Ask Data Anything - Election results example

In modern organizations, data management is a major issue and at the same time a major resource. In our experience, the first challenge a business that wants to use its data is facing how to have a unified view of their data. Generally data inside organizations is stored in different databases that have often proprietary API making it difficult to move from one database to the other. Furthermore, also when the technology used to store data is the same, there are still semantic problems like different terminologies, languages etc.

The bigger the company is, the lower the possibility to standardize the procedures are, so that these kind of situations will not happen. This happens because we are human and we naturally tend to interpret data using our own experience and knowledge. Thus we cannot expect the technical team to call all pieces of a car using the exact same terminology as the logistic department. This is why, our solution aims at giving the possibility to standardize the way in which the end user interact with the data without actually changing the source of the data.

Ask Data Anything (ADA), allows companies to add a semantical layer on top of the data without the need of copying data. The product is managing term disambiguation, aggregation of data using hierarchies defined in ontologies, data integration between different data sources.

Ask Data Anything - NYPD Motor vehicle accidents

In modern organizations, data management is a major issue and at the same time a major resource. In our experience, the first challenge a business that wants to use its data is facing how to have a unified view of their data. Generally data inside organizations is stored in different databases that have often proprietary API making it difficult to move from one database to the other. Furthermore, also when the technology used to store data is the same, there are still semantic problems like different terminologies, languages etc.

The bigger the company is, the lower the possibility to standardize the procedures are, so that these kind of situations will not happen. This happens because we are human and we naturally tend to interpret data using our own experience and knowledge. Thus we cannot expect the technical team to call all pieces of a car using the exact same terminology as the logistic department. This is why, our solution aims at giving the possibility to standardize the way in which the end user interact with the data without actually changing the source of the data.

Ask your Data Anything (ADA), allows companies to add a semantical layer on top of the data without the need of copying data. The product is managing term disambiguation, aggregation of data using hierarchies defined in ontologies, data integration between different data sources.

Ask Data Anything

Ask Data Anything is Cognitum's approach to exploring data by using a subset of natural language which articulates concepts and instances modeled in ontologies to provide a meaningful quering experience. Ask Data Anything seizes on regularities of language to provide a natural interpretation of queries being asked; its semantics are provided via R and rOntorion (alternatively  F# and Ontorion).

Technically, Ask Data Anything is capable of performing projection, sub-setting, grouping and aggregation operations, providing answers for queries involving the following information:

• What? Any of the columns of your data table are considered a quantitative field over which to perform queries,
• How? How the output is to be shown. The results of the query can be retrieved on either a table, histogram or a map,
• Where? (Optional) The "in" preposition allows to restrict the search to an specific named group of items  as happens for instance with continents which can be seeing as a group of countries,
• Of? (Optional) The "of" preposition allows to dive into the data, restricting the desired results to a certain set of types (concepts in the Fluent Editor sense) by searching the data in a certain column for instances (in Fluent Editor sense) of those types; we call this material sub-setting,
• By? (Optional) By which type (in Fluent Editor sense) you would like to group the results for aggregation purposes.
• When? (Optional) Queries can contain time constraints.