive and efficient - much more efficient than current graph visualization tools. • The fact that I use a formal graph data model (RDF triple/quad) means that any statement can be ‘decorated’ with additional RDF statements/information. Here are but a few useful, illustrative ‘predicates’:

• ExplainFurther, ExplainDifferently, RealWorldUses (these are self-explanatory, may have cardinality > 1, and may form arbitrarily long chains) • Provenance: Who made this statement • Validity: Who agrees that this statement is valid • ProbabilisticValidity: What is the probability that a statement is valid/factual (typically used for scientific or imperfect observations) • Contention: Who disagrees with a statement, and what are their reasons • GeoLocation: A geographical point or area associated with a statement or statement element • VoteTally: Students will be able to collaboratively vote on any statement and these results can be displayed in the graphical browser • Temporal History: Some knowledge/facts are not static - they change with time. Hence, graphical ‘time slider’ controls will be provided so that

students can view information at different times. For example, a city’s population could be viewed at any time in the past or future (projected). • UX: Statements and groups thereof can be decorated with metadata hints for how the actual graphical knowledge browser should render the

statement(s) and what operations they support (such as ‘jump into,’ available expansion predicate vocabularies, and display time slider).

I hope this is enough to permit readers to better understand what follows and some of the motivation for why things were designed this way.


Subject Object

Introduction to RDF Triples*

One of the simplest spoken language sentence structures is the pattern: Subject + Predicate + Object.

For example, in the sentence “Jim lives in Seattle.”, we have:

• Subject = Jim • Predicate = lives in • Object = Seattle

This simple sentence structure is the basis for the unit of information used in the W3C’s Semantic Web Resource Description Framework (RDF). Any and all complex information can be decomposed into this basic, atomic format called an RDF “triple.”

Often, a triple is visualized as a mathematical directed graph:

Or, for the above example: Jim Seattle

The above graph is a bit simplified. In the Semantic Web, the elements of a triple are semantically precise and unique strings** (URIs to be specific). For example, “Jim” might actually be defined as http://bigonto.org/earth/us/humans/093a5e21-988e-449f-b89d-55b09d1c2b3b. Similarly, the predicate “lives in” might be defined as http://world.eduweb.org/predicates/human/geo/lives-in. Fortunately, non-unique human-friendly labels may be associated with RDF resources to make graphs more readable. The basic idea is that globally-unique URIs can be assigned to concepts, such as “Jim” or “lives in.” This enables unambiguous statements to be asserted that refer to specific concepts using specific (globally-unique) predicates. Thus, using semantically-precise triples, intricate networks of semantically precise statements can be created to richly describe any area of knowledge. Due to the inherent tree structure of URIs, RDF triple elements are often derived from nodes in taxonomic classification trees. Benefits resulting from the selection of RDF triples as the basic unit of information for the educational knowledge base include:

• Automatic addressability and incorporation of everything on the Internet • Intuitive visual/graphical representation of knowledge and information • Unrestricted decoration of knowledge to facilitate learning (e.g., predicates such as Why or ExplainDifferently) • Ability to represent and adapt to any information regardless of its structural characteristics (unlike DBMS schemas) • Basic multi-lingual support due to RDF’s support for language tags (“Biology”@en vs. “Biologie”@fr) • By using language tags and very brief text in graph nodes, translation to any language becomes much simpler.

Predicate lives in

* Note: In this project, ‘Quads’, not Triples, are used, where a 4th tuple element (uuid) is added to support efficient reification (statement about a statement). ** The object element may be either a URI or a string literal such as “98.6 F”.


http://www.w3.org/TR/rdf-concepts/

http://www.isi.edu/in-notes/rfc2396.txt

http://earth.us.humans/093a5e21-988e-449f-b89d-55b09d1c2b3b









http://world.eduweb.predicates/human/geo/lives-in



First Grade

Example: Browsing First Grade Curriculum (extremely preliminary) (This is not what a child would see - this design work is under construction.)

Subject[ ]

Numbers

Alphabet

Arithmetic

Reading

Spelling

Telling Time

Letter Sounds

Upper-Case

Lower-Case

Handwriting Lessons[ ]

Hours

Minutes

Hours & Minutes

Lessons[ ]

Lessons[ ]

Lessons[ ]

[ 1 ]

Category

Category

Category

Category

Category

Category

[ 2 ]

...

...

...

...

...

Clicking on this node launches an external, custom, highly-specialized

time -telling practice application

(Nodes can contain text, URLs,

HTML, applications,

multimedia, etc.)


In general, Predicates will be blue.

Predicates corresponding to a collection of statements (a ‘bag’) will sometimes be displayed as a

node with [ ] brackets.

Example: Astronomy/Solar System Browsing Session (simplified, intentionally incomplete, under-construction, very preliminary)

The Sun

Star

is-a

majorPlanet []

meanDiameter 1,390,000 km

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

The Earth

is-a

Major Planet

The Moon moon

meanDiameter

12,742 km

is-a Moon

meanDiameter

384,403 km

149,600,000 km

meanOrbitalRadius

3,474 km

meanOrbitalRadius

“An astronomical body that radiates energy resulting from sustained, internal thermonuclear reactions” @en

Astronomical Body

is-a

definition

“A naturally-occurring, gravitationally bound aggregation of matter located in space“@en

definition

“An astronomical body orbiting a star, or n-ary star system, which is not itself a star, has sufficient mass to have a nearly round shape, and has cleared the neighborhood around its orbit” @en

definition

minorPlanet []

“An astronomical body orbiting a star, or n-ary star system, which is not itself a star and has sufficient mass to have a nearly round shape” @en

definition [1]

[2]

...

Pluto Minor Planet

is-a

In all diagrams, students interactively collapse and expand

the graph branches/nodes to quickly view just the content of interest.

[Tabular summary of selected

planetary data]

planetarySummary


Please note the use of @en tags - using language tags will make

translation of graph data much simpler than translating entire

textbooks.

Global Warming – Synopsis X

Global Warming – Synopsis

Earth – Temperature Increasing

X

Open in new panel...

Caused By...

Basis...

Effects...


Contention...

Interactive hovering and node expansion user session...

Mouse hover popup displays available predicates

(Optionally, user could first select desired predicate vocabulary)

Distributed Collaboration and Decision Making (group)

User Actions

Example: Interactive browsing a topic with distributed group voting and collaboration (very preliminary)

Tally nodes could be linked to interactive chat

session view so voters could debate premise.

Global Warming – Synopsis

Humans – Generate CO2


Earth – Atmosphere.CO2 Increasing

Caused By

Humans .[ Factories, Home Heating ]

Caused By

Humans.Power Plants

Humans.Major Transportation

Source [] (weighted set)

Vote Tally Voting Data

84

3

1

Agree

Disagree

Unsure Vote Agree

Vote Disagree

Voting Action

Voting Action

Humans .[ Cars , Trucks ]

33%

33%

12%

22%

Popup GUI Controller

umich.edu/~gs265/society/greenhouse.htm Ref

X

Temporal Data (Displayed information interactively changes in

real-time based on selected year via slider)

Scope of slider(s) could encompass entire graph or

subset

Note: RDF triples do not

necessarily have to be rendered

as a distinct node-edge-

node.

1900 1950 2000 2050 2100

Year: 2000

Humans – Engage In Deforestation

Burning – Produces CO2 Trees – Convert CO2

Caused By

Harvesting – Reduces Tree Population

Type []

Relevance

Burning – Reduces Tree Population

Relevance

Voting...


Global Warming

Projected Effects

Example of Social/Scientific Topic RDF Graph (extremely preliminary) Purpose: Show that graphs/diagrams can be very useful vs. narrative text/HTML

IPCC

Major Sources

China

US

Coal Burning

Oil Burning

Deforestation

Increase in global temperatures primarily caused by increases in

atmospheric CO2 levels arising from multiple human activities.

Set [ ]

(2100) 3.2° F surface temperature rise

7.8” ocean level rise Best Case

Intermediate

Worst Case

(2100) 5.0 ° F surface temperature rise

31.1” ocean level rise

(2100) 6.48 ° F surface temperature rise

54.3” ocean level rise

Country Industries [ ]

Electric Cars

Improved Energy

Efficiency

CFL Lights

4X > efficiency vs. incandescent

lighting

Disadvantage Advantage

Lighting

LED Lights

Higher initial cost, more R&D needed

Safe, 10X > efficiency vs. incandescent

lighting


Increased probability of toddler neurodevelopmental diseases

(autism, Down syndrome)

Incandescent

Possibly Unsafe: Mercury is released into homes and environment, high cost

Relevance

Asserted By

Synopsis

...

Basis

Solutions

Technology Technology

Relevance

Current autism rate in U.S. alone > 29,000

children per year

Validity of research concluding released

mercury levels are safe is currently disputed.

Contention

Type Type Type

Energy Inefficient


Safe

Category Category

Sources

Could easily be line graphs depending on visualization

metadata Related To Climate

Change

Greenhouse Effect

Known As

Solutions

Global CO2 Reform Policies

Targets

1900 1950 2000 2050 2100

Year: 2100

Set [ ]


An example of a statement ‘grouping element’

Consumption of Fossil Fuel

Should Decrease

C

Global Warming

Gradual increase in Atmospheric CO2

Caused By

Observed increase in global surface temperature

Defined As

Human Activity

Caused By

Graph

Deforestation Home Heating

Factories

Cars, Trucks

Major Transportation

Power Plants

Arctic Ice Melt

1 Meter Ocean Rise by 2100

Species Extinction

Major Coastline Recession

10% Humans Lose Housing by 2100

Temperature Rise > 10 °F

Projected Effect [] *

40+ Scientific Societies

Validity Endorsed By

World

Fossil Fuel Consumption

Type []

D

B

E

F

A

Solution []

Infrared Light Absorbed By Re-Emits Infrared Light Radiates Sunlight Earth.Surface Warms

Earth.Surface To

Earth.Surface Warms

Global Warming

Contributes To A B

C

F

C D

G

E

G

Argument: World should decrease its consumption of fossil fuel

Example Knowledge Graph - Argument Graph Hybrid (very preliminary)

*Some illustrative statements are approximations

Atmosphere.CO2

Graph should be read as: • Sunlight warms Earth’s surface • Earth’s surface radiates infrared light • The infrared light is absorbed by the atmosphere’s CO2

• The atmosphere’s CO2 re-emits the infrared light • ...to the Earth’s surface

• ...which warms the Earth’s surface • ...which contributes to Global Warming

Type []

Note: At this very early stage, it is thought that the above type of

argument diagram will support in-place expand/collapse of nodes to

permit exploration of hidden, hierarchically-contained sub-

argument elements, their premises, and their underlying facts and associated metadata (voting,

uncertainty, etc.)

ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land.90S.90N.df_1901-2000mean.dat

Ref

Distributed student groups would be able to vote on any fact statement and cite other facts, arguments or

argument premises, as the basis for their vote. Distributed students could then discuss their votes and the underlying premises in a virtual group environment. Essentially all nodes have further expansion predicates available to ultimately get to the root validity, pedigree,

basis, or origin of the fact/premise under discussion/referenced. This slide also illustrates how the

(many) corresponding pages of Wikipedia’s unstructured text

may be compressed into a single diagram which allows ‘bigger

picture’ structure and interrelationships to be

displayed.







84

3

1

Agree

Disagree

Unsure

Vote Agree

Vote Disagree

Voting Action

Voting Action

Earth.Temperature Graph

Increasing Trend

Human.Activity Caused By

IPCC

40 Scientific Societies

Agrees With

Agrees With

Disagrees With

Trend

Natural Geologic Fluctuation

Increasing

Caused By

Agrees With

Undecided About


84

3

1

Agree

Disagree

Unsure

Vote Agree

Vote Disagree

Voting Action

Voting Action

Earth.Temperature Graph

Increasing Trend


IPCC

40 Scientific Societies

Agrees With

Agrees With

Disagrees With

- Alternate Idea - (Graphical Thought Bubbles)

?

Trend

Human.Activity

Increasing

Caused By

User Actions

User Actions

Trend

Natural Geologic Fluctuation

Increasing

Caused By


Visualization of Rationale for Voting w/Discussion (very preliminary) Major benefits: 1) specificity (precise statement discussed), and 2) aggregation of many equivalent opinions (scalability)

Chat Group: G&G 120B

Ian: Mike, I disagree—I think GW is the result of natural environmental fluctations. See my thought bubble. Mike: Ian, whether or not that’s the case, don’t you think we should be reducing our carbon emissions? The polar ice is melting and the sea levels are going to rise regardless of whether GW is caused by humans or due to natural causes. Ian: Mike, you have a point, the cause is unimportant – we need to take action, and now.

X

Ian X

Mike X

Distributed student groups would be able to vote on any fact statement and cite other facts, arguments or

argument premises, as the basis for their vote. Distributed students could then discuss their votes and the underlying premises in a virtual group environment. Essentially all nodes have further expansion predicates available to ultimately get to the root validity, pedigree,

basis, or origin of the fact/premise under discussion/referenced.

Note: Student name labels in thought

bubbles correspond to names and colors in

chat window.


RDF Graph for Example Algebra Problem (very preliminary)

Step 1

2x – 3 = 5 Solve

2x – 3 + 3 = 5 + 3

2x = 8

Add 3 to both sides Why

Algebraic equations are solved by manipulating the equation until the variable, x, is on one side of the equal sign while the numeric values are placed on the opposite side. This is done by performing

operations, one at a time, on both sides of the equal sign so that

equality is preserved. By doing this step-by-step, one gradually simplifies the equation until the last operation yields the answer.

Explain Further

Allowable Operations

It is illegal to divide by

zero.

Note: Advanced mouse hovering techniques will be used to make navigation and expand/collapse

of graph nodes efficient and intuitive.

Solution

Problem

Step 2

Solution 1

Steps

2x – 3 = 5

To move the 3 to the opposite

side of equal sign.

To solve Algebra problems, one needs to get x on one side of the equal sign by

itself.

Why

Step Expansion Labels: Operation Before During After

View Options

2x / 2 = 8 / 2

x = 4

Divide both sides by 2.

Operation

After

During

2x = 8

Before

x = 4

Set [ ]

Answer

+

-

x

÷

Raise to Power

Logarithm

Operation

After

During

Before

Exception

It is illegal to take square

root of negative number.

Exception

...

Author

Control Graph Visualization This, for example, would allow

a user to see only During predicates for steps, if desired.

This shows the result of a user interacting with and exploring the problem/graph by successively

expanding desired predicates. This verbose detail (and more) would be available if the user elects to

display it.


Solution 2x – 3 = 5 Begin

2x – 3 + 3 = 5 + 3

2x = 8

2x / 2 = 8 / 2

x = 4

Step 1 Add 3 to both sides.

Operation

As long as you do the same operation to both sides of an

equation, both sides will remain equal.

Explain Step

Algebraic equations are solved by manipulating the equation until the variable, x, is on one side of the equal sign while the numeric values are placed on the opposite side. This is done by performing

operations, one at a time, on both sides of the equal sign. By doing this step-by-step, you gradually simplify the equation until the last operation yields the answer.

Why

Step 1 Result

Step 2 Result

Step 2

+, -, /, x, raise to power, logarithm Valid Operations

Divide both sides by 2. Operation

Explain

Why

Expand…

Expand…

It is illegal to divide by zero.

It is illegal to take the square root of a negative

number.

Exception

Exception

Note: Hovering the cursor over a predicate

will show a popup Collapse… button.

Older Example of Previous Algebra Problem


Subject Object Predicate

Domain [] Range[]

Type[]

[0] [1] [2]

type1 type2 type3

[0]

[1]

Type[]

[0] [1]

type5 type6

type4

[0]

vocabulary1

Examples: Fetus, Infant, Child, Human,

Mammal

Polymorphic Type uuids (Allow Polymorphic Queries/Patterns)

MemberOfVocabulary

vocabulary2 Associated Predicate

Vocabularies[]

vocabulary3

[0]

[1]

[2]

[0]

[1]

…

Elements[]

Subject Object Predicate

Single, logical data structure type

•Subjects can be associated with zero or more types. •Subjects (and Types) can be associated with zero or more predicate vocabularies. •Predicate vocabularies allow filtered graphical expansion of graphs and easier query formulation GUIs.

Predicate[] Notation for displaying

predicates which denote collections of related objects

Subject Object Predicate Object

Predicate Metadata/reification:

Statement about Statement aka: Composition of Subject

(All metadata are triples as well)

( Composed Subject)

[0] Object Subject

(statement ) uuid

rdf:statement rdf:type

Unique Identifiers (uuids) enable metadata

(This is how data will tentatively

be stored “under the hood.”)

subject uuid rdf:subject

predicate uuid rdf:predicate

object uuid or value

rdf:object

(statement ) uuid1 0.27 x:Uncertainty

Example metadata statements describe statement

x:MeasurementTime

Vocabulary Definition: A group of related predicates.

1240463339800

Preliminary Thoughts on Graph Data & Metadata Model

x:AssertedBy NOAA


Example Astronomy RDF Ontology (with 3 instances: Sun, Earth, and Moon)

(simplified, intentionally incomplete, under-construction, very preliminary)

Type (Class) Definitions (RDF Triples) // Type: Astronomical Body kb.astro.o:AstronomicalBody, rdf:type, rdfs:Class kb.astro.o:AstronomicalBody, rdfs:label, “Astronomical Body” @en kb.astro.o:AstronomicalBody, kb.gen:definition, “A naturally-occurring, gravitationally bound aggregation of matter located in space“@en // Type: Star extends Astronomical Body kb.astro.o:Star, rdf:type, rdfs:Class kb.astro.o:Star, rdfs:subClassOf, kb.astro.o:AstronomicalBody kb.astro.o:Star, rdfs:label, “Star” @en kb.astro.o:Star, kb.gen:definition, “An astronomical body that radiates energy resulting from sustained, internal thermonuclear reactions” @en // Type: Major Planet extends Astronomical Body kb.astro.o:MajorPlanet, rdf:type, rdfs:Class kb.astro.o:MajorPlanet, rdfs:subClassOf, kb.astro.o:AstronomicalBody kb.astro.o:MajorPlanet, rdfs:label, “Major Planet” @en kb.astro.o:MajorPlanet, kb.gen:definition, “An astronomical body orbiting a star, or n-ary star system, which is not itself a star, has sufficient mass to have a nearly round shape, and has cleared the neighborhood around its orbit” @en // Type: Minor Planet extends Astronomical Body kb.astro.o:MinorPlanet, rdf:type, rdfs:Class kb.astro.o:MinorPlanet, rdfs:subClassOf, kb.astro.o:AstronomicalBody kb.astro.o:MinorPlanet, rdfs:label, “Minor Planet” @en kb.astro.o:MinorPlanet, kb.gen:definition, “An astronomical body orbiting a star, or n-ary star system, which is not itself a star and has sufficient mass to have a nearly round shape” @en // Type: Moon extends Astronomical Body kb.astro.o:Moon, rdf:type, rdfs:Class kb.astro.o:Moon, rdfs:subClassOf, kb.astro.o:AstronomicalBody kb.astro.o:Moon, rdfs:label, “Moon” @en kb.astro.o:Moon, kb.gen:definition, “An astronomical body orbiting a planet” @en

Property (Predicate) Definitions (RDF Triples) // Property: majorPlanet kb.astro.o:majorPlanet, rdf:type, rdf:Property kb.astro.o:majorPlanet, rdfs:label, “majorPlanet” @en kb.astro.o:majorPlanet, rdfs:domain, kb.astro.o:AstronomicalBody kb.astro.o:majorPlanet, rdfs:range, kb.astro.o:MajorPlanet // Property: moon kb.astro.o:moon, rdf:type, rdf:Property kb.astro.o:moon, rdfs:label, “moon” @en kb.astro.o:moon, rdfs:domain, kb.astro.o:AstronomicalBody kb.astro.o:moon, rdfs:range, kb.astro.o:Moon // Property: definition kb.gen:definition, rdf:type, rdfs:Property kb.gen:definition, rdfs:Label, “definition” @en // Property: meanDiameter kb.astro.o:meanDiameter, rdf:type, rdfs:Property kb.astro.o:meanDiameter, rdfs:Label, “meanDiameter” @en kb.astro.o:meanDiameter, rdfs:domain, kb.astro.o:AstronomicalBody kb.astro.o:meanDiameter, rdfs:range, rdfs:Literal // Property: meanOrbitalRadius kb.astro.o:meanOrbitalRadius, rdf:type, rdfs:Property kb.astro.o:meanOrbitalRadius, rdfs:Label, “meanOrbitalRadius” @en kb.astro.o:meanOrbitalRadius, rdfs:domain, kb.astro.o:AstronomicalBody kb.astro.o:meanOrbitalRadius, rdfs:range, rdfs:Literal

Astronomical Body

Star

Major Planet

Minor Planet

Moon

Instance Definitions (RDF Triples) // Instance: The Sun kb.astro.i:Sun, rdf:type, kb.astro.o:Star kb.astro.i:Sun, rdfs:label, “The Sun” @en kb.astro.i:Sun, kb:meanDiameter, “1,390,000 km” @en kb.astro.i:Sun, kb.astro.o:majorPlanet, kb.astro.i.Earth // Instance: The Earth kb.astro.i:Earth, rdf:type, kb.astro.o:MajorPlanet kb.astro.i:Earth, rdfs:label, “The Earth” @en kb.astro.i:Earth, kb.astro.o:meanDiameter, “12,742 km” @en kb.astro.i:Earth, kb.astro.o:meanOrbitalRadius, “149,600,000 km” @en kb.astro.i:Earth, kb.astro.o:moon, kb.astro.i:Moon // Instance: The Moon kb.astro.i:Moon, rdf:type, kb.astro.o:Moon kb.astro.i:Moon, rdfs:label, “The Moon” @en kb.astro.i:Moon, kb:meanDiameter, “3,474 km” @en kb.astro.i:Moon, kb.astro.o:meanOrbitalRadius, “384,403 km” @en

rdfs:subClassOf

The Sun

Star rdf:type

majorPlanet []

meanDiameter 1,390,000 km

[0]

[1]

[2]

[3]

[4]

[5]

[6]

[7]

The Earth

rdf:type

Major Planet

The Moon moon

meanDiameter

12,742 km

rdf:type Moon

meanDiameter

384,403 km

149,600,000 km

meanOrbitalRadius

3,474 km

meanOrbitalRadius


Example Astronomy RDF Ontology – Actual RDF/XML <?xml version="1.0"?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:kb="http://dmlkb.org/kb/gen#" xmlns:kb.astro.o="http://dmlkb.org/kb/astro.o#" xmlns:kb.astro.i="http://dmlkb.org/kb/astro.i#"> <rdfs:Class rdf:about="http://dmlkb.org/kb/astro.o#AstronomicalBody"> <rdfs:label xml:lang="en">Astronomical Body</rdfs:label> <kb.astro.o:definition xml:lang="en">A naturally-occurring, gravitationally bound aggregation of matter located in space</kb.astro.o:definition> </rdfs:Class> <rdfs:Class rdf:about="http://dmlkb.org/kb/astro.o#Star"> <rdfs:subClassOf rdf:resource="http://dmlkb.org/kb/astro.o#AstronomicalBody" /> <rdfs:label xml:lang="en">Star</rdfs:label> <kb.astro.o:definition xml:lang="en">An astronomical body that radiates energy resulting from sustained, internal thermonuclear reactions</kb.astro.o:definition> </rdfs:Class> <rdfs:Class rdf:about="http://dmlkb.org/kb/astro.o#MajorPlanet"> <rdfs:subClassOf rdf:resource="http://dmlkb.org/kb/astro.o#AstronomicalBody" /> <rdfs:label xml:lang="en">Major Planet</rdfs:label> <kb.astro.o:definition xml:lang="en">An astronomical body orbiting a star, or n-ary star system, which is not itself a star, has sufficient mass to have a nearly round shape, and has cleared the neighborhood around its orbit</kb.astro.o:definition> </rdfs:Class> <rdfs:Class rdf:about="http://dmlkb.org/kb/astro.o#MinorPlanet"> <rdfs:subClassOf rdf:resource="http://dmlkb.org/kb/astro.o#AstronomicalBody" /> <rdfs:label xml:lang="en">Minor Planet</rdfs:label> <kb.astro.o:definition xml:lang="en">An astronomical body orbiting a star, or n-ary star system, which is not itself a star and has sufficient mass to have a nearly round shape</kb.astro.o:definition> </rdfs:Class> <rdfs:Class rdf:about="http://dmlkb.org/kb/astro.o#Moon"> <rdfs:subClassOf rdf:resource="http://dmlkb.org/kb/astro.o#AstronomicalBody" /> <rdfs:label xml:lang="en">Moon</rdfs:label> <kb.astro.o:definition xml:lang="en">An astronomical body orbiting a planet</kb.astro.o:definition> </rdfs:Class> <rdfs:Property rdf:about="http://dmlkb.org/kb/astro.o#majorPlanet"> <rdfs:domain rdf:resource="http://dmlkb.org/kb/astro.o#Star" /> <rdfs:range rdf:resource="kb.astro.o:MajorPlanet" /> <rdfs:label xml:lang="en">majorPlanet</rdfs:label> </rdfs:Property> <rdfs:Property rdf:about="http://dmlkb.org/kb/astro.o#meanDiameter"> <rdfs:domain rdf:resource="kb.astro.o:AstronomicalBody" /> <rdfs:range rdf:resource="rdfs:Literal" /> <rdfs:label xml:lang="en">meanDiameter</rdfs:label> </rdfs:Property> <rdfs:Property rdf:about="http://dmlkb.org/kb/astro.o#meanOrbitalRadius"> <rdfs:domain rdf:resource="kb.astro.o:AstronomicalBody" /> <rdfs:range rdf:resource="rdfs:Literal" /> <rdfs:label xml:lang="en">meanOrbitalRadius</rdfs:label> </rdfs:Property> <rdfs:Property rdf:about="http://dmlkb.org/kb/gen#definition"> <rdfs:label xml:lang="en">definition</rdfs:label> <rdfs:range rdf:resource="rdfs:Literal" /> </rdfs:Property> <kb.astro.o:Star rdf:about="http://dmlkb.org/kb/astro.i#Sun"> <rdfs:label xml:lang="en">The Sun</rdfs:label> <kb.astro.o:meanDiameter>1,390,000 km</kb.astro.o:meanDiameter> <kb.astro.o:majorPlanet rdf:resource="http://dmlkb/kb/astro.i#Earth" /> </kb.astro.o:Star> <kb.astro.o:MajorPlanet rdf:about="http://dmlkb.org/kb/astro.i#Earth"> <rdfs:label xml:lang="en">The Earth</rdfs:label> <kb.astro.o:meanDiameter>12,742 km</kb.astro.o:meanDiameter> <kb.astro.o:meanOrbitalRadius>149,600,000 km</kb.astro.o:meanOrbitalRadius> <kb.astro.o:moon rdf:resource="http://dmlkb/kb/astro.i#Moon" /> </kb.astro.o:MajorPlanet> <kb.astro.o:Moon rdf:about="http://dmlkb.org/kb/astro.i#Moon"> <rdfs:label xml:lang="en">The Moon</rdfs:label> <kb.astro.o:meanDiameter>3,474 km</kb.astro.o:meanDiameter> <kb.astro.o:meanOrbitalRadius>384,403 km</kb.astro.o:meanOrbitalRadius> </kb.astro.o:Moon> </rdf:RDF>

This is the actual XML needed to assert the triples in the previous slide. If you are unfamiliar with RDF, try this: 1. Copy the XML text from here. (PDF text on this page loses its formatting when copied.) 2. Paste it into the Check by Direct Input text area on the W3C RDF Validator web page

(http://www.w3.org/RDF/Validator/). 3. In the Display Result Options drop-down list, select: Triples and Graph. 4. Click on the Parse RDF button. 5. Browse the resulting parsed RDF triples as well as the (large) generated graph image.


https://sites.google.com/site/rickcreamer/Home/portfolio-1/example-rdf-astronomy-ontology

http://www.w3.org/RDF/Validator/

http://sites.google.com/site/rickcreamer/Home/miscellaneous-items/national-educational-software-technology-project/AstronomyOntologyValidatorGraph.png

Example Astronomy RDF Ontology – Actual RDF Triples (After parsing the previous slide’s XML on the W3C RDF Validator web page)

Number Subject Predicate Object

1 http://dmlkb.org/kb/astro.o#AstronomicalBody http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Class

2 http://dmlkb.org/kb/astro.o#AstronomicalBody http://www.w3.org/2000/01/rdf-schema#label "Astronomical Body"@en

3 http://dmlkb.org/kb/astro.o#AstronomicalBody http://dmlkb.org/kb/astro.o#definition "A naturally-occurring, gravitationally bound aggregation of matter located in space"@en

4 http://dmlkb.org/kb/astro.o#Star http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Class

5 http://dmlkb.org/kb/astro.o#Star http://www.w3.org/2000/01/rdf-schema#subClassOf http://dmlkb.org/kb/astro.o#AstronomicalBody

6 http://dmlkb.org/kb/astro.o#Star http://www.w3.org/2000/01/rdf-schema#label "Star"@en

7 http://dmlkb.org/kb/astro.o#Star http://dmlkb.org/kb/astro.o#definition "An astronomical body that radiates energy resulting from sustained, internal thermonuclear

reactions"@en

8 http://dmlkb.org/kb/astro.o#MajorPlanet http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Class

9 http://dmlkb.org/kb/astro.o#MajorPlanet http://www.w3.org/2000/01/rdf-schema#subClassOf http://dmlkb.org/kb/astro.o#AstronomicalBody

10 http://dmlkb.org/kb/astro.o#MajorPlanet http://www.w3.org/2000/01/rdf-schema#label "Major Planet"@en

11 http://dmlkb.org/kb/astro.o#MajorPlanet http://dmlkb.org/kb/astro.o#definition "An astronomical body orbiting a star, or n-ary star system, which is not itself a star, has sufficient mass

to have a nearly round shape, and has cleared the neighborhood around its orbit"@en

12 http://dmlkb.org/kb/astro.o#MinorPlanet http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Class

13 http://dmlkb.org/kb/astro.o#MinorPlanet http://www.w3.org/2000/01/rdf-schema#subClassOf http://dmlkb.org/kb/astro.o#AstronomicalBody

14 http://dmlkb.org/kb/astro.o#MinorPlanet http://www.w3.org/2000/01/rdf-schema#label "Minor Planet"@en

15 http://dmlkb.org/kb/astro.o#MinorPlanet http://dmlkb.org/kb/astro.o#definition "An astronomical body orbiting a star, or n-ary star system, which is not itself a star and has sufficient

mass to have a nearly round shape"@en

16 http://dmlkb.org/kb/astro.o#Moon http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Class

17 http://dmlkb.org/kb/astro.o#Moon http://www.w3.org/2000/01/rdf-schema#subClassOf http://dmlkb.org/kb/astro.o#AstronomicalBody

18 http://dmlkb.org/kb/astro.o#Moon http://www.w3.org/2000/01/rdf-schema#label "Moon"@en

19 http://dmlkb.org/kb/astro.o#Moon http://dmlkb.org/kb/astro.o#definition "An astronomical body orbiting a planet"@en

20 http://dmlkb.org/kb/astro.o#majorPlanet http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Property

21 http://dmlkb.org/kb/astro.o#majorPlanet http://www.w3.org/2000/01/rdf-schema#domain http://dmlkb.org/kb/astro.o#Star

22 http://dmlkb.org/kb/astro.o#majorPlanet http://www.w3.org/2000/01/rdf-schema#range kb.astro.o:MajorPlanet

23 http://dmlkb.org/kb/astro.o#majorPlanet http://www.w3.org/2000/01/rdf-schema#label "majorPlanet"@en

24 http://dmlkb.org/kb/astro.o#meanDiameter http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Property

25 http://dmlkb.org/kb/astro.o#meanDiameter http://www.w3.org/2000/01/rdf-schema#domain kb.astro.o:AstronomicalBody

26 http://dmlkb.org/kb/astro.o#meanDiameter http://www.w3.org/2000/01/rdf-schema#range rdfs:Literal

27 http://dmlkb.org/kb/astro.o#meanDiameter http://www.w3.org/2000/01/rdf-schema#label "meanDiameter"@en

28 http://dmlkb.org/kb/astro.o#meanOrbitalRadius http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Property

29 http://dmlkb.org/kb/astro.o#meanOrbitalRadius http://www.w3.org/2000/01/rdf-schema#domain kb.astro.o:AstronomicalBody

30 http://dmlkb.org/kb/astro.o#meanOrbitalRadius http://www.w3.org/2000/01/rdf-schema#range rdfs:Literal

31 http://dmlkb.org/kb/astro.o#meanOrbitalRadius http://www.w3.org/2000/01/rdf-schema#label "meanOrbitalRadius"@en

32 http://dmlkb.org/kb/gen#definition http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2000/01/rdf-schema#Property

33 http://dmlkb.org/kb/gen#definition http://www.w3.org/2000/01/rdf-schema#label "definition"@en

34 http://dmlkb.org/kb/gen#definition http://www.w3.org/2000/01/rdf-schema#range rdfs:Literal

35 http://dmlkb.org/kb/astro.i#Sun http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dmlkb.org/kb/astro.o#Star

36 http://dmlkb.org/kb/astro.i#Sun http://www.w3.org/2000/01/rdf-schema#label "The Sun"@en

37 http://dmlkb.org/kb/astro.i#Sun http://dmlkb.org/kb/astro.o#meanDiameter "1,390,000 km"

38 http://dmlkb.org/kb/astro.i#Sun http://dmlkb.org/kb/astro.o#majorPlanet http://dmlkb/kb/astro.i#Earth

39 http://dmlkb.org/kb/astro.i#Earth http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dmlkb.org/kb/astro.o#MajorPlanet

40 http://dmlkb.org/kb/astro.i#Earth http://www.w3.org/2000/01/rdf-schema#label "The Earth"@en

41 http://dmlkb.org/kb/astro.i#Earth http://dmlkb.org/kb/astro.o#meanDiameter "12,742 km"

42 http://dmlkb.org/kb/astro.i#Earth http://dmlkb.org/kb/astro.o#meanOrbitalRadius "149,600,000 km"

43 http://dmlkb.org/kb/astro.i#Earth http://dmlkb.org/kb/astro.o#moon http://dmlkb/kb/astro.i#Moon

44 http://dmlkb.org/kb/astro.i#Moon http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dmlkb.org/kb/astro.o#Moon

45 http://dmlkb.org/kb/astro.i#Moon http://www.w3.org/2000/01/rdf-schema#label "The Moon"@en

46 http://dmlkb.org/kb/astro.i#Moon http://dmlkb.org/kb/astro.o#meanDiameter "3,474 km"

47 http://dmlkb.org/kb/astro.i#Moon http://dmlkb.org/kb/astro.o#meanOrbitalRadius "384,403 km"


http://dmlkb.org/kb/astro.o

http://www.w3.org/1999/02/22-rdf-syntax-ns







http://www.w3.org/2000/01/rdf-schema





















































































































kb.astro.o:MajorPlanet




















kb.astro.o:AstronomicalBody





rdfs:Literal




















kb.astro.o:AstronomicalBody





rdfs:Literal





http://dmlkb.org/kb/gen



















rdfs:Literal

http://dmlkb.org/kb/astro.i

















http://dmlkb/kb/astro.i




















http://dmlkb/kb/astro.i


















The End (for now)

This is the end of this quick snapshot in time of my ideas on ‘reinventing learning.’ I have many other ideas but haven’t

the time to evolve them or write them down.

If you want to help, feel free to contact me at:



mailto:[email protected]

Design

Next-Gen E-Learning Ideas