11/29/2023 0 Comments Scientific data table creator![]() ![]() The same goesįor addition quantities with different dimensions. Relation that only the database creator can know about. Testing equality between to quantities that have different physicalĭimension is likely to be meaningless, unless there is some implicit Testing equality of weight and date probably does not. But not all operations between them make sense. You could have these quantities appear to qualify columns in the dataīase of a physicist. Speed, date, duration, temperature, heat. Physics uses a lot of scalar quantities: weight, distance, I will attempt to illustrate a possible type vision with To your generator, if you hope for an answer (which is a variant of You have to say what data, what semantic information, you provide Numbers, and any idea you may have to fold, spindle or mutilate them Kind of semantic information, a column of numbers is just a column of Generator, so that your queries make sense. Though a physicist told me that is not the case.Īlso you should make clear what you intend to provide as input to your ![]() There is a possibility that they may have addressed this typing issue, Information can be found on these tools (usually very proprietary), I also know that physicists use "databases" to store theirĮxperimental data before exploiting it with specialized software. Hence, first of all, you should look whether there is something toīe learned from object oriented databases. Oriented languages, and all languages with data abstraction. Programming languages, but of abstract types as found now in object I am not thinking of elementary types as found in most It may not beĮasy or even meaningful to attempt to deal with it in a purelyĪutomated way. See also as a dimensional problem in the physics sense. I suspect that you may have a typing problem, which I tend to It isĪ semantic issue that depends much on the semantics you attach to your But thereĪs remarked by Raphael, generating queries is relatively easy. ![]() Influenced by your example and the queries that go with it. The various types of queries one can make. Would really require more study of how this kind of view may combine with Since there are no answers yet, I will attempt to Seen it (but I am not in databases), and I would be surprised if no I have no idea whether this has been addressed before. The tables and the relationships that I study are not very complicated.Ĭould anyone tell me which field this problem belongs to? Are there some good results/proposals that are easy to understand? And this conclusion can be more or less inferred from the two given relationships.Ĭertainly, the problem becomes more complexe when there are relationships among several tables. Intuitively, we can say that Query 1 and Query 2 make more sense than Query 3. The second issue is, how to rank the meaningful queries? For example, Then, the first issue is, how to automatically generate some queries? For instance: 1) Sum of Quantity by ArticleID There are two relationships in this table, which may be given or inferred (the detection of the relationships is not an issue here): a) one ArticleID maps one Price b) Sale = Price * Quantity. Here is an example: ArticleID Price Quantity Sale Are there some algorithms to automatically generate a ranked set of meaningful queries, from the relationships inside the table? But some queries are meaningful, some are meaningless. The main question is: given a table of data, there are lots of possible queries that can be made. But I have some problems to solve, and would like to know which branch this kind of problems belong to, and what are the results. While in dynamic settings mode the "Columns" and "Keys" tab become read-only to allow you a preview of the dynamic settings.My field of research is not Database or AI. ![]() If no mapping is defined in both Name-Based SQL Type mapping and KNIME-Based SQL Type Mapping, then the default mapping is used. The mappings defined in the Name-Based SQL Type Mapping have a higher priority than the mappings defined in the KNIME-Based SQL Type Mapping. All dynamic settings which are made via the "Dynamic Type Settings" and "Dynamic Column Settings" tab are applied to the data table specification of the input data table. Once enable it allows to dynamically define the SQL type of the columns as well as the assignment of columns to primary or unique keys. Tick the "Use dynamic settings" option to enable the dynamic settings behavior. The node supports advanced options such as null or not null, primary key or unique keys, default SQL type mapping based on column name or KNIME data type, and default key definitions based on column names. This node allows a user to create a new database table either manually or based on the specification of a KNIME input data table (see "Use dynamic settings" below). ![]()
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