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"The study of databases intersects almost every topic in computer science" - I've heard this before, especially for Compilers. But it has been false for a long

by quonn 12y ago

"The study of databases intersects almost every topic in computer science" - I've heard this before, especially for Compilers. But it has been false for a long time, CS is far more diverse now. For example, how do Databases intersect AI/Machine Learning/Computer Vision, Computer Graphics, Numerics/Simulation, Robotics, Bioinformatics, Computer Architecture or Cryptography?

applecore 12y ago
All of the fields you've listed are largely about the representation of data. A database is simply data that's structured to support an algorithm that models some aspect of reality based on that data.
- quonn 12y ago
  Sure you can say, everything inside a computer is about representing data, so all is the same. But it's not particularly useful to do that.
  - pessimizer 12y ago
    >you can say, everything inside a computer is about representing data hence: "The study of databases intersects almost every topic in computer science"
    - quonn 12y ago
      I just claimed this point of view is useless, so you can't just pick it up as if I agreed. Furthermore data representation in that broad sense is more related to data structures, not databases. Really, we all know what a database is. It is something very different from, say, a block cipher.
      - deleted 12y ago
        [deleted]
      - pessimizer 12y ago
        You claimed that point of view was useless, but you didn't argue why it was useless. My point of view is that none of "AI/Machine Learning/Computer Vision, Computer Graphics, Numerics/Simulation, Robotics, Bioinformatics, Computer Architecture or Cryptography" can be implemented (or even well conceptualized) without figuring out how they are to store, retrieve, encode, efficiently memoize, guarantee consistency or atomicity, or apply bulk transformations to their data. It's silly to dispute that databases touch all areas of computing by simply declaring that databases touching all areas of computing is meaningless, because it's obvious that databases would touch all areas of computing, because computers are data storage, retrieval, and processing devices. Maybe you're restricting your definition to RDMS (while mentally drawing some arbitrary sharp distinction between data structures and databases.) >Really, we all know what a database is. This is simply a declaration. If you know what a database is, define it, then make your case about what areas of computing that it is irrelevant to. Argument by common sense is empty.
redwood 12y ago
Taking some leaps here but AI/Machine Learning/Computer Vision - online index selection / query plan optimization. Computer Graphics - geo 3d indexes Numerics/Simulation - query plan optimization Robotics -if you go meta here there is a lot of overlap with distributed system coordination Bioinformatics - minimal except that this by definition requires uniquely rich data structures that need to be able to be accessed and stored in a database Computer Architecture - databases certainly are themselves architected to perform on computer architectures and the reverse is probably true Cryptography - databases often employ encryption and other security capabilities that are of critical importance but true this isn't the field you mention
JadeNB 12y ago
> how do Databases intersect AI/Machine Learning I am not in any way a computer-science expert, but surely these topics have substantial overlap? (For example, a machine that is learning must store its accumulated knowledge somewhere.)
- quonn 12y ago
  There is data mining, which is like machine learning + databases. But for many, many machine learning problems, the learning occurs offline and the data is simply stored in files, then the learning algorithm is run. The result is a model, which in many cases has a small constant representation (common exceptions: kNN and SVM). There is no database involved. Now you can of course try to learn from an existing database (data mining) or from huge amounts of data, probably stored in a distributed database (big data). But many systems will not and even then the database part is usually not of much concern. So I still don't see much overlap.
  - siddboots 12y ago
    The overlap goes well beyond the question of whether an literal database software system is used: Knowledge representation (as in modern AI), feature representation (as in ML), and relational data modelling are essentially all different branches of the same domain of study. Consider, for example, the connection with logic resolution languages like Prolog.
sampo 12y ago
> how do Databases intersect ... Bioinformatics You must be kidding. The whole field of bioinformatics was born when the biologists started to have large enough collections of protein and DNA sequences that working with them by hand was not practical anymore.
matwood 12y ago
But it has been false for a long time Actually it has been getting more true for a long time. With computers in nearly every aspect of society we have more data than ever to sift through. AI/ML is a big data problem. Numerics and simulations become more effective with large amounts of data. Instead of simulating a result from 1 data point, try 100s, 1000s or millions or data points.

by quonn 12y ago

applecore 12y ago

All of the fields you've listed are largely about the representation of data. A database is simply data that's structured to support an algorithm that models some aspect of reality based on that data.

quonn 12y ago
Sure you can say, everything inside a computer is about representing data, so all is the same. But it's not particularly useful to do that.
- pessimizer 12y ago
  >you can say, everything inside a computer is about representing data hence: "The study of databases intersects almost every topic in computer science"
  - quonn 12y ago
    I just claimed this point of view is useless, so you can't just pick it up as if I agreed. Furthermore data representation in that broad sense is more related to data structures, not databases. Really, we all know what a database is. It is something very different from, say, a block cipher.
    - deleted 12y ago
      [deleted]
    - pessimizer 12y ago
      You claimed that point of view was useless, but you didn't argue why it was useless. My point of view is that none of "AI/Machine Learning/Computer Vision, Computer Graphics, Numerics/Simulation, Robotics, Bioinformatics, Computer Architecture or Cryptography" can be implemented (or even well conceptualized) without figuring out how they are to store, retrieve, encode, efficiently memoize, guarantee consistency or atomicity, or apply bulk transformations to their data. It's silly to dispute that databases touch all areas of computing by simply declaring that databases touching all areas of computing is meaningless, because it's obvious that databases would touch all areas of computing, because computers are data storage, retrieval, and processing devices. Maybe you're restricting your definition to RDMS (while mentally drawing some arbitrary sharp distinction between data structures and databases.) >Really, we all know what a database is. This is simply a declaration. If you know what a database is, define it, then make your case about what areas of computing that it is irrelevant to. Argument by common sense is empty.

redwood 12y ago

Taking some leaps here but AI/Machine Learning/Computer Vision - online index selection / query plan optimization. Computer Graphics - geo 3d indexes Numerics/Simulation - query plan optimization Robotics -if you go meta here there is a lot of overlap with distributed system coordination Bioinformatics - minimal except that this by definition requires uniquely rich data structures that need to be able to be accessed and stored in a database Computer Architecture - databases certainly are themselves architected to perform on computer architectures and the reverse is probably true Cryptography - databases often employ encryption and other security capabilities that are of critical importance but true this isn't the field you mention

JadeNB 12y ago

> how do Databases intersect AI/Machine Learning I am not in any way a computer-science expert, but surely these topics have substantial overlap? (For example, a machine that is learning must store its accumulated knowledge somewhere.)

quonn 12y ago
There is data mining, which is like machine learning + databases. But for many, many machine learning problems, the learning occurs offline and the data is simply stored in files, then the learning algorithm is run. The result is a model, which in many cases has a small constant representation (common exceptions: kNN and SVM). There is no database involved. Now you can of course try to learn from an existing database (data mining) or from huge amounts of data, probably stored in a distributed database (big data). But many systems will not and even then the database part is usually not of much concern. So I still don't see much overlap.
- siddboots 12y ago
  The overlap goes well beyond the question of whether an literal database software system is used: Knowledge representation (as in modern AI), feature representation (as in ML), and relational data modelling are essentially all different branches of the same domain of study. Consider, for example, the connection with logic resolution languages like Prolog.

sampo 12y ago

> how do Databases intersect ... Bioinformatics You must be kidding. The whole field of bioinformatics was born when the biologists started to have large enough collections of protein and DNA sequences that working with them by hand was not practical anymore.

matwood 12y ago

But it has been false for a long time Actually it has been getting more true for a long time. With computers in nearly every aspect of society we have more data than ever to sift through. AI/ML is a big data problem. Numerics and simulations become more effective with large amounts of data. Instead of simulating a result from 1 data point, try 100s, 1000s or millions or data points.