The authors present the results of a longitudinal investigation in the utilization of Linked Data technologies along the content value chain. The authors analyzed 71 papers in the period from 2006 to 2014 that used Linked data technologies in editorial workflows. By coding the primary and secondary research topics addressed in the paper the authors draw a conclusion of the maturity of Linked Data technologies as support systems along the content value chain. The survey indicates that Linked Data technologies are constantly maturing as a support infrastructure for editorial processes. The validity of the survey results for application domains not related to editorial tasks is open to discussion.
The growing recognition of Linked Data among the research
community as “Semantic Web done right” [
As illustrated in Figure 1 a survey about the occurrence of the phrase “Linked Data” in research publications of the ACM digital library from the period 2006 to 2014 reveals the growing popularity of this technological concept in the computer sciences till 2013 with a decline in 2014. Linked Data as a generic technology for data management is being applied across various application areas and industries, making it very hard to come to a general statement concerning its level of maturity and industry adoption. So is this distribution from figure 1 an indicator for the growing maturity of a research field? And if yes, how can this maturity be operationalized empirically? 100 0
Tassilo Pellegrini
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To tackle these questions the authors chose to analyze a subset of
research papers from the ACM database that address the
application of Linked Data within editorial workflows. This subset
allowed us to apply a unified classification scheme – known as the
content value chain [
The original concept of the value chain as developed by Michael
Porter in 1979 is used as an analytical framework for the analysis
of value creation processes at the firm level or the industry level
[
In this paper we refer to a generic abstraction of the content value
chain consisting of five steps: 1) content acquisition, 2) content
editing, 3) content bundling, 4) content distribution and 5) content
consumption. As illustrated by [
Content editing entails all necessary steps that deal with the semantic adaptation, interlinking and enrichment of data. Adaptation can be understood as a process in which acquired data is provided in a way that it can be used in the editorial process. Interlinking and enrichment are often performed via processes like tagging and/or referencing to enrich media documents either by disambiguating existing concepts or by providing background knowledge for deeper insights.
Content bundling is mainly concerned with the contextualization and personalization of information products. It can be used to provide customized access to media files i.e. by using metadata for the device-sensitive delivery of content, or to compile thematically relevant material into Landing Pages or Dossiers thus improving the navigability, findability and reuse of information.
In a Linked Data environment the process of content distribution mainly deals with the provision of machine-readable and semantically interoperable (meta)data via Application Programming Interfaces (APIs) or SPARQL Endpoints. These can be designed either to serve internal purposes so that data can be reused within controlled environments (i.e. within or between units) or for external purposes so that data can be shared between unknown users (i.e. as open SPARQL Endpoints on the Web). Content consumption entails any means that enable a human user to search for and interact with content items in a pleasant und purposeful way. So according to this view this level mainly deals with end user applications that make use of Linked Data to provide access to content i.e. by providing reasonable retrieval tools and/or visualizations.
The five steps of the content value chain comprise the classification scheme.
We selected a sample of 71 papers (out of 1921) dealing with the utilization of Linked Data in editorial workflows in the period from 2006 to 2014 from the ACM Digital Library (DL). The selected papers had to comply with the following criteria: 1) the work must analyse the utilization of Linked Data with reference to some sort of editorial workflow; and 2) the work must not be purely theoretical but provide at least a proof of concept. The relevant papers have then been analysed and clustered according to the five classes acquisition, editing, bundling, distribution, consumption. As most papers treated more than one of these topics we weighted each paper according to the primary and secondary topic discussed, thus also gaining a better understanding how the research topics relate to each other.
The weighted greyscale values have been calculated as follows. Given that black is 100%. 50% divided by the amount of papers with main classification (black) multiplied with the amount of the related classifications for the secondary classification. Figure 4 illustrates the results of our survey.
The main application areas of Linked Data in editorial workflows fall into the areas editing (23 papers), bundling (18 papers) and consumption (21 papers).
Crawling and leveraging processes could be subsumed as
acquisition process [
Scientific editing using algorithmic methods to classify data into separated, semantically enriched lists or ontologies were treated in 23 papers as main topic. All of these editing methods were part of a recognition process used for video-, text- or graphic- analysis in terms of media-analysis and enrichment of metadata. 18 papers concerned content bundling as main topic. Bundling can easily be defined as fine-grained representations of resource parts used for personalization and contextualization of the content. Just 4 papers described distributions for example in case of improved accessibility of information. The main difference to the content bundling process and the content consumption process explained later on, therefore was, that only APIs can access this data which in case of content bundling wasn't put to visualized graphs of the content. This low number of distributions is not significant for further conclusions. 21 papers applied Linked Data through a framework visualizing graph-based relations of links. This sort of standard for framework developers was to visualize links of Linked Data for purposes like content recommendation.
2006: We found just one paper in 2006 with relation to our research focus. This paper addressed content acquisition as main topic and editing issues as secondary topic. 2007: In 2007 one paper was classified treating content bundling as main topic and content acquisition as secondary topic. Two papers addressing content consumption as primary topic and acquisition, editing and bundling in treating only content consumption. 2008: In 2008 we determine one paper addressing content distribution and one paper addressing content consumption both referring to content editing. 2009: We have three papers classified as content editing, content bundling and content consumption. The subrelations in case of content bundling is editing and in case of content consumption the subrelations equally refer to content bundling and content distribution. 2010: In 2010 the authors detected one paper treating content acquisition, one paper treating content distribution and another one content consumption. Two papers treated content editing frameworks. All of the five papers treated content acquisition as their secondary topic. 2011: In 2011 one paper was about content acquisition, editing, distribution and content consumption. The relations begin in the content editing class including a single subrelation to content acquisition and content consumption. Four papers have all an equal amount of subrelations to content acquisition and editing. Additionally one paper described a framework for content consumption. 2012: In 2012 the authors found one paper addressing content acquisition as main topic and content editing as secondary topic. Two papers demonstrated the opposite pattern, discussing editing as main topic and acquisition as secondary topic. Four papers refer to content bundling with subrelations to content acquisition and content editing, while one of them also mentioned content distribution or content consumption as tertiary topic. Four papers address content consumption as main topic showing subrelations to content acquisition in all of their descriptions and one paper including further treatment of editing. 2013: All papers that describe content editing frameworks in the year of 2013 also have acquisitional processes as topic. One of three papers addressing content editing have a subrelation to content bundling. Two papers are subrelated to content distribution and one to content consumption. Only one paper related to content bundling subrelated to content acquisition and content editing. Four papers give reason to content consumption. Their relation to subclasses are three addressing content editing, two addressing content bundling and four addressing content consumption frameworks as main topic. 2014: In 2014 the classification scheme of the content value chain seems applicable to a huge amount of papers. We analysed 25 papers and came to the conclusion that scientific content editing utilizing combinations of vocabularies for the preparation of linked data is high of note, i.e. automatic extraction RDF-Triples from web sources for purposes of content enrichment. So 11 papers are classified as content editing in nearly all cases within acquisitional preprocessing. Content bundling with 5 papers and content consumption with 6 papers as main classification seem very similar spreaded in relation to the former years.
The results show a trend in the utilization of Linked Data
technologies towards content editing, content bundling and
content consumption. Especially the increasing amount of papers
addressing consumption purposes after 2009 is taken as an
indicator for the increasing maturity of Linked Data technologies
in editorial workflows. We also made out a reason of the
increasing usage of content acquisition processes beginning in
2008, assuming that the data infrastructure achieved reclaimable
integrity. Concerning the main result the intertwinedness of
research topics have seamless integration of distinct steps in the
content value chain. Metadata acquisition systems can minimize
the human burden in recording data [
To gain further insights the authors plan to extend the sample size of their survey in their future work. The current amount of 71 papers is simply too small to draw precise conclusions on the state of the art and future direction of Linked Data utilization in editorial workflows. But apart from these limitations the insights generated by the survey indicate that Linked Data technologies are constantly maturing as a support infrastructure for editorial processes. The validity of the survey results for application domains not related to editorial tasks is open to discussion.
Value of Report, Semantic Semantic