The sheer volume of electronic documents being published on the Web can be overwhelming for users if the searching aspect is not properly addressed. This problem is particularly acute inside archives and repositories containing large collections of web resources or, more precisely, web pages and other web objects. Using the existing search capabilities in web archives, results can be compromised because of the size of data, content heterogeneity and changes in scientific terminologies and meanings. During the course of this research, we will explore whether semantic web technologies, particularly ontology-based annotation and retrieval, could improve precision in search results in multi-disciplinary web archives

Khan, Arshad

Martin, David J.

Tiropanis, Thanassis

English

Southampton (e-Prints Soton)

Using Semantic Indexing to Improve Searching Performance in Web Archives Arshad Khan*, David MartinΨ, and Thanassis TiropanisΨ *National Centre for Research Methods (NCRM), University of Southampton Southampton, UK  Email: a.khan@soton.ac.uk  Ψ Geography and Environment, University of Southampton, Southampton, UK  Email: D.J.Martin@soton.ac.uk  Ψ School of Electronics & Computer Sciences (ECS), University of Southampton, Southampton UK Email: tt2@ecs.soton.ac.uk   Abstract—The sheer volume of electronic documents being published on the  Web can  be overwhelming for  users if the searching  aspect  is  not  properly  addressed.  This  problem  is particularly acute inside archives and repositories containing large  collections  of  web  resources  or,  more  precisely,  web pages  and  other  web  objects.  Using  the  existing  search capabilities  in  web  archives,  results  can  be  compromised because of the size of data, content heterogeneity and changes in scientific terminologies and meanings. During the course of this  research,  we  will  explore  whether  semantic  web technologies,  particularly  ontology-based  annotation  and retrieval, could improve precision in search results in  multi-disciplinary web archives. Keywords—Semantic indexing; archive searching; multi-disciplinary web archives; semantic searching; linked data I. INTRODUCTION  Information  scientists  have  long  been  struggling  to find  a  system  that  can  help  them  organize  disparate collections of web archives (or, in a general sense, web resource  archives)  so  that  users  can  have  access  to complete  and  coherent  collections  [1]  in  a  much  more meaningful  way.  Although both  web archives and  web repositories  are  sometimes  used  to  refer  to  archives  of web resources, the term web archive will be used through the remainder of this paper. The prevalent access in web archives is based on the search over automatically extracted metadata from web documents  [2]  which  have  to  be  indexed  for  keyword searching. Providing broader access (unlike the current keyword search) to the collection of those web archives via  an  ontological  framework  structure  could  not  only increase the utilization of these hard-earned resources but also  make  them  more  research-oriented,  structured  and flexible  to  cope  with  the  changing  needs  of  users  [1], especially the research community. The problem with conventional text based searching in web archives is that it only categorises the content in the archive on the basis of instance occurrence and query weighting  with  no  attention  paid  to  context,  relevance, terminological  coherence  or  relationship  between  web pages, nor does it relate the web pages of the repository to external sources on the web of data.  Web resources archives contain complex collections of  research  materials  in  online  domains  that  can  serve distinct  communities,  for  example  social  scientists  or historians  who  desire  to  search  information  based  on contextual  and  provenance  information  [3].  We understand  that  semantic  web  technologies  will  be  of tremendous  help  in  identifying  and  integrating  such heterogeneous  documents  inside  web  archives  and enabling context and meaning-based search in them by exploiting  existing  vocabularies  and  domain-specific ontologies. To  further  investigate  the  above  issues,  a  thorough review  of  the  most  relevant  research  was  carried  out under the umbrella of web archiving, searching strategies in  web archives and the application of  next generation semantic web technologies. Particular attention has been given to linked data to see if users’ searching experience could be improved by locating more precise and relevant information in web archives and repositories. In almost all  cases,  past  research  has  focused  on  individual components of a typical web page in a particular domain such  as  semantically  annotating  and  linking  research datasets  in  biology,  e.g.,  [4]  multimedia  objects  in  a newspaper archive, or [5] research publications (usually in proprietary formats) in scientific publication archives, to  generate  semantic  metadata  and  generate  improved search results. This paper will describe the application and extension of  keyword  searching  in  web  archives  of  multi-disciplinary research data  by annotating web documents using  more  specialized  and  archival  domain-specific ontologies and subsequently searching over the annotated metadata  and  instances  of  data  i.e.  Knowledge  Base (KB).  We  will  also  take  into  account  the  existing  and widely  used  classification  systems  e.g.,  thesaurus, typologies and taxonomies of social science to see if they can be synthesized into building an annotation ontology for creating annotation metadata. II. CORE AREA OF RESEARCH The development of a single on-line resource built by subject experts (e.g., a site presenting the methods and results  from  a  research  project  in  a  social  science discipline) can be time-consuming and expensive (in part, because they are not IT experts) and the full value of the resource only comes into play close to the point at which project  funding  ends.  Those  online  resources  not  only provide  a  valuable  personal  development  resource  for researchers wishing to benefit from the training or data provided,  but  also  provide  an  important  repository  of social, economic, historical and human knowledge. They are  frequently  created  as  the  end-product  of  particular projects  by  academics  and  researchers  associated  with particular disciplines.  Following the completion of a project, the materials contained in some of these resources are considered for archival purposes so that they remain available despite the end of funding and dispersal of  teams.  This is an increasingly familiar situation as funders and institutions seek to develop repositories to increase the impact and availability of their work.  Such archives or repositories of web resources enable users to search for information in the  collection  using  basic  keyword  searching  which proves to be ineffective simply because they retrieve web pages, datasets, and research papers merely on the basis of incidental mentions of a term in users’ queries.  Such a searching  strategy  misses  the  context,  relationship, historical  details  and  other  attributes  of  a  particular resource which would have enabled users to extend their exploration to other related records in the archive. One such web resources repository is the ReStore repository [6]  which  will  be  used  as  a  test-bed  for  the experimentation  and  search  performance  evaluation described here.    Figure 1: An overview of web resource, creation, development and its archival into a web resource archive, e.g., ReStore repository   Figure 1 shows a typical web resource development and  archival  process  involving  funding  of  a  research project,  development  of  a  web  resource  by  the  project team  based  in  higher  education  institutions,  and  the archival of the resource in a web archive such as ReStore repository. Figure 1 also presents an opportunity to think about the problem which may arise at the time of searching the respective  archive  having  different  online  materials created as part of various social science research projects.  III. THE PROBLEM Some of the frequently observed problems stemming from the current searching methodologies include, but are not limited to:   The  typical  keyword-search,  usually  based  on keyword-matching  or  phrase-matching  algorithms, hardly  takes  into  account  context,  relevance  and relationship  between  web  documents,  data,  people, organizations, projects and other artefacts.    Too many web pages make it almost impossible for users to go through and look for relevant information as a result of searching.   The  outputs  of  the  same  research  project  may  be spread out over several repository/archive services, e.g.,  published  research  papers  uploaded  to  an institutional repository, core research data uploaded to  another  data  management  service  such  as Economic  &  Social  Data  Service  (ESDS)  and videos/audios  uploaded  to  video  sharing  services such as YouTube, Google videos etc.  Essentially,  the  content  of  valuable  online  resource collections  becomes  disintegrated  and  spread  across different  online  archives.  These  are  in  most  cases findable  by  standard  search  engines  but  with  no classification  hierarchy  or  associated  relationships  that links to their siblings (parts of the same web resource) or external, related objects that could be made available to users. An example would be research on a similar topic undertaken  either  in  the  past  or  currently.  Similarly,  a research  funding  organization  may  be  funding  another project in the same field or related workshops may have been offered as part of different projects.  These types of relationship  are  well  understood  by  the  academic researcher  but  not  readily  amenable  to  discovery  via existing searchable metadata.  IV. EXPERIMENTAL SETUP The  overall  purpose  of  this  research  is  to  establish whether  accuracy  and  relevance  in  search  results  are improved  both  at  system  level  and  in  terms  of  user experience  when  searching  for  information  in  a repository  of  web  resources  having  a  meaningful semantic index.  We  have  outlined  the  current  state  of  searching  in website  archives  which  largely  employ  only  keyword-based searching techniques to retrieve information. We are  now  able  to  formulate  the  following  research questions  which  will  act  as  a  driving  force  for  this particular research.   1.  Can keyword-based searching be applied to semantically indexed metadata created by the semantic annotation process to enhance information retrieval in web resource archives? 2.  Can domain-specific terms in an Ontology and their expressions in KB improve precision and recall in search results when added to the keywords search? 3.  Does semantic indexing of ontology and KB along with inferencing cater to the heterogeneous types of data contained in web archives in terms of relationships, relevance? 4.  Does the scale of searching over large multi-disciplinary web resources in web archives effect system performance in terms of the number of queries submitted at a particular point of time and the time it takes for the system to retrieve relevant information from multiple data sources? It is important to remember that in all of the above, users of such archives have to be kept in the forefront of the research as they will be the ultimate beneficiaries of any new systems based on such research in the future.   V. PROPOSED ONTOLOGY-BASED SEARCHING SYSTEM Figure  2  shows  the  building  blocks  of  the experimentation  environment  which  will  enable  us  to conduct various experiments and evaluate search results performance in different scenarios.  The  results  have  to  be  evaluated  while  keeping  in view  traditional  RDBMS  keyword-based  searching techniques  which  are  usually  applied  in  many  web resources archives including the ReStore repository.  Figure 2 shows basic components of the experimental setup  including  KIM  (Knowledge  &  Information Management) platform  with  inherent  support of GATE (General  Architecture  for  Text  Engineering),  Open source  full-text  search  engine  Lucene,    ReStore repository  domain  ontology  fully  mapped  to  KIM ontology  and  the  resulting  semantic  metadata  or  RDF triples store with searching interface on top of it. It also follows that by incorporating the existing semantic web technologies and linked data concepts, we can enhance searching  performance  in  web  archives.  A  quantitative approach  towards  measuring  performance  has  been adopted to evaluate accuracy of search results. Sesame RDF repository will be an OWLIM semantic repository  for  managing  RDF  triples  in  addition  to inferencing  and  SPARQL  query  evaluation  during  the course of various experimentation.                                                          Figure 2: Proposed Semantic indexing based searching architecture built on KIM platform incorporating RDF(s) Sesame semantic repository and distributed (shared) ontological framework.  VI. THE CHALLENGE OF SCALE Annotation  of  web  documents  containing  different types of data on a large scale is certainly an issue, but the presence  of  a  well-modelled  ontology  representing  the domain  of  interest  could  address  that  issue  to  a  large extent.  Also  the  trend  of  submitting  lengthy  search queries  [7]  is  making  it  increasingly  difficult  for keyword-based search engines to perform well as users are  becoming  more  and  more  interested  in  the  context precision,  related  information  and  the  source  and provenance of what is being searched.  The challenge is therefore of  improving performance of  the  keyword-based  search  using  semantics  without losing  search  scalability  [8]  and  users’  interaction experience,  to  which they have become accustomed as the  web  has  become  an  essential  component  of  their lives.  However  it  still  remains  to  be  seen  whether  the different  environments  in  which  web  resources  have originally  been  created  (e.g.,  web  served,  harvested  or manually  collected),  archived  and  indexed  could influence  the  accuracy  of  results  and  performance  of systems. During  our  experimental  setup  we  will  analyse  the above from different perspectives in order to support our research and solidify the basis of our findings. We have already  started  the  actual  annotation  work  along  with indexing and retrieval of information. We have already made progress in formulating the research framework and will proceed to undertake it in order to be able to evaluate performance  in  different  scenarios,  e.g.,  scale, heterogeneity  of  documents  and  retrieval  of  related information. VII. ONTOLOGY ARCHITECTURE OF RESTORE REPOSITORY In Figure 3, we have put together very basic terms and concepts (classes, properties) in a container with a view to mapping and extending them to other ontologies and storing the resulting annotation metadata (instances of  classes  or  KB  together  in  the  form  of  integrated ontologies. The KB and mapped network of ontologies are assumed to be searched at a time to produce relevant and accurate results with a view to evolving it iteratively as  new  terms  are  added.  GATE  will  process structured/semi-structured  content  in  documents  and OWLIM  represents  RDF  triple  store  containing inference,  querying  engine  for  information  retrieval.  Figure 3: ReStore synthetic ontology architecture to be integrated into the KIM’s bootstrap ontology KIMO to aid in (a) annotating domain-specific (Social Science Research Methods) resources in ReStore repository (b) searching relevant information in integrated ontologies. VIII. CONCLUSION AND FUTURE WORK The  core  purpose  of  conducting  this  research  is  to find out if searching over the content of archived  web resources could produce more accurate, meaningful and trust-worthy results by using semantic web technologies and  linked  data  techniques.  In  today’s  world  of  blogs, wikis,  CMSs  and  social  networking,  the  speed  of publishing information on the web has greatly increased thereby  affecting  information  consumption  due  to information overload. The problem is particularly acute in relation to web resources developed as part of specific research projects.  Despite their value, in most cases these disappear from the effective  searching spectrum due to non-availability  of  meaningful  metadata  (except  basic bibliographic page-specific metadata), lack of linkage to contemporary research and lack of full exposure to the mainstream web. Such highly specialised web resources become  almost  un-searchable,  or  in  some  cases misrepresented in search results in web  archives where searching  is  performed  using  keywords  matching algorithms.  This  paper  describes  a  research  agenda  which  is focused on the addition of extra semantic meaning to the existing content of a web resources archive (in our case the  Restore  repository  so  as  to  permit  more  effective searching which takes account of similar content within and beyond their parental domain in order to make them part of the structured and meaningful web of data.   ACKNOWLEDGMENT The authors acknowledge the support of ESRC Award No. RES-576-25-0023. REFERENCES  [1]  P. Wu, A. Heok, and I. Tamsir, “Annotating the Web Archives–An Exploration of Web Archives Cataloging and  Semantic  Web,”  Digital  Libraries:  Achievements, Challenges and Opportunities, pp. 12-21, 2006. [2]  M. Costa, and M. Silva, "Towards information retrieval evaluation over web archives." pp. 37-38. [3]  P.  H.  J.  Wu,  A.  K.  H.  Heok,  and  I.  P.  Tamsir, “Annotating Web archives—structure, provenance, and context  through  archival  cataloguing,”  New  Review  of Hypermedia and Multimedia, vol. 13, no. 1, pp. 55-75, 2007/07/01, 2007. [4]  C. Berkley, S. Bowers, M. B. Jones, J. S. Madin, and M. Schildhauer,  "Improving  data  discovery  in  metadata repositories  through  semantic  search,"  Proceedings  of the  International  Conference  on  Complex,  Intelligent and Software Intensive Systems, CISIS 2009. pp. 1152-1159. [5]  P. Castells, F. Perdrix, E. Pulido, M. Rico, R. Benjamins, J.  Contreras,  and  J.  Lorés,  "Neptuno:  Semantic  Web Technologies for a Digital Newspaper Archive," Lecture Notes  in  Computer  Science  C.  Bussler,  J.  Davies,  D. Fensel  et  al.,  eds.,  pp.  445-458:  Springer  Berlin  / Heidelberg, 2004. [6]  "ReStore  repository:  A  sustainable  web  resources repository," 14/01/2013, 2013; http://www.restore.ac.uk. [7]  M.  A.  Hearst,  “'Natural'  Search  User  Interfaces,” Communications of the ACM, vol. 54, no. 11, pp. 60-6767, Nov., 2011. [8]  S. Kara, Ö. Alan, O. Sabuncu, S. Akpınar, N. K. Cicekli, and F. N. Alpaslan, “An ontology-based retrieval system using semantic indexing,” Information Systems, 2011.   

Annotating the Web Archives–An Exploration of Web Archives Cataloging and Semantic Web,” Digital Libraries: Achievements, Challenges and Opportunities,

Annotating Web archives—structure, provenance, and context through archival cataloguing,”

Improving data discovery in metadata repositories through semantic search,&quot;

Neptuno: Semantic Web Technologies for a Digital Newspaper Archive,&quot;

Towards information retrieval evaluation over web archives.&quot;

Using semantic indexing to improve searching 
performance in web archives

he sheer volume of electronic documents being published on the Web can be overwhelming for users if the searching aspect is not properly addressed. This problem is particularly acute inside archives and repositories containing large collections of web resources or, more precisely, web pages and other web objects. Using the existing search capabilities in web archives, results can be compromised because of the size of data, content heterogeneity and changes in scientific terminologies and meanings. During the course of this research, we will explore whether semantic web technologies, particularly ontology-based annotation and retrieval, could improve precision in search results in multi-disciplinary web archives

Martin, David

National Centre for Research Methods: NCRM EPrints Repository

Using Semantic Indexing to Improve Searching Performance in Web Archives Arshad Khan*, David MartinΨ, and Thanassis TiropanisΨ *National Centre for Research Methods (NCRM), University of Southampton Southampton, UK  Email: a.khan@soton.ac.uk  Ψ Geography and Environment, University of Southampton, Southampton, UK  Email: D.J.Martin@soton.ac.uk  Ψ School of Electronics & Computer Sciences (ECS), University of Southampton, Southampton UK Email: tt2@ecs.soton.ac.uk   Abstract—The sheer volume of electronic documents being published on the Web can be overwhelming for users if the searching aspect is not properly addressed. This problem is particularly acute inside archives and repositories containing large collections of web resources or, more precisely, web pages and other web objects. Using the existing search capabilities in web archives, results can be compromised because of the size of data, content heterogeneity and changes in scientific terminologies and meanings. During the course of this research, we will explore whether semantic web technologies, particularly ontology-based annotation and retrieval, could improve precision in search results in multi-disciplinary web archives. Keywords—Semantic indexing; archive searching; multi-disciplinary web archives; semantic searching; linked data I. INTRODUCTION  Information scientists have long been struggling to find a system that can help them organize disparate collections of web archives (or, in a general sense, web resource archives) so that users can have access to complete and coherent collections [1] in a much more meaningful way. Although both web archives and web repositories are sometimes used to refer to archives of web resources, the term web archive will be used through the remainder of this paper. The prevalent access in web archives is based on the search over automatically extracted metadata from web documents [2] which have to be indexed for keyword searching. Providing broader access (unlike the current keyword search) to the collection of those web archives via an ontological framework structure could not only increase the utilization of these hard-earned resources but also make them more research-oriented, structured and flexible to cope with the changing needs of users [1], especially the research community. The problem with conventional text based searching in web archives is that it only categorises the content in the archive on the basis of instance occurrence and query weighting with no attention paid to context, relevance, terminological coherence or relationship between web pages, nor does it relate the web pages of the repository to external sources on the web of data.  Web resources archives contain complex collections of research materials in online domains that can serve distinct communities, for example social scientists or historians who desire to search information based on contextual and provenance information [3]. We understand that semantic web technologies will be of tremendous help in identifying and integrating such heterogeneous documents inside web archives and enabling context and meaning-based search in them by exploiting existing vocabularies and domain-specific ontologies. To further investigate the above issues, a thorough review of the most relevant research was carried out under the umbrella of web archiving, searching strategies in web archives and the application of next generation semantic web technologies. Particular attention has been given to linked data to see if users’ searching experience could be improved by locating more precise and relevant information in web archives and repositories. In almost all cases, past research has focused on individual components of a typical web page in a particular domain such as semantically annotating and linking research datasets in biology, e.g., [4] multimedia objects in a newspaper archive, or [5] research publications (usually in proprietary formats) in scientific publication archives, to generate semantic metadata and generate improved search results. This paper will describe the application and extension of keyword searching in web archives of multi-disciplinary research data  by annotating web documents using more specialized and archival domain-specific ontologies and subsequently searching over the annotated metadata and instances of data i.e. Knowledge Base (KB). We will also take into account the existing and widely used classification systems e.g., thesaurus, typologies and taxonomies of social science to see if they can be synthesized into building an annotation ontology for creating annotation metadata. 101Copyright (c) IARIA, 2013.     ISBN:  978-1-61208-248-6WEB 2013 : The First International Conference on Building and Exploring Web Based EnvironmentsII. CORE AREA OF RESEARCH The development of a single on-line resource built by subject experts (e.g., a site presenting the methods and results from a research project in a social science discipline) can be time-consuming and expensive (in part, because they are not IT experts) and the full value of the resource only comes into play close to the point at which project funding ends. Those online resources not only provide a valuable personal development resource for researchers wishing to benefit from the training or data provided, but also provide an important repository of social, economic, historical and human knowledge. They are frequently created as the end-product of particular projects by academics and researchers associated with particular disciplines.  Following the completion of a project, the materials contained in some of these resources are considered for archival purposes so that they remain available despite the end of funding and dispersal of teams.  This is an increasingly familiar situation as funders and institutions seek to develop repositories to increase the impact and availability of their work.  Such archives or repositories of web resources enable users to search for information in the collection using basic keyword searching which proves to be ineffective simply because they retrieve web pages, datasets, and research papers merely on the basis of incidental mentions of a term in users’ queries.  Such a searching strategy misses the context, relationship, historical details and other attributes of a particular resource which would have enabled users to extend their exploration to other related records in the archive. One such web resources repository is the ReStore repository [6] which will be used as a test-bed for the experimentation and search performance evaluation described here.    Figure 1: An overview of web resource, creation, development and its archival into a web resource archive, e.g., ReStore repository   Figure 1 shows a typical web resource development and archival process involving funding of a research project, development of a web resource by the project team based in higher education institutions, and the archival of the resource in a web archive such as ReStore repository. Figure 1 also presents an opportunity to think about the problem which may arise at the time of searching the respective archive having different online materials created as part of various social science research projects.  III. THE PROBLEM Some of the frequently observed problems stemming from the current searching methodologies include, but are not limited to:  The typical keyword-search, usually based on keyword-matching or phrase-matching algorithms, hardly takes into account context, relevance and relationship between web documents, data, people, organizations, projects and other artefacts.   Too many web pages make it almost impossible for users to go through and look for relevant information as a result of searching.  The outputs of the same research project may be spread out over several repository/archive services, e.g., published research papers uploaded to an institutional repository, core research data uploaded to another data management service such as Economic & Social Data Service (ESDS) and videos/audios uploaded to video sharing services such as YouTube, Google videos etc.  Essentially, the content of valuable online resource collections becomes disintegrated and spread across different online archives. These are in most cases findable by standard search engines but with no classification hierarchy or associated relationships that links to their siblings (parts of the same web resource) or external, related objects that could be made available to users. An example would be research on a similar topic undertaken either in the past or currently. Similarly, a research funding organization may be funding another project in the same field or related workshops may have been offered as part of different projects.  These types of relationship are well understood by the academic researcher but not readily amenable to discovery via existing searchable metadata.  IV. EXPERIMENTAL SETUP The overall purpose of this research is to establish whether accuracy and relevance in search results are improved both at system level and in terms of user experience when searching for information in a repository of web resources having a meaningful semantic index.  We have outlined the current state of searching in website archives which largely employ only keyword-based searching techniques to retrieve information. We 102Copyright (c) IARIA, 2013.     ISBN:  978-1-61208-248-6WEB 2013 : The First International Conference on Building and Exploring Web Based Environmentsare now able to formulate the following research questions which will act as a driving force for this particular research.   1. Can keyword-based searching be applied to semantically indexed metadata created by the semantic annotation process to enhance information retrieval in web resource archives? 2. Can domain-specific terms in an Ontology and their expressions in KB improve precision and recall in search results when added to the keywords search? 3. Does semantic indexing of ontology and KB along with inferencing cater to the heterogeneous types of data contained in web archives in terms of relationships, relevance? 4. Does the scale of searching over large multi-disciplinary web resources in web archives effect system performance in terms of the number of queries submitted at a particular point of time and the time it takes for the system to retrieve relevant information from multiple data sources? It is important to remember that in all of the above, users of such archives have to be kept in the forefront of the research as they will be the ultimate beneficiaries of any new systems based on such research in the future.   V. PROPOSED ONTOLOGY-BASED SEARCHING SYSTEM Figure 2 shows the building blocks of the experimentation environment which will enable us to conduct various experiments and evaluate search results performance in different scenarios.  The results have to be evaluated while keeping in view traditional RDBMS keyword-based searching techniques which are usually applied in many web resources archives including the ReStore repository.  Figure 2 shows basic components of the experimental setup including KIM (Knowledge & Information Management) platform with inherent support of GATE (General Architecture for Text Engineering), Open source full-text search engine Lucene,  ReStore repository domain ontology fully mapped to KIM ontology and the resulting semantic metadata or RDF triples store with searching interface on top of it. It also follows that by incorporating the existing semantic web technologies and linked data concepts, we can enhance searching performance in web archives. A quantitative approach towards measuring performance has been adopted to evaluate accuracy of search results. Sesame RDF repository will be an OWLIM semantic repository for managing RDF triples in addition to inferencing and SPARQL query evaluation during the course of various experimentation.                                                          Figure 2: Proposed Semantic indexing based searching architecture built on KIM platform incorporating RDF(s) Sesame semantic repository and distributed (shared) ontological framework.  VI. THE CHALLENGE OF SCALE Annotation of web documents containing different types of data on a large scale is certainly an issue, but the presence of a well-modelled ontology representing the domain of interest could address that issue to a large extent. Also the trend of submitting lengthy search queries [7] is making it increasingly difficult for keyword-based search engines to perform well as users are becoming more and more interested in the context precision, related information and the source and provenance of what is being searched.  The challenge is therefore of  improving performance of the keyword-based search using semantics without losing search scalability [8] and users’ interaction experience, to which they have become accustomed as the web has become an essential component of their lives. However it still remains to be seen whether the different environments in which web resources have originally been created (e.g., web served, harvested or manually collected), archived and indexed could influence the accuracy of results and performance of systems. During our experimental setup we will analyse the above from different perspectives in order to support our research and solidify the basis of our findings. We have 103Copyright (c) IARIA, 2013.     ISBN:  978-1-61208-248-6WEB 2013 : The First International Conference on Building and Exploring Web Based Environmentsalready started the actual annotation work along with indexing and retrieval of information. We have already made progress in formulating the research framework and will proceed to undertake it in order to be able to evaluate performance in different scenarios, e.g., scale, heterogeneity of documents and retrieval of related information. VII. ONTOLOGY ARCHITECTURE OF RESTORE REPOSITORY In Figure 3, we have put together very basic terms and concepts (classes, properties) in a container with a view to mapping and extending them to other ontologies and storing the resulting annotation metadata (instances of classes or KB together in the form of integrated ontologies. The KB and mapped network of ontologies are assumed to be searched at a time to produce relevant and accurate results with a view to evolving it iteratively as new terms are added. GATE will process structured/semi-structured content in documents and OWLIM represents RDF triple store containing inference, querying engine for information retrieval.  Figure 3: ReStore synthetic ontology architecture to be integrated into the KIM’s bootstrap ontology KIMO to aid in (a) annotating domain-specific (Social Science Research Methods) resources in ReStore repository (b) searching relevant information in integrated ontologies. VIII. CONCLUSION AND FUTURE WORK The core purpose of conducting this research is to find out if searching over the content of archived web resources could produce more accurate, meaningful and trust-worthy results by using semantic web technologies and linked data techniques. In today’s world of blogs, wikis, CMSs and social networking, the speed of publishing information on the web has greatly increased thereby affecting information consumption due to information overload. The problem is particularly acute in relation to web resources developed as part of specific research projects.  Despite their value, in most cases these disappear from the effective searching spectrum due to non-availability of meaningful metadata (except basic bibliographic page-specific metadata), lack of linkage to contemporary research and lack of full exposure to the mainstream web. Such highly specialised web resources become almost un-searchable, or in some cases misrepresented in search results in web archives where searching is performed using keywords matching algorithms.  This paper describes a research agenda which is focused on the addition of extra semantic meaning to the existing content of a web resources archive (in our case the Restore repository so as to permit more effective searching which takes account of similar content within and beyond their parental domain in order to make them part of the structured and meaningful web of data.   ACKNOWLEDGMENT The authors acknowledge the support of ESRC Award No. RES-576-25-0023. REFERENCES  [1] P. Wu, A. Heok, and I. Tamsir, “Annotating the Web Archives–An Exploration of Web Archives Cataloging and Semantic Web,” Digital Libraries: Achievements, Challenges and Opportunities, pp. 12-21, 2006. [2] M. Costa, and M. Silva, "Towards information retrieval evaluation over web archives." pp. 37-38. [3] P. H. J. Wu, A. K. H. Heok, and I. P. Tamsir, “Annotating Web archives—structure, provenance, and context through archival cataloguing,” New Review of Hypermedia and Multimedia, vol. 13, no. 1, pp. 55-75, 2007/07/01, 2007. [4] C. Berkley, S. Bowers, M. B. Jones, J. S. Madin, and M. Schildhauer, "Improving data discovery in metadata repositories through semantic search," Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009. pp. 1152-1159. [5] P. Castells, F. Perdrix, E. Pulido, M. Rico, R. Benjamins, J. Contreras, and J. Lorés, "Neptuno: Semantic Web Technologies for a Digital Newspaper Archive," Lecture Notes in Computer Science C. Bussler, J. Davies, D. Fensel et al., eds., pp. 445-458: Springer Berlin / Heidelberg, 2004. [6] "ReStore repository: A sustainable web resources repository," 14/01/2013, 2013; http://www.restore.ac.uk. [7] M. A. Hearst, “'Natural' Search User Interfaces,” Communications of the ACM, vol. 54, no. 11, pp. 60-6767, Nov., 2011. [8] S. Kara, Ö. Alan, O. Sabuncu, S. Akpınar, N. K. Cicekli, and F. N. Alpaslan, “An ontology-based retrieval system using semantic indexing,” Information Systems, 2011.   104Copyright (c) IARIA, 2013.     ISBN:  978-1-61208-248-6WEB 2013 : The First International Conference on Building and Exploring Web Based Environments

Using Semantic Indexing to Improve Searching Performance in Web Archives

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Using semantic indexing to improve searching performance in web archives

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