58,968 research outputs found
Object-oriented querying of existing relational databases
In this paper, we present algorithms which allow an object-oriented
querying of existing relational databases. Our goal is to provide an improved query
interface for relational systems with better query facilities than SQL. This
seems to be very important since, in real world applications, relational systems
are most commonly used and their dominance will remain in the near future. To
overcome the drawbacks of relational systems, especially the poor query facilities
of SQL, we propose a schema transformation and a query translation algorithm.
The schema transformation algorithm uses additional semantic information to enhance
the relational schema and transform it into a corresponding object-oriented
schema. If the additional semantic information can be deducted from an underlying
entity-relationship design schema, the schema transformation may be done
fully automatically. To query the created object-oriented schema, we use the
Structured Object Query Language (SOQL) which provides declarative query facilities
on objects. SOQL queries using the created object-oriented schema are
much shorter, easier to write and understand and more intuitive than corresponding
S Q L queries leading to an enhanced usability and an improved querying of
the database. The query translation algorithm automatically translates SOQL queries
into equivalent SQL queries for the original relational schema
Compensation methods to support cooperative applications: A case study in automated verification of schema requirements for an advanced transaction model
Compensation plays an important role in advanced transaction models, cooperative work and workflow systems. A schema designer is typically required to supply for each transaction another transaction to semantically undo the effects of . Little attention has been paid to the verification of the desirable properties of such operations, however. This paper demonstrates the use of a higher-order logic theorem prover for verifying that compensating transactions return a database to its original state. It is shown how an OODB schema is translated to the language of the theorem prover so that proofs can be performed on the compensating transactions
Semantic validation in spatio-temporal schema integration
This thesis proposes to address the well-know database integration problem with a new method that combines functionality from database conceptual modeling techniques with functionality from logic-based reasoners. We elaborate on a hybrid - modeling+validation - integration approach for spatio-temporal information integration on the schema level. The modeling part of our methodology is supported by the spatio-temporal conceptual model MADS, whereas the validation part of the integration process is delegated to the description logics validation services. We therefore adhere to the principle that, rather than extending either formalism to try to cover all desirable functionality, a hybrid system, where the database component and the logic component would cooperate, each one performing the tasks for which it is best suited, is a viable solution for semantically rich information management. First, we develop a MADS-based flexible integration approach where the integrated schema designer has several viable ways to construct a final integrated schema. For different related schema elements we provide the designer with four general policies and with a set of structural solutions or structural patterns within each policy. To always guarantee an integrated solution, we provide for a preservation policy with multi-representation structural pattern. To state the inter-schema mappings, we elaborate on a correspondence language with explicit spatial and temporal operators. Thus, our correspondence language has three facets: structural, spatial, and temporal, allowing to relate the thematic representation as well as the spatial and temporal features. With the inter-schema mappings, the designer can state correspondences between related populations, and define the conditions that rule the matching at the instance level. These matching rules can then be used in query rewriting procedures or to match the instances within the data integration process. We associate a set of putative structural patterns to each type of population correspondence, providing a designer with a patterns' selection for flexible integrated schema construction. Second, we enhance our integration method by employing validation services of the description logic formalism. It is not guaranteed that the designer can state all the inter-schema mappings manually, and that they are all correct. We add the validation phase to ensure validity and completeness of the inter-schema mappings set. Inter-schema mappings cannot be validated autonomously, i.e., they are validated against the data model and the schemas they link. Thus, to implement our validation approach, we translate the data model, the source schemas and the inter-schema mappings into a description logic formalism, preserving the spatial and temporal semantics of the MADS data model. Thus, our modeling approach in description logic insures that the model designer will correctly define spatial and temporal schema elements and inter-schema mappings. The added value of the complete translation (i.e., including the data model and the source schemas) is that we validate not only the inter-schema mappings, but also the compliance of the source schemas to the data model, and infer implicit relationships within them. As the result of the validation procedure, the schema designer obtains the complete and valid set of inter-schema mappings and a set of valid (flexible) schematic patterns to apply to construct an integrated schema that meets application requirements. To further our work, we model a framework in which a schema designer is able to follow our integration method and realize the schema integration task in an assisted way. We design two models, UML and SEAM models, of a system that provides for integration functionalities. The models describe a framework where several tools are employed together, each involved in the service it is best suited for. We define the functionalities and the cooperation between the composing elements of the framework and detail the logics of the integration process in an UML activity diagram and in a SEAM operation model
Implementing Database Coordination in P2P Networks
We are interested in the interaction of databases in Peer-to-Peer (P2P) networks. In this paper we propose a new solution for P2P databases, that we call database coordination. We see coordination as managing semantic interdependencies among databases at runtime. We propose a data coordination model where the notions of Interest Groups and Acquaintances play the most crucial role. Interest groups support the formation of peers according to data models they have in common; and acquaintances allow for peers inter-operation. Finally, we present an architecture supporting database coordination and show how it is implemented on top of JXTA
Believe It or Not: Adding Belief Annotations to Databases
We propose a database model that allows users to annotate data with belief
statements. Our motivation comes from scientific database applications where a
community of users is working together to assemble, revise, and curate a shared
data repository. As the community accumulates knowledge and the database
content evolves over time, it may contain conflicting information and members
can disagree on the information it should store. For example, Alice may believe
that a tuple should be in the database, whereas Bob disagrees. He may also
insert the reason why he thinks Alice believes the tuple should be in the
database, and explain what he thinks the correct tuple should be instead.
We propose a formal model for Belief Databases that interprets users'
annotations as belief statements. These annotations can refer both to the base
data and to other annotations. We give a formal semantics based on a fragment
of multi-agent epistemic logic and define a query language over belief
databases. We then prove a key technical result, stating that every belief
database can be encoded as a canonical Kripke structure. We use this structure
to describe a relational representation of belief databases, and give an
algorithm for translating queries over the belief database into standard
relational queries. Finally, we report early experimental results with our
prototype implementation on synthetic data.Comment: 17 pages, 10 figure
Bridging the Semantic Gap with SQL Query Logs in Natural Language Interfaces to Databases
A critical challenge in constructing a natural language interface to database
(NLIDB) is bridging the semantic gap between a natural language query (NLQ) and
the underlying data. Two specific ways this challenge exhibits itself is
through keyword mapping and join path inference. Keyword mapping is the task of
mapping individual keywords in the original NLQ to database elements (such as
relations, attributes or values). It is challenging due to the ambiguity in
mapping the user's mental model and diction to the schema definition and
contents of the underlying database. Join path inference is the process of
selecting the relations and join conditions in the FROM clause of the final SQL
query, and is difficult because NLIDB users lack the knowledge of the database
schema or SQL and therefore cannot explicitly specify the intermediate tables
and joins needed to construct a final SQL query. In this paper, we propose
leveraging information from the SQL query log of a database to enhance the
performance of existing NLIDBs with respect to these challenges. We present a
system Templar that can be used to augment existing NLIDBs. Our extensive
experimental evaluation demonstrates the effectiveness of our approach, leading
up to 138% improvement in top-1 accuracy in existing NLIDBs by leveraging SQL
query log information.Comment: Accepted to IEEE International Conference on Data Engineering (ICDE)
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