Schema-agnostic databases - Revision history

Jarble: link semantic parsing using Find link

2021-05-15T22:22:19Z

← Previous revision		Revision as of 22:22, 15 May 2021
Line 84:		Line 84:
	== Semantic complexity ==		== Semantic complexity ==

	As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.		As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of [[semantic parsing]] techniques over large, heterogeneous and schema-less databases.
	More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature.<ref name="freitasThesis"/><ref name="Mapping"/><ref name="Bischof"/> Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provide a probabilistic model on the semantic complexity of mapping schema-agnostic queries.		More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature.<ref name="freitasThesis"/><ref name="Mapping"/><ref name="Bischof"/> Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provide a probabilistic model on the semantic complexity of mapping schema-agnostic queries.

WOSlinker: change source to syntaxhighlight

2021-01-31T16:10:35Z

change source to syntaxhighlight

← Previous revision		Revision as of 16:10, 31 January 2021
Line 30:		Line 30:
	which maps to the following [[SPARQL]] query in the dataset vocabulary:		which maps to the following [[SPARQL]] query in the dataset vocabulary:

	<~~source~~ lang="sparql">		<syntaxhighlight lang="sparql">
	PREFIX : <http://dbpedia.org/resource/>		PREFIX : <http://dbpedia.org/resource/>
	PREFIX dbpedia2: <http://dbpedia.org/property/>		PREFIX dbpedia2: <http://dbpedia.org/property/>
Line 41:		Line 41:
	?x dbpedia2:spouse ?y .		?x dbpedia2:spouse ?y .
	}		}
			</syntaxhighlight>
	</source>

	==== Example 2 ====		==== Example 2 ====

	<~~source~~ lang="sparql">		<syntaxhighlight lang="sparql">
	SELECT ?x {		SELECT ?x {
	?x isA book .		?x isA book .
Line 52:		Line 52:
	FILTER (?p > 300)		FILTER (?p > 300)
	}		}
			</syntaxhighlight>
	</source>

	which maps to the following [[SPARQL]] query in the dataset vocabulary:		which maps to the following [[SPARQL]] query in the dataset vocabulary:

	<~~source~~ lang="sparql">		<syntaxhighlight lang="sparql">
	PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>		PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
	PREFIX : <http://dbpedia.org/resource/>		PREFIX : <http://dbpedia.org/resource/>
Line 67:		Line 67:
	FILTER(?p > 300)		FILTER(?p > 300)
	}		}
			</syntaxhighlight>
	</source>

	=== Schema-agnostic keyword queries ===		=== Schema-agnostic keyword queries ===

Kku: link semantic matching using Find link

2019-05-02T15:44:13Z

link semantic matching using Find link

← Previous revision		Revision as of 15:44, 2 May 2019
Line 1:		Line 1:
	'''Schema-agnostic databases''' or '''vocabulary-independent databases''' aim at supporting users to be abstracted from the representation of the data, supporting the automatic semantic matching between queries and [[database]]s. '''Schema-agnosticism''' is the property of a database of mapping a query issued with the user terminology and structure, automatically mapping it to the dataset vocabulary.		'''Schema-agnostic databases''' or '''vocabulary-independent databases''' aim at supporting users to be abstracted from the representation of the data, supporting the automatic [[semantic matching]] between queries and [[database]]s. '''Schema-agnosticism''' is the property of a database of mapping a query issued with the user terminology and structure, automatically mapping it to the dataset vocabulary.

	The increase in the size and in the semantic heterogeneity of database schemas bring new requirements for users querying and searching [[structured data]]. At this scale it can become unfeasible for data consumers to be familiar with the representation of the data in order to query it. At the center of this discussion is the [[semantic gap]] between users and databases, which becomes more central as the scale and complexity of the data grows.		The increase in the size and in the semantic heterogeneity of database schemas bring new requirements for users querying and searching [[structured data]]. At this scale it can become unfeasible for data consumers to be familiar with the representation of the data in order to query it. At the center of this discussion is the [[semantic gap]] between users and databases, which becomes more central as the scale and complexity of the data grows.

Gulumeemee: Reverted 1 edit by 2600:8807:2D01:AE0:4451:35D4:AB61:731F identified as test/vandalism using STiki

2018-08-25T10:07:00Z

Reverted 1 edit by 2600:8807:2D01:AE0:4451:35D4:AB61:731F identified as test/vandalism using STiki

← Previous revision		Revision as of 10:07, 25 August 2018
Line 22:		Line 22:
	==== Example 1 ====		==== Example 1 ====
	<pre>		<pre>
			SELECT ?y {
	SELECT ?y {f_‘³4ƒYÜÒÍ/—_ð:LÆ)‰åe„ôŒS–÷M–é_Ò0Ý''''''Bold text'''''Italic text'''''
	BillClinton hasDaughter ?x .		BillClinton hasDaughter ?x .
	?x marriedTo ?y .		?x marriedTo ?y .

2600:8807:2D01:AE0:4451:35D4:AB61:731F: ÿy>_'_OÃWz×™‘ÖÒÂ°ç_†ÉÇè’d†ø_7_ÆÎÒè[zRš—éiª_&ÿð_$·2z”Ó1C]6^¡žåèC„„¸êÏ:_ÿ±}_,_]A&ßÛïóÈN¢ñ²-œ_Ä

2018-08-25T06:43:40Z

ÿy>_'_OÃWz×™‘ÖÒÂ°ç_†ÉÇè’d†ø_7_ÆÎÒè[zRš—éiª_&ÿð_$·2z”Ó1C]6^¡žåèC„„¸êÏ:_ÿ±}_,_]A&ßÛïóÈN¢ñ²-œ_Ä

← Previous revision		Revision as of 06:43, 25 August 2018
Line 22:		Line 22:
	==== Example 1 ====		==== Example 1 ====
	<pre>		<pre>
			SELECT ?y {f_‘³4ƒYÜÒÍ/—_ð:LÆ)‰åe„ôŒS–÷M–é_Ò0Ý''''''Bold text'''''Italic text'''''
	SELECT ?y {
	BillClinton hasDaughter ?x .		BillClinton hasDaughter ?x .
	?x marriedTo ?y .		?x marriedTo ?y .

Magioladitis: /* Semantic complexity */Improved article to match Manual of Style, References after punctuation per WP:CITEFOOT and WP:PAIC using AWB (12151)

2017-05-02T07:33:07Z

Semantic complexity: Improved article to match Manual of Style, References after punctuation per WP:CITEFOOT and WP:PAIC using AWB (12151)

← Previous revision		Revision as of 07:33, 2 May 2017
Line 85:		Line 85:

	As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.		As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.
	More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature<ref name="freitasThesis"/><ref name="Mapping"/><ref name="Bischof"/>. Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provide a probabilistic model on the semantic complexity of mapping schema-agnostic queries.		More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature.<ref name="freitasThesis"/><ref name="Mapping"/><ref name="Bischof"/> Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provide a probabilistic model on the semantic complexity of mapping schema-agnostic queries.

	== References ==		== References ==

Cedar101: /* Schema-agnostic structured queries */ source lang="sparql"

2017-04-27T00:48:57Z

Schema-agnostic structured queries: source lang="sparql"

← Previous revision		Revision as of 00:48, 27 April 2017
Line 20:		Line 20:
	Consist of schema-agnostic queries following the syntax of a structured standard (for example [[SQL]], [[SPARQL]]). The syntax and semantics of operators are maintained, while different terminologies are used.		Consist of schema-agnostic queries following the syntax of a structured standard (for example [[SQL]], [[SPARQL]]). The syntax and semantics of operators are maintained, while different terminologies are used.

	==== Example ====		==== Example 1 ====
	<pre>		<pre>
	SELECT ?y {		SELECT ?y {
Line 30:		Line 30:
	which maps to the following [[SPARQL]] query in the dataset vocabulary:		which maps to the following [[SPARQL]] query in the dataset vocabulary:

			<source lang="sparql">
	<pre>
	PREFIX : <http://dbpedia.org/resource/>		PREFIX : <http://dbpedia.org/resource/>
	PREFIX dbpedia2: <http://dbpedia.org/property/>		PREFIX dbpedia2: <http://dbpedia.org/property/>
Line 41:		Line 41:
	?x dbpedia2:spouse ?y .		?x dbpedia2:spouse ?y .
	}		}
	</~~pre~~>		</source>

	==== ~~Examples~~ ====		==== Example 2 ====

			<source lang="sparql">
	<pre>
	SELECT ?x {		SELECT ?x {
	?x isA book .		?x isA book .
Line 52:		Line 52:
	FILTER (?p > 300)		FILTER (?p > 300)
	}		}
			</source>

	</pre>

	which maps to the following [[SPARQL]] query in the dataset vocabulary:		which maps to the following [[SPARQL]] query in the dataset vocabulary:

			<source lang="sparql">
	<pre>
	PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>		PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
	PREFIX : <http://dbpedia.org/resource/>		PREFIX : <http://dbpedia.org/resource/>
Line 68:		Line 67:
	FILTER(?p > 300)		FILTER(?p > 300)
	}		}
	</~~pre~~>		</source>

	=== Schema-agnostic keyword queries ===		=== Schema-agnostic keyword queries ===

Julianoens: consolidating references.

2017-04-19T19:18:04Z

consolidating references.

← Previous revision		Revision as of 19:18, 19 April 2017
Line 5:		Line 5:
	== Description ==		== Description ==

	The evolution of data environments towards the consumption of data from multiple data sources and the growth in the ''schema size'', ''complexity'', ''dynamicity'' and ''decentralisation'' (SCoDD) of schemas<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf "Schema-agnostic queries over large-schema databases: a distributional semantics approach"] PhD Thesis, 2015</ref><ref>Pat Helland, ["If you have too much data, then 'good enough' is good enough"], Commun. ACM 54(6): 40–47, 2011.</ref><ref>M. L. Brodie and J. T. Liu, ["The power and limits of relational technology in the age of information ecosystems"], Keynote, On The Move Federated Conferences, Heraklion, Greece, October 25–29, 2010.</ref> increases the complexity of contemporary data management. The SCoDD trend emerges as a central data management concern in [[Big data\|Big Data]] scenarios, where users and applications have a demand for more complete data, produced by independent data sources, under different semantic assumptions and contexts of use, which is the typical scenario for [[Semantic Web]] Data applications.		The evolution of data environments towards the consumption of data from multiple data sources and the growth in the ''schema size'', ''complexity'', ''dynamicity'' and ''decentralisation'' (SCoDD) of schemas<ref name="freitasThesis">A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf "Schema-agnostic queries over large-schema databases: a distributional semantics approach"] PhD Thesis, 2015</ref><ref>Pat Helland, ["If you have too much data, then 'good enough' is good enough"], Commun. ACM 54(6): 40–47, 2011.</ref><ref>M. L. Brodie and J. T. Liu, ["The power and limits of relational technology in the age of information ecosystems"], Keynote, On The Move Federated Conferences, Heraklion, Greece, October 25–29, 2010.</ref> increases the complexity of contemporary data management. The SCoDD trend emerges as a central data management concern in [[Big data\|Big Data]] scenarios, where users and applications have a demand for more complete data, produced by independent data sources, under different semantic assumptions and contexts of use, which is the typical scenario for [[Semantic Web]] Data applications.

	The evolution of databases in the direction of heterogeneous data environments strongly impacts the usability, [[semiotics]] and semantic assumptions behind existing data accessibility methods such as structured queries, keyword-based search and visual query systems. With schema-less databases containing potentially millions of dynamically changing attributes, it becomes unfeasible for some users to become aware of the 'schema' or vocabulary in order to query the database. At this scale, the effort in understanding the schema in order to build a structured query can become prohibitive.		The evolution of databases in the direction of heterogeneous data environments strongly impacts the usability, [[semiotics]] and semantic assumptions behind existing data accessibility methods such as structured queries, keyword-based search and visual query systems. With schema-less databases containing potentially millions of dynamically changing attributes, it becomes unfeasible for some users to become aware of the 'schema' or vocabulary in order to query the database. At this scale, the effort in understanding the schema in order to build a structured query can become prohibitive.
Line 14:		Line 14:

	The development of approaches to support [[natural language user interface\|natural language interfaces]] (NLI) over databases have aimed towards the goal of schema-agnostic queries. Complementarily, some approaches based on keyword search have targeted keyword-based queries which express more complex information needs. Other approaches have explored the construction of structured queries over databases where schema constraints can be relaxed. All these approaches (natural language, keyword-based search and structured queries) have targeted different degrees of sophistication in addressing the problem of supporting a flexible semantic matching between queries and data, which vary from the completely absence of the semantic concern to more principled semantic models.		The development of approaches to support [[natural language user interface\|natural language interfaces]] (NLI) over databases have aimed towards the goal of schema-agnostic queries. Complementarily, some approaches based on keyword search have targeted keyword-based queries which express more complex information needs. Other approaches have explored the construction of structured queries over databases where schema constraints can be relaxed. All these approaches (natural language, keyword-based search and structured queries) have targeted different degrees of sophistication in addressing the problem of supporting a flexible semantic matching between queries and data, which vary from the completely absence of the semantic concern to more principled semantic models.
	While the demand for schema-agnosticism has been an implicit requirement across semantic search and natural language query systems over structured data, it is not sufficiently individuated as a concept and as a necessary requirement for contemporary database management systems. Recent works have started to define and model the semantic aspects involved on schema-agnostic queries.<ref~~>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf~~ "~~Schema-agnostic queries over large-schema databases: a distributional semantics approach~~"~~] PhD Thesis, 2015<~~/~~ref~~><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref>		While the demand for schema-agnosticism has been an implicit requirement across semantic search and natural language query systems over structured data, it is not sufficiently individuated as a concept and as a necessary requirement for contemporary database management systems. Recent works have started to define and model the semantic aspects involved on schema-agnostic queries.<ref name="freitasThesis"/><ref name="Mapping">A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref name="Bischof">S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref>

	=== Schema-agnostic structured queries ===		=== Schema-agnostic structured queries ===
Line 86:		Line 86:

	As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.		As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.
	More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature.<ref~~>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf~~ "~~Schema-agnositc queries over large-schema databases: a distributional semantics approach~~"~~] PhD Thesis, 2015<~~/~~ref~~><ref~~>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf,~~ "~~On the Semantic~~ Mapping ~~of Schema-agnostic Queries: A Preliminary Study~~"~~], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.<~~/~~ref~~><ref~~>S.~~ Bischof~~, M. Kroetzsch, A. Polleres, S. Rudolph, [~~"~~Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.<~~/~~ref~~> Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> ~~provides~~ a probabilistic model on the semantic complexity of mapping schema-agnostic queries.		More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature<ref name="freitasThesis"/><ref name="Mapping"/><ref name="Bischof"/>. Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provide a probabilistic model on the semantic complexity of mapping schema-agnostic queries.

	== References ==		== References ==

Cherkash: clean up using AWB

2017-04-17T09:37:33Z

clean up using AWB

← Previous revision		Revision as of 09:37, 17 April 2017
Line 5:		Line 5:
	== Description ==		== Description ==

	The evolution of data environments towards the consumption of data from multiple data sources and the growth in the ''schema size'', ''complexity'', ''dynamicity'' and ''decentralisation'' (SCoDD) of schemas <ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf ~~“Schema~~-agnostic queries over large-schema databases: a distributional semantics ~~approach”~~] PhD Thesis, 2015</ref><ref>Pat Helland, ["If you have too much data, then 'good enough' is good enough"], Commun. ACM 54(6): 40–47, 2011.</ref><ref>M. L. Brodie and J. T. Liu, ["The power and limits of relational technology in the age of information ecosystems"], Keynote, On The Move Federated Conferences, Heraklion, Greece, October 25–29, 2010.</ref> increases the complexity of contemporary data management. The SCoDD trend emerges as a central data management concern in [[Big data\|Big Data]] scenarios, where users and applications have a demand for more complete data, produced by independent data sources, under different semantic assumptions and contexts of use, which is the typical scenario for [[Semantic Web]] Data applications.		The evolution of data environments towards the consumption of data from multiple data sources and the growth in the ''schema size'', ''complexity'', ''dynamicity'' and ''decentralisation'' (SCoDD) of schemas<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf "Schema-agnostic queries over large-schema databases: a distributional semantics approach"] PhD Thesis, 2015</ref><ref>Pat Helland, ["If you have too much data, then 'good enough' is good enough"], Commun. ACM 54(6): 40–47, 2011.</ref><ref>M. L. Brodie and J. T. Liu, ["The power and limits of relational technology in the age of information ecosystems"], Keynote, On The Move Federated Conferences, Heraklion, Greece, October 25–29, 2010.</ref> increases the complexity of contemporary data management. The SCoDD trend emerges as a central data management concern in [[Big data\|Big Data]] scenarios, where users and applications have a demand for more complete data, produced by independent data sources, under different semantic assumptions and contexts of use, which is the typical scenario for [[Semantic Web]] Data applications.

	The evolution of databases in the direction of heterogeneous data environments strongly impacts the usability, [[semiotics]] and semantic assumptions behind existing data accessibility methods such as structured queries, keyword-based search and visual query systems. With schema-less databases containing potentially millions of dynamically changing attributes, it becomes unfeasible for some users to become aware of the `schema' or vocabulary in order to query the database. At this scale, the effort in understanding the schema in order to build a structured query can become prohibitive.		The evolution of databases in the direction of heterogeneous data environments strongly impacts the usability, [[semiotics]] and semantic assumptions behind existing data accessibility methods such as structured queries, keyword-based search and visual query systems. With schema-less databases containing potentially millions of dynamically changing attributes, it becomes unfeasible for some users to become aware of the 'schema' or vocabulary in order to query the database. At this scale, the effort in understanding the schema in order to build a structured query can become prohibitive.

	== Schema-agnostic queries ==		== Schema-agnostic queries ==
Line 14:		Line 14:

	The development of approaches to support [[natural language user interface\|natural language interfaces]] (NLI) over databases have aimed towards the goal of schema-agnostic queries. Complementarily, some approaches based on keyword search have targeted keyword-based queries which express more complex information needs. Other approaches have explored the construction of structured queries over databases where schema constraints can be relaxed. All these approaches (natural language, keyword-based search and structured queries) have targeted different degrees of sophistication in addressing the problem of supporting a flexible semantic matching between queries and data, which vary from the completely absence of the semantic concern to more principled semantic models.		The development of approaches to support [[natural language user interface\|natural language interfaces]] (NLI) over databases have aimed towards the goal of schema-agnostic queries. Complementarily, some approaches based on keyword search have targeted keyword-based queries which express more complex information needs. Other approaches have explored the construction of structured queries over databases where schema constraints can be relaxed. All these approaches (natural language, keyword-based search and structured queries) have targeted different degrees of sophistication in addressing the problem of supporting a flexible semantic matching between queries and data, which vary from the completely absence of the semantic concern to more principled semantic models.
	While the demand for schema-agnosticism has been an implicit requirement across semantic search and natural language query systems over structured data, it is not sufficiently individuated as a concept and as a necessary requirement for contemporary database management systems. Recent works have started to define and model the semantic aspects involved on schema-agnostic queries.<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf ~~“Schema~~-agnostic queries over large-schema databases: a distributional semantics ~~approach”~~] PhD Thesis, 2015</ref><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref>		While the demand for schema-agnosticism has been an implicit requirement across semantic search and natural language query systems over structured data, it is not sufficiently individuated as a concept and as a necessary requirement for contemporary database management systems. Recent works have started to define and model the semantic aspects involved on schema-agnostic queries.<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf "Schema-agnostic queries over large-schema databases: a distributional semantics approach"] PhD Thesis, 2015</ref><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref>

	=== Schema-agnostic structured queries ===		=== Schema-agnostic structured queries ===
Line 86:		Line 86:

	As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.		As of 2016 the concept of schema-agnostic queries has been developed primarily in academia. Most of schema-agnostic query systems have been investigated in the context of [[Natural language user interface\|Natural Language Interfaces]] over databases or over the [[Semantic Web]].<ref>Unger et al., ["Introduction to Question Answering over Linked Data"], In Proceedings of the 2014 Reasoning Web Summer School, 2014</ref> These works explore the application of semantic parsing techniques over large, heterogeneous and schema-less databases.
	More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature.<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf ~~“Schema~~-agnositc queries over large-schema databases: a distributional semantics ~~approach”~~] PhD Thesis, 2015</ref><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref> Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provides a probabilistic model on the semantic complexity of mapping schema-agnostic queries.		More recently, the individuation of the concept of schema-agnostic query systems and databases have appeared more explicitly within the literature.<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf "Schema-agnositc queries over large-schema databases: a distributional semantics approach"] PhD Thesis, 2015</ref><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref> Freitas et al.<ref>A. Freitas, J. E. Sales, S. Handschuh, E. Curry, [http://andrefreitas.org/papers/preprint_iwcs_2015.pdf "How hard is the Query? Measuring the Semantic Complexity of Schema-Agnostic Queries"], In Proceedings of the 11th International Conference on Computational Semantics (IWCS), London, 2015.</ref> provides a probabilistic model on the semantic complexity of mapping schema-agnostic queries.

	== References ==		== References ==

Leonardossouza at 13:24, 8 March 2017

2017-03-08T13:24:49Z

← Previous revision		Revision as of 13:24, 8 March 2017
Line 14:		Line 14:

	The development of approaches to support [[natural language user interface\|natural language interfaces]] (NLI) over databases have aimed towards the goal of schema-agnostic queries. Complementarily, some approaches based on keyword search have targeted keyword-based queries which express more complex information needs. Other approaches have explored the construction of structured queries over databases where schema constraints can be relaxed. All these approaches (natural language, keyword-based search and structured queries) have targeted different degrees of sophistication in addressing the problem of supporting a flexible semantic matching between queries and data, which vary from the completely absence of the semantic concern to more principled semantic models.		The development of approaches to support [[natural language user interface\|natural language interfaces]] (NLI) over databases have aimed towards the goal of schema-agnostic queries. Complementarily, some approaches based on keyword search have targeted keyword-based queries which express more complex information needs. Other approaches have explored the construction of structured queries over databases where schema constraints can be relaxed. All these approaches (natural language, keyword-based search and structured queries) have targeted different degrees of sophistication in addressing the problem of supporting a flexible semantic matching between queries and data, which vary from the completely absence of the semantic concern to more principled semantic models.
	While the demand for schema-agnosticism has been an implicit requirement across semantic search and natural language query systems over structured data, it is not sufficiently individuated as a concept and as a necessary requirement for contemporary database management systems. Recent works have started to define and model the semantic aspects involved on schema-agnostic queries.<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf “Schema-~~agnositc~~ queries over large-schema databases: a distributional semantics approach”] PhD Thesis, 2015</ref><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref>		While the demand for schema-agnosticism has been an implicit requirement across semantic search and natural language query systems over structured data, it is not sufficiently individuated as a concept and as a necessary requirement for contemporary database management systems. Recent works have started to define and model the semantic aspects involved on schema-agnostic queries.<ref>A. Freitas, [http://andrefreitas.org/papers/thesis_schema_agnostic.pdf “Schema-agnostic queries over large-schema databases: a distributional semantics approach”] PhD Thesis, 2015</ref><ref>A. Freitas, J. C. Pereira Da Silva, E. Curry, [http://andrefreitas.org/papers/schema_agnostic_i_final_version.pdf, "On the Semantic Mapping of Schema-agnostic Queries: A Preliminary Study"], Workshop of the Natural Language Interfaces for the Web of Data (NLIWoD), 13th International Semantic Web Conference (ISWC), Rival del Garda, 2014.</ref><ref>S. Bischof, M. Kroetzsch, A. Polleres, S. Rudolph, ["Schema-Agnostic Query Rewriting in SPARQL 1.1"], In Proceedings of the 13th International Semantic Web Conference. Springer 2014.</ref>

	=== Schema-agnostic structured queries ===		=== Schema-agnostic structured queries ===