scholarly journals GRADI: A Graphical Database Interface for a Multimedia DBMS

Author(s):  
Daniel A. Keim ◽  
Vincent Lum
1986 ◽  
Vol 22 (6) ◽  
pp. 511-521 ◽  
Author(s):  
Clifford Burgess ◽  
Kathleen Swigger

1986 ◽  
Vol 11 (1-4) ◽  
pp. 355-359
Author(s):  
C.G. Burgess ◽  
W. Leigh ◽  
D. Ali

1991 ◽  
Author(s):  
Daniel A. Keim ◽  
Vincent Y. Lum

2005 ◽  
Vol 10 (5) ◽  
pp. 59-94
Author(s):  
Deja Hepziba Francis ◽  
Sanjay Madria ◽  
Chaman Sabharwal

2021 ◽  
pp. 1-13
Author(s):  
Daniel A. Contreras ◽  
Zachary Batist ◽  
Ciara Zogheib ◽  
Tristan Carter

Abstract The documentation and analysis of archaeological lithics must navigate a basic tension between examining and recording data on individual artifacts or on aggregates of artifacts. This poses a challenge both for artifact processing and for database construction. We present here an R Shiny solution that enables lithic analysts to enter data for both individual artifacts and aggregates of artifacts while maintaining a robust yet flexible data structure. This takes the form of a browser-based database interface that uses R to query existing data and transform new data as necessary so that users entering data of varying resolutions still produce data structured around individual artifacts. We demonstrate the function and efficacy of this tool (termed the Queryable Artifact Recording Interface [QuARI]) using the example of the Stelida Naxos Archaeological Project (SNAP), which, focused on a Paleolithic and Mesolithic chert quarry, has necessarily confronted challenges of processing and analyzing large quantities of lithic material.


2021 ◽  
Vol 12 (5) ◽  
Author(s):  
Alexandre F. Novello ◽  
Marco A. Casanova

A Natural Language Interface to Database (NLIDB) refers to a database interface that translates a question asked in natural language into a structured query. Aggregation questions express aggregation functions, such as count, sum, average, minimum and maximum, and optionally a group by clause and a having clause. NLIDBs deliver good results for standard questions but usually do not deal with aggregation questions. The main contribution of this article is a generic module, called GLAMORISE (GeneraL Aggregation MOdule using a RelatIonal databaSE), that extends NLIDBs to cope with aggregation questions. GLAMORISE covers aggregations with ambiguities, timescale differences, aggregations in multiple attributes, the use of superlative adjectives, basic recognition of measurement units, and aggregations in attributes with compound names.


2012 ◽  
Vol 05 (10) ◽  
pp. 789-796
Author(s):  
Corey Lawson ◽  
Kirk Larson ◽  
Jonathan Van Erdewyk ◽  
Christopher Smith ◽  
Al Rizzo ◽  
...  

1976 ◽  
Author(s):  
Ian M. Cuthill
Keyword(s):  

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