4 ms·

I worked at a company that got sold on Semantic Web and made an initial investment in tools and training. While I found the concepts intriguing, the teams taske

I worked at a company that got sold on Semantic Web and made an initial investment in tools and training. While I found the concepts intriguing, the teams tasked with making it work gave up after about six months of trying to make it work with the use case they had. I understand that it can be a powerful set of concepts for certain kinds of use cases but it feels like the level of dedication and care needed to make it work is probably beyond many organizations' ability to execute. The impression I got was that it was like deciding to use a Kibble Balance [0] to weigh yourself in the morning. You have to match the use case to the tool and for many organizations this simply will not be the right tool. [0] https://en.wikipedia.org/wiki/Kibble_balance https://en.wikipedia.org/wiki/Kibble_balance

specialist 8y ago
I worked for a semantic web startup, back when it was the next big thing. We had a tool (UI & backend) purportedly for managing ontologies, taxonomies, vocabularies. Our customers were begging for real world solutions. Would have paid any price. Our leadership (CTO) was mesmerized by metametametadata. Not kidding. And had zero interest in customer's real needs. Such a missed opportunity. The two lessons I took away... 1/ Most real world modeling problems are some narrowed use case of knowledge representation. Our customers didn't want a general purpose tool. They wanted something tailored (customizable) for their immediate use cases. As a UI designer, I guess I should have realized this quicker. My only defense is initial lack of customer interaction. 2/ At the time, for general purpose graph splunking, there was no UI solution for the "focus+context" problem. Human sized ways to query, represent, and navigate large graphs, all in one. I did come up with a novel UI/UX that I felt would solve "focus+context", but we ran out of runway before I could get past the lo-fi prototypes. On my to do list is to take another run at the problem, leveraging Neo4j's (awesome) Cypher query language. I may discover that Neo4j's UI may have already solved the "focus+context" problem.
- CuriousSkeptic 8y ago
  Would love to see examples of useful ux. Do you have anything to share? I have this hobby project where I’m thinking of using some kind of knowledge graph to represent beliefs about scientific facts and urban myths. An attempt to crowd source peer review of the pop-sci cited in online fora of various kinds. My prototype app being a nutrition planner based on dietary recommendation sources from the graph in question. Not being a ux-designer, I’m a bit stuck on how to approach it.
  - specialist 8y ago
    What tools do existing nutritionists use?
    - CuriousSkeptic 8y ago
      My target group for this would not be nutritionists. Just people like me with way to much curiosity about various topics. But a fair suggestion, I should look into that. The long term aim of the application isn’t nutrition though. I’m thinking more of a general stack exchange like platform for quality checking beliefs in various domains. The music brainz database might be a good example of how it would fit into an application echo system.
      - specialist 8y ago
        Cool. I'm glad someone pointed out Skirky's thesis (which you saw). You may also want to peek at folksonomy. https://en.wikipedia.org/wiki/Folksonomy https://en.wikipedia.org/wiki/Folksonomy I used to be believe the world was knowable and representable, definitively. Much like the aspirations of the Cyc effort. https://en.wikipedia.org/wiki/Cyc https://en.wikipedia.org/wiki/Cyc I now believe the usefulness of any particular model and captured dataset depends on who's asking the questions. For nutrition, there might be different views for laypersons, producers, nutritionists, researchers, etc. Sure, the domain is the same. But the details relevant to each, their use cases, will determine the schemas, the datasets, the granularity, the queries. Further, efforts to create the uber-nutrition-o-pedia knowledgebase, useful for all audiences, will inevitably disappoint. In other words: One size fits none. I don't mean to be a buzz kill. I'm just relating my pessimism after once having lofty ambitions. YMMV. -- I have completely different notions about belief systems, fact checking, etc. There have been many "what is true" efforts. There will be many more. A contributor at mondaynote.com writes about some school's effort (Berkeley?) and links to similar efforts. I think they'll all fail to meet their goals. As we learned from MC 900ft Jesus: Truth is Out of Style. I no longer care if something is true. I only care who said it. Every tidbit needs to sourced, cited, digitally signed. So you can trace who said what when. Authoritatively. Anything without a signature is nothing more than gossip. Then use the existing web of trust infrastructure. News outlets, bloggers, researchers, any one who want to be taken seriously will sign their real names to their works. If someone's cert gets pwned, or is revealed as a shell, then it can be revoked. And everyone will know. Sorry if that's a lot to take in. I'm still chewing on the notion.

specialist 8y ago

I worked for a semantic web startup, back when it was the next big thing. We had a tool (UI & backend) purportedly for managing ontologies, taxonomies, vocabularies. Our customers were begging for real world solutions. Would have paid any price. Our leadership (CTO) was mesmerized by metametametadata. Not kidding. And had zero interest in customer's real needs. Such a missed opportunity. The two lessons I took away... 1/ Most real world modeling problems are some narrowed use case of knowledge representation. Our customers didn't want a general purpose tool. They wanted something tailored (customizable) for their immediate use cases. As a UI designer, I guess I should have realized this quicker. My only defense is initial lack of customer interaction. 2/ At the time, for general purpose graph splunking, there was no UI solution for the "focus+context" problem. Human sized ways to query, represent, and navigate large graphs, all in one. I did come up with a novel UI/UX that I felt would solve "focus+context", but we ran out of runway before I could get past the lo-fi prototypes. On my to do list is to take another run at the problem, leveraging Neo4j's (awesome) Cypher query language. I may discover that Neo4j's UI may have already solved the "focus+context" problem.

CuriousSkeptic 8y ago
Would love to see examples of useful ux. Do you have anything to share? I have this hobby project where I’m thinking of using some kind of knowledge graph to represent beliefs about scientific facts and urban myths. An attempt to crowd source peer review of the pop-sci cited in online fora of various kinds. My prototype app being a nutrition planner based on dietary recommendation sources from the graph in question. Not being a ux-designer, I’m a bit stuck on how to approach it.
- specialist 8y ago
  What tools do existing nutritionists use?
  - CuriousSkeptic 8y ago
    My target group for this would not be nutritionists. Just people like me with way to much curiosity about various topics. But a fair suggestion, I should look into that. The long term aim of the application isn’t nutrition though. I’m thinking more of a general stack exchange like platform for quality checking beliefs in various domains. The music brainz database might be a good example of how it would fit into an application echo system.
    - specialist 8y ago
      Cool. I'm glad someone pointed out Skirky's thesis (which you saw). You may also want to peek at folksonomy. https://en.wikipedia.org/wiki/Folksonomy https://en.wikipedia.org/wiki/Folksonomy I used to be believe the world was knowable and representable, definitively. Much like the aspirations of the Cyc effort. https://en.wikipedia.org/wiki/Cyc https://en.wikipedia.org/wiki/Cyc I now believe the usefulness of any particular model and captured dataset depends on who's asking the questions. For nutrition, there might be different views for laypersons, producers, nutritionists, researchers, etc. Sure, the domain is the same. But the details relevant to each, their use cases, will determine the schemas, the datasets, the granularity, the queries. Further, efforts to create the uber-nutrition-o-pedia knowledgebase, useful for all audiences, will inevitably disappoint. In other words: One size fits none. I don't mean to be a buzz kill. I'm just relating my pessimism after once having lofty ambitions. YMMV. -- I have completely different notions about belief systems, fact checking, etc. There have been many "what is true" efforts. There will be many more. A contributor at mondaynote.com writes about some school's effort (Berkeley?) and links to similar efforts. I think they'll all fail to meet their goals. As we learned from MC 900ft Jesus: Truth is Out of Style. I no longer care if something is true. I only care who said it. Every tidbit needs to sourced, cited, digitally signed. So you can trace who said what when. Authoritatively. Anything without a signature is nothing more than gossip. Then use the existing web of trust infrastructure. News outlets, bloggers, researchers, any one who want to be taken seriously will sign their real names to their works. If someone's cert gets pwned, or is revealed as a shell, then it can be revoked. And everyone will know. Sorry if that's a lot to take in. I'm still chewing on the notion.