(highlight:: Information = Data + Context + Metadata
Transcript:
Speaker 2
I'm wondering what constitutes good information for you?
Speaker 1
Well, I think good information starts with good data. And data is the ingredients that make up information. On its own, you can't use data. It has to have context. And that's what information is. And this is my personal belief in philosophy. So to have good information, not only do you have to have that good data, but you also have to have put into the right context for that situation. And that's where you get into semantics and a lot of other things. But good information definitely boils down to the data, the way that it's structured and the way that it's presented.
Speaker 2
I'm writing down notes as you're speaking. And I wrote down the formula data plus context equals information. Is that fair summary of that idea?
Speaker 1
Yes. And then that's surrounded by, let's just call it meta, the metadata, which points you to how to take that data and make it into information.)
- Time 0:03:04
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(highlight:: Defining Ontology: The Study of Things and How They Relate to Other Things
Key takeaways:
• Ontology is the study of how things relate to each other and whether something is real or not.
• Over time, ontology has expanded to include determining whether something is concrete, physical, conceptual, or abstract.
• The relationship between things has become a significant aspect of ontology.
• Ontology is not only a philosophy but also a scientific pursuit that information scientists can use to organize, understand, and explain information.
Transcript:
Speaker 1
It's really the study of things and how they relate to other things. And ontology comes out of the schools of philosophy from Greece. And back then ontology was really to determine if something was real or not. And through the centuries, ontology has grown into not only is it real, but is it something that's concrete or something that's actually physical? Or is it something that's more conceptual or abstract? And then the how things relate to each other has become a much more important part of ontology than it was back in classical times. And now we have implied ontology where it's not just a philosophy, but actually a scientific pursuit where information scientists can use these philosophical thoughts to help organize Information, understand information and explain information.)
- Time 0:06:36
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(highlight:: Ontologies v.s. Taxonomies
Transcript:
Speaker 1
In my view, taxonomies are very specific applications of an ontology. So an ontology looks at how things are related, whether they are a part of something, whether they are related closely to something, whether they are not something. So an apple is not an orange. And a taxonomy is focused on specifically types, a type of. So the most famous taxonomy is the biological taxonomy. So a cat is a type of feline. A feline is a type of mammal, and a mammal is a type of animal. And it's that very specific kind of line from animal to cat. An ontology goes a little bit broader. A paw is a part of a cat. And a cat eats meat. That kind of breaks the rules of a taxonomy, but it is accepted within an ontology.)
- Time 0:09:56
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(highlight:: Hypernyms and Maronyms in Taxonomies and Ontologies
Transcript:
Speaker 1
So taxonomies deal with what's called hypernemes. And then a hypernem is just getting to something very specific, the very specific name. So that's what hypernem means, hyper very specific, nim name. And then you have marinems, which are the parts of marrow, meaning part and nim name. So the part name of something. So like a pause, a part of the arm or the leg. And then the leg is part of the body. So you have these, what I call nims, the most popular nim quote unquote nim that everybody's used to are synonyms. So the like name. So tree is a synonym to a plant, although you could kind of argue that it's also a type of, but in certain contexts, they are synonyms. So you really, you're dealing with the different names, issues surrounding a subject.)
- Time 0:12:51
-

1min Snip
- Time 0:26:09
-

(highlight:: Information = Data + Context + Metadata
Transcript:
Speaker 2
I'm wondering what constitutes good information for you?
Speaker 1
Well, I think good information starts with good data. And data is the ingredients that make up information. On its own, you can't use data. It has to have context. And that's what information is. And this is my personal belief in philosophy. So to have good information, not only do you have to have that good data, but you also have to have put into the right context for that situation. And that's where you get into semantics and a lot of other things. But good information definitely boils down to the data, the way that it's structured and the way that it's presented.
Speaker 2
I'm writing down notes as you're speaking. And I wrote down the formula data plus context equals information. Is that fair summary of that idea?
Speaker 1
Yes. And then that's surrounded by, let's just call it meta, the metadata, which points you to how to take that data and make it into information.)
- Time 0:03:04
-

(highlight:: Defining Ontology: The Study of Things and How They Relate to Other Things
Key takeaways:
• Ontology is the study of how things relate to each other and whether something is real or not.
• Over time, ontology has expanded to include determining whether something is concrete, physical, conceptual, or abstract.
• The relationship between things has become a significant aspect of ontology.
• Ontology is not only a philosophy but also a scientific pursuit that information scientists can use to organize, understand, and explain information.
Transcript:
Speaker 1
It's really the study of things and how they relate to other things. And ontology comes out of the schools of philosophy from Greece. And back then ontology was really to determine if something was real or not. And through the centuries, ontology has grown into not only is it real, but is it something that's concrete or something that's actually physical? Or is it something that's more conceptual or abstract? And then the how things relate to each other has become a much more important part of ontology than it was back in classical times. And now we have implied ontology where it's not just a philosophy, but actually a scientific pursuit where information scientists can use these philosophical thoughts to help organize Information, understand information and explain information.)
- Time 0:06:36
-

(highlight:: Ontologies v.s. Taxonomies
Transcript:
Speaker 1
In my view, taxonomies are very specific applications of an ontology. So an ontology looks at how things are related, whether they are a part of something, whether they are related closely to something, whether they are not something. So an apple is not an orange. And a taxonomy is focused on specifically types, a type of. So the most famous taxonomy is the biological taxonomy. So a cat is a type of feline. A feline is a type of mammal, and a mammal is a type of animal. And it's that very specific kind of line from animal to cat. An ontology goes a little bit broader. A paw is a part of a cat. And a cat eats meat. That kind of breaks the rules of a taxonomy, but it is accepted within an ontology.)
- Time 0:09:56
-

(highlight:: Hypernyms and Maronyms in Taxonomies and Ontologies
Transcript:
Speaker 1
So taxonomies deal with what's called hypernemes. And then a hypernem is just getting to something very specific, the very specific name. So that's what hypernem means, hyper very specific, nim name. And then you have marinems, which are the parts of marrow, meaning part and nim name. So the part name of something. So like a pause, a part of the arm or the leg. And then the leg is part of the body. So you have these, what I call nims, the most popular nim quote unquote nim that everybody's used to are synonyms. So the like name. So tree is a synonym to a plant, although you could kind of argue that it's also a type of, but in certain contexts, they are synonyms. So you really, you're dealing with the different names, issues surrounding a subject.)
- Time 0:12:51
-

1min Snip
- Time 0:26:09
-