Changeset 3240
- Timestamp:
- 08/06/13 08:52:24 (11 years ago)
- Location:
- SMC4LRT/chapters
- Files:
-
- 2 edited
- 2 moved
Legend:
- Unmodified
- Added
- Removed
-
SMC4LRT/chapters/Design_SMCinstance.tex
r3233 r3240 2 2 3 3 4 \subsection{Linked Data - Express dataset in RDF} 5 6 4 Linked Data - Express dataset in RDF 5 6 \begin{quotation} 7 7 I do think that ISOcat, CLAVAS, RELcat, an actual language 8 8 resource all provide a part of the semantic network. … … 15 15 that's where I'm ultimately heading with all these registries related to 16 16 semantic interoperability ... I hope ;-) 17 \end{quotation} 17 18 \todocite{Menzo} 18 19 19 20 20 Partly as by-product of the entities-mapping effort we will get the metadata -descriptionrendered in RDF, linked with21 Partly as by-product of the entities-mapping effort we will get the metadata rendered in RDF, linked with 21 22 So theoretically we then only need to provide them ``on the web'', to make them a nucleus of the LinkedData-Cloud. 22 23 … … 304 305 305 306 306 \s ection{RELcat - Ontological relations}307 \subsection{RELcat - Ontological relations} 307 308 Information in RELcat is already stored in RDF (Schuurman, Windhouwer 2011). One relation from the example relation set for CMDI : 308 309 isocat:DC-2538 rel:sameAs dce:date. … … 336 337 337 338 338 \section{SMC LOD }339 \section{SMC LOD - Semantic Web Application} 339 340 340 341 \todoin{read: Europeana RDF Store Report} … … 357 358 \todocode{Load data: relcat, clavas, olac-and-dc-providers cmd, lt-world?} 358 359 359 360 361 362 360 \section{Summary} 361 362 363 -
SMC4LRT/chapters/Design_SMCschema.tex
r3233 r3240 1 1 2 \chapter{S emantic Mapping Component - Design}2 \chapter{System Design - Mapping on schema level} 3 3 \label{ch:design} 4 4 … … 8 8 9 9 10 \todoin{appendix: reference architecture} 11 12 13 \section{Data Model?} 14 15 Terms ? 16 move to SKOS ? 17 18 RDF 19 20 \subsection{CMD namespace} 10 \begin{note} 11 Do we need separate \\section{Data Model}? 21 12 Describe the CMD-format? 13 \end{note} 14 15 \begin{figure*}[!ht] 16 \includegraphics[width=0.8\textwidth]{images/SMC_modules.png} 17 \caption{The process of transforming the CMD metadata records to and RDF representation} 18 \label{fig:smc_modules} 19 \end{figure*} 20 21 For broader context see the reference architecture diagram in Figure \ref{fig:ref_arch}. 22 23 24 \subsection{Use Cases} 25 26 \begin{itemize} 27 28 \item MD Search employing Semantic Mapping 29 \item MD Search employing Fuzzy Search 30 \end{itemize} 31 32 \section{Crosswalks -- Mapping on schema level} 33 34 merging the pieces of information provided by those, 35 offering them semi-transaprently to the user (or application) on the consumption side. 36 37 a module of the Component Metadata Infrastructure performing semantic mapping on search indexes. This builds the base for query expansion to facilitate semantic search and enhance recall when querying the Metadata Repository. 22 38 23 39 … … 66 82 %So we disambiguate (or narrow down the ambiguity) by prefixing context. 67 83 68 69 \subsection{Query language} 70 CQL? 71 72 73 \section{Crosswalks -- Mapping on schema level} 74 75 merging the pieces of information provided by those, 76 offering them semi-transaprently to the user (or application) on the consumption side. 77 78 a module of the Component Metadata Infrastructure performing semantic mapping on search indexes. This builds the base for query expansion to facilitate semantic search and enhance recall when querying the Metadata Repository. 79 84 \subsection{Interface Specification} 80 85 81 86 In this section, we describe the actual task of the proposed application -- \textbf{mapping indexes to indexes} -- in abstract terms. The returned mappings can be used by other applications to expand or translate the original user query, to match elements in other schemas. … … 125 130 \verb| Person.Name, Person.FullName]| 126 131 132 \subsection{Initialization} 133 134 First there is an initialization phase, in which the application fetches the information from the source modules (cf. \ref{components}). All profiles and components from the Component Registry are read and all the URIs to data categories are extracted to construct an inverted map of data categories: 135 \newline 136 137 \textit{datcatURI $\mapsto$ profile.component.element[]} 138 \newline 139 140 The collected data categories are enriched with information from corresponding registries (DCRs), adding the verbose identifier, the description and available translations into other working languages. %, usable as base for multi-lingual search user-interface. 141 142 Finally relation sets defined in the Relation Registry are fetched and matched with the data categories in the map to create sets of semantically equivalent (or otherwise related) data categories. 143 127 144 128 145 \subsection{Extensions} … … 135 152 Also, use of \emph{other than equivalency relations will necessitate more complex logic in the query expansion and accordingly also more complex response of the SMC, either returning the relation types themselves as well or equip the list of indexes with some similarity ratio.} 136 153 137 \subsection{Initialization}138 139 First there is an initialization phase, in which the application fetches the information from the source modules (cf. \ref{components}). All profiles and components from the Component Registry are read and all the URIs to data categories are extracted to construct an inverted map of data categories:140 \newline141 142 \textit{datcatURI $\mapsto$ profile.component.element[]}143 \newline144 145 The collected data categories are enriched with information from corresponding registries (DCRs), adding the verbose identifier, the description and available translations into other working languages. %, usable as base for multi-lingual search user-interface.146 147 Finally relation sets defined in the Relation Registry are fetched and matched with the data categories in the map to create sets of semantically equivalent (or otherwise related) data categories.148 154 149 155 … … 163 169 Controlled Vocabularies 164 170 Synonym Expansion (via TermExtraction(ContentSet)) 171 172 173 \subsection{Query language} 174 CQL? 165 175 166 176 … … 181 191 182 192 183 \s ection{User Interface?}184 185 \subs ection*{Query Input}186 187 \subs ection*{Columns}188 189 \subs ection*{Summaries}190 191 \subs ection*{Differential Views}193 \subsection{User Interface?} 194 195 \subsubsection*{Query Input} 196 197 \subsubsection*{Columns} 198 199 \subsubsection*{Summaries} 200 201 \subsubsection*{Differential Views} 192 202 Visualize impact of given mapping in terms of covered dataset (number of matched records). 193 203 194 \subs ection*{Visualization}204 \subsubsection*{Visualization} 195 205 Landscape, Treemap, SOM 196 206 197 Ontology Mapping and Alignement / saiks/Ontology4 4auf1.pdf 198 199 \section{Semantic Mapping in Metadata vs. Content/Annotation} 200 AF + DCR + RR 207 \todoin{check Ontology Mapping and Alignement / saiks/Ontology4 4auf1.pdf} 208 201 209 202 210 \section{Summary} -
SMC4LRT/chapters/Results.tex
r3233 r3240 1 \chapter{Results} 2 \label{ch:results} 3 4 \section{Use Cases} 5 6 \begin{itemize} 7 8 \item MD Search employing Semantic Mapping 9 \item MD Search employing Fuzzy Search 10 \item Visualization of the Results - ? 11 \end{itemize} 12 13 A trivial example for a concept-based query expansion: 14 Confronted with a user query: \texttt{Actor.Name = Sue} and knowing that \texttt{Actor} is equivalent or similar to \texttt{Person} and \texttt{Name} is synonym to \texttt{FullName} the expanded query could look like: 15 \texttt{Actor.Name = Sue OR Actor.FullName = Sue OR Person.Name = Sue OR Person.FullName= is Sue} 16 17 Another example concerning instance mapping: the user looking for all resource produced by or linked to a given institution, does not have to guess or care for various spellings of the name of the institution used in the description of the resources, but rather can browse through a controlled vocabulary of institutions and see all the resources of given institution. While this could be achieved by simple normalizing of the literal-values (and indeed that definitely has to be one processing step), the linking to an ontology enables to user to also continue browsing the ontology to find institutions that are related to the original institution by means of being concerned with similar topics and retrieve a union of resources for such resulting cluster. Thus in general the user is enabled to work with the data based on information that is not present in the original dataset. 18 19 20 \section{Research Questions } 1 \chapter{Evaluation} 2 \label{ch:Evaluation} 21 3 22 4 … … 155 137 156 138 139 \section{Summary} 157 140 158 \section{SMC-Browser Advanced Interactive User Interface} 141 142 143 \chapter{Results} 144 \label{ch:results} 145 146 147 \section { Software module} 148 149 The core function of the SMC is implemented as a set of XSL-stylesheets, with auxiliary functionality (like caching or a wrapping web service) being provided by a wrapping application implemented in Java. There is also a plan to provide an XQuery implementation. The SMC module is being maintained in the CMDI code repository\footnote {\url{http://svn.clarin.eu/SMC}}. 150 151 152 \subsection{SMC Browser -- Advanced Interactive User Interface} 159 153 160 154 Explore the Component Metadata Framework … … 171 165 172 166 167 \section{Discussion} 168 169 \subsection{Semantic Mapping in Metadata vs. Content/Annotation} 170 AF + DCR + RR 171 172 173 \section{Summary} 174 175 173 176 \begin{figure*}[!ht] 174 177 \includegraphics[width=1\textwidth]{images/screen_SMC-Browser_2013-01-23} -
SMC4LRT/chapters/appendix.tex
r2703 r3240 14 14 \todocite{DCR data model} 15 15 16 \begin{figure*}[!ht] 17 \begin{center} 18 \includegraphics[width=1\textwidth]{images/EDC_components_v4.png} 19 \end{center} 20 \caption{Reference Architecture} 21 \label{fig:ref_arch} 22 \end{figure*}
Note: See TracChangeset
for help on using the changeset viewer.