Interactive interfaces as computerized tools to present summarization data of dataset attributes for collaborative datasets
Various embodiments relate generally to data science and data analysis, and computer software and systems, to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby one or more interfaces, such as user interfaces, may be implemented as computerized tools for presenting summarization of dataset attributes to facilitate discovery, formation, and analysis of interrelated collaborative datasets. In some examples, a method may include presenting data representing summary characteristic data in a user interface. This may include user interface elements each specifying a value of a dataset attribute for a collaborative dataset. Also, the method may include presenting aggregated data attributes for a subset of the collaborative dataset associated with the linked atomized datasets. In one example, an interactive overlay window may be activated.
1. A method comprising:
providing access to a collaborative dataset access interface via a user interface;
receiving data to form a first input via the user interface as a first user interface element to initiate a data operation on a collaborative atomized dataset;
receiving a data signal indicating selection of the data operation;
activating a programmatic interface to perform the selected operation responsive to the data signal;
presenting a data entry interface in the user interface to receive operation data instructions;
transforming the operation data instructions into graph-related data instructions to access data associated with the collaborative atomized dataset by converting a command from a high-level language to a graph-level language, the command being configured to perform statistical and data analysis, and using the graph-level language to access the collaborative atomized dataset to perform the data operation, the data operation being a query;
implementing the graph-related data instructions to perform the data operation; and
retrieving data representing results responsive to executing the graph-related data instructions.
2. The method of claim 1 wherein receiving the data to form the first input to initiate the data operation comprises:
initiating a statistical data analysis operation.
3. The method of claim 1 further comprising:
activating a subset of executable code to present in a portion of the user interface an interactive overlay window as a second interface element; and
presenting the interactive overlay window to include aggregated data attributes for the collaborative atomized dataset.
4. The method of claim 3 further comprising:
determining selection of a third user interface element of the interactive overlay window to identify a graphical representation of a range of values in a distribution of a plurality of ranges of values for a subset of data in the collaborative atomized dataset.
5. The method of claim 1 further comprising:
performing a statistical data analysis operation to generate a range of values in a distribution of a plurality of ranges of values for a subset of data in the collaborative atomized dataset.
6. The method of claim 1 wherein receiving the data to form the first input to initiate the data operation comprises:
initiating a query operation.
7. The method of claim 6 wherein initiating the query operation comprises:
generating a plurality of queries each of which is configured to access at least one atomized dataset having a different data format associated with one of any number of different data storage technologies; and
retrieving data representing query results from the at least one of the different data storage technologies.
8. The method of claim 1 wherein transforming the operation data instructions comprises:
converting commands in a structured query language (“SQL”) into a graph-level language; and
using the graph-level language to access the collaborative atomized dataset to perform the data operation.
9. The method of claim 1 wherein transforming the operation data instructions further comprises:
accessing a triplestore repository to access the data associated with the collaborative atomized dataset.
10. An apparatus comprising:
a memory including executable instructions; and
a processor, responsive to executing the instructions, is configured to:
provide access to a collaborative dataset access interface via a user interface
receive data to form a first input via the user interface as a first user interface element to initiate a data operation on a collaborative atomized dataset;
receive a data signal indicating selection of the data operation;
activate a programmatic interface to perform the selected operation responsive to the data signal;
present a data entry interface in the user interface to receive operation data instructions;
transform the operation data instructions into graph-related data instructions to access data associated with the collaborative atomized dataset by converting a command from a high-level language to a graph-level language, the command being configured to perform statistical and data analysis, and using the graph-level language to access the collaborative atomized dataset to perform the data operation, the data operation being a query;
implement the graph-related data instructions to perform the data operation; and
retrieve data representing results responsive to executing the graph-related data instructions.
11. The apparatus of claim 10 wherein the processor is further configured to:
initiate a statistical data analysis operation.
12. The apparatus of claim 10 wherein the processor is further configured to:
activate a subset of executable code to present in a portion of the user interface an interactive overlay window as a second interface element; and
present the interactive overlay window to include aggregated data attributes for the collaborative atomized dataset.
13. The apparatus of claim 12 wherein the processor is further configured to:
determine selection of a third user interface element of the interactive overlay window to identify a graphical representation of a range of values in a distribution of a plurality of ranges of values for a subset of data in the collaborative atomized dataset.
14. The apparatus of claim 10 wherein the processor is further configured to:
perform a statistical data analysis operation to generate a range of values in a distribution of a plurality of ranges of values for a subset of data in the collaborative atomized dataset.
15. The apparatus of claim 10 wherein the processor is further configured to:
initiate a query operation.
16. The apparatus of claim 15 wherein the processor is further configured to:
generate a plurality of queries each of which is configured to access at least one atomized dataset having a different data format associated with one of any number of different data storage technologies; and
retrieve data representing query results from the at least one of the different data storage technologies.
17. The apparatus of claim 10 wherein the processor is further configured to:
convert commands in a structured query language (“SQL”) into a graph-level language; and
use the graph-level language to access the collaborative atomized dataset to perform the data operation.
18. The apparatus of claim 10 wherein the processor is further configured to:
access a triplestore repository to access the collaborative data associated with the atomized dataset.