=Paper=
{{Paper
|id=Vol-1769/paper06
|storemode=property
|title=Semantic Wikis Versioning with BiFröST
|pdfUrl=https://ceur-ws.org/Vol-1769/paper06.pdf
|volume=Vol-1769
|authors=Krzysztof Kutt
|dblpUrl=https://dblp.org/rec/conf/aiia/Kutt16
}}
==Semantic Wikis Versioning with BiFröST==
https://ceur-ws.org/Vol-1769/paper06.pdf
Semantic Wikis Versioning with BiFröST
Krzysztof Kutt?
AGH University of Science and Technology
Al. Mickiewicza 30, 30-059 Krakow, Poland,
kkutt@agh.edu.pl
Abstract. One of the powerful and popular tools that are used to sup-
port Collaborative Knowledge Engineering are Semantic Wikis. They
are easily accessible and provide ACL mechanisms, but they lack a good
versioning mechanism. In this paper an extended version of such a mech-
anism is proposed. Besides elements that appear in every Wiki system,
like simple changelog and place for discussion, it incorporates changes
ontologies, rich metadata, semantic metrics and reasoning unit tests. All
of them are gathered into the form of the provenance graph that can be
serialized into Turtle syntax and (automatically) analyzed. First proto-
type of such a mechanism for Loki wiki called BiFröST was developed.
Keywords: semantic wikis, collaborative knowledge engineering, knowl-
edge evaluation, change management
1 Introduction and Motivation
Knowledge bases are created not by a single knowledge engineers, but by a team
of people who either sit in the same room (in a company) or people who do not
even know each other (as in the Wikipedia project1 ). It can therefore be easily
seen that there is a need to move from traditional Knowledge Engineering (KE)
to Collaborative Knowledge Engineering (CKE) and to consider issues related
to the collaborativeness.
Primarily, following issues should be taken into account, cf. [12]: (1) The
sources vary in the knowledge of the topic, in the same way the user do. Is it
possible to identify which of them are better? (2) Conflicts in collaborative set-
ting are natural. People in general and experts in particular may have different
views on the same subject. Conflicts can also arise from the bad will of some
users: they can consciously enter incorrect information to the knowledge base,
e.g. vandalism on Wikipedia. How can we resolve conflicts? (3) There are differ-
ent kinds of users and different types of changes: some users aim at enhancing
the knowledge base, the other ones at bringing coherence, and still others at
improving text quality. Is there a way to identify them and use in some way?
Among tools that support CKE teams and tries to address these issues are:
(a) WebProtégé2 , a collaborative version of open source ontology editing tool
?
The author pursues his doctorate under the supervision of Grzegorz J. Nalepa.
1
See: https://www.wikipedia.org/.
2
See: http://webprotege.stanford.edu/.
Protégé that was used, inter alia, in the process of the International Classification
of Diseases (ICD-11) preparation, where 270 doctors have worked together on the
base that consists of 45k classes [14], (b) Noctua3 , another online tool, which
provides knowledge validation by interacting with users. System creates user
profiles and then asks questions related to each one’s field of knowledge or interest
(e.g. “Could you write something about X?”) [2], and many more.
In this paper, one specific group of tools that supports CKE teams will be con-
sidered. They are called Semantic Wikis and they are quite interesting because
of their popularity (see section 2). Like traditional wikis, they are conceptually
simple but powerful for massive cooperation, and also provide a semantic layer on
which one can define concepts and relations that are easily machine-understand.
What is important from the CKE point of view, is the fact that every Wiki
system has integrated collaboration mechanisms such as ACL (Access Control
Lists), which allows for gaining different access levels for different users and
version control for tracking all changes that was done within wiki pages. Among
Semantic Wikis’ drawbacksis the fact that they provide only simple “straight”
changelogs in which all versions are saved with small comments, as well as some
place to discuss editions, but nothing more. This is not enough to really support
CKE within wikis, because “classical” changelog does not provides any way to
specify used resources nor to automatically evaluate conflicts.
In this paper extended versioning mechanism for Semantic Wikis is proposed
with taking care of CKE collaborative issues presented above. It is based on a
semantic graph in which changes are related to each other as well as to some
additional information, what gives a possibility to automatically analyse the
changelog and provide some feedback about collaboration quality.
The rest of the text is structured as follows. In part 2 Semantic Wiki systems
and their capabilities are characterized. Section 3 outlines the approach. The
paper is concluded in section 4.
2 Semantic Wikis
Wiki systems are a kind of containers for text pages (“wiki pages”) and media
files (images, audio files, and others). Wiki pages are human readable plain
text files that uses special structures to denote different types of content (e.g.
headers, images). Pages within a Wiki are usually grouped within the so-called
namespaces and identified by unique names. They are also linked to each other
creating a hyperwikitext structure4 .
Semantic wikis enrich the wiki technology with semantic information. They
are quite popular, as evidenced by the large number of semantic wiki systems.
Examples are: KnowWE [1], OntoWiki [6] or SweetWiki [3]. The most popular is
the Semantic MediaWiki (SMW) [7] that is based on the MediaWiki system used
by the Wikipedia project. Its capabilities include, but are not limited to, stating
information about categories and relations between wiki pages and querying a
3
See: http://projetos.dia.tecpar.br/noctua/index.php?clicked=info.
4
For more information and wikis comparison see: http://www.wikimatrix.org/.
wiki with a specific query language as well as with a standard SPARQL language.
Semantic Wikis are therefore good knowledge management tools [8] that are used
not only in KE projects but also in software engineering ones [4,5], [10,11].
Loki [8,9] is another Semantic Wiki, developed as a plugin for DokuWiki
system that stores knowledge using Prolog-based representation. It is distributed
as free software5 , what makes it easily accessible by any interested group of
people. To be more precise, Loki is not a single plugin but a set of independent
plugins, e.g. BPwiki [10] for storing and visualizing Business Processes within
wiki and SBVRwiki [11] for processing business rules.
Semantic Wikis were used in many projects, ranging from historical ones, like
Catalogus Professorum Lipsiensis, knowledge base that describes life and work
of 1.400 professors of Universität Leipzig in 1409-2009 [13], through the business
ones, e.g. Prosecco project, where semantic wiki was used as a storage for SBVR
business rules that describes the small and medium enterprises [11], to medical
ones, like Digitalys CareMate, a decision support system for paramedics [1].
3 Outline of the Solution
Extended versioning mechanism for Semantic Wikis proposed in this paper is
based on the PROV graph6 , a W3C standard prepared for describing data prove-
nance. PROV graph represents relations between entities (wiki pages and their
revisions), activities and agents (users). E.g. the graph states that the first
revision of a page welcome was created on 31/08/2016 by Chris (what con-
sists of three triples that connect selected wiki page–subject, with main page,
creation time and author)7 . New facts (triples in the RDF form) are added to the
changelog after one of three possible user activities: page creation, edition and
deletion. The graph incorporates also pieces of information provided by modules,
which were selected in order to most comprehensively catch the properties of the
changes (see Figure 1):
Changes ontologies: main activities within Wikis are page creation, edition
and deletion, but these ones do not exhaust the issue. We should take into
account that there are different types of changes (see Section 1) and each
edition is stated by the factual change (What was done? E.g. Typos or other
small bugs fixed or New content added ) and the goal (Why it was done?
E.g. Errors fixing or Knowledge database expansion) that form some kind
of ontologies (one for every task’s “type”, e.g. one for preparing conference
papers and the other for developing system specification within wiki).
Rich metadata: besides “standard” timestamp and user, the framework also
provide more information about each page edition: internal (other wiki pages)
and external (e.g. books) sources of knowledge in the form of an URI, as well
as about user: name, e-mail address, etc.
5
See: http://loki.ia.agh.edu.pl/.
6
See W3C documentation on: https://www.w3.org/TR/prov-primer/.
7
Detailed specification of created triples is provided on the page: http://loki.ia.
agh.edu.pl/wiki/docs:prov#how_the_prov_plugin_works.
Fig. 1. Extended semantic wiki versioning architecture. The BiFröST framework is
a prototypical implementation based on the Loki Semantic Wiki.
Semantic statistics: how many concepts / instances / relations were added /
removed / corrected in this revision?
Reasoning (unit) tests: as an analogy to the unit tests in software engineer-
ing, we added a possibility to define test cases that will be executed during
page saving to ensure the minimum level of knowledge quality.
Issue tracker: it is not possible to cover all aspects of changes by automatically
computed characteristics (semantic statistics and reasoning tests mentioned
above). There should be also a place for discussion between experts.
The advantage of the proposed solution over “classical” changelog within
CKE setting is based on the power of the PROV graph based on the RDF
triples that can be (automatically) queried with SPARQL. With this in mind
exemplary use case scenarios are indicated, as a response for issues described in
Section 1:
Get rid of bad changes. With tests’ statistics, one can quickly identify which
changes are bad and should be examined. In a more rigorous case, a wiki’s
administrator can block the ability to save changes if new revision is worse
than previous one (less tests were passed).
Sources analysis. By combining tests’ statistics and sources lists, to determine
which sources have low quality and shouldn’t be used in the future.
User types identification. Thanks to placing the solution on the top of changes
ontology, we can identify different kinds of users, e.g. good users and bad
users (who introduces bad changes) or creators (they add a lot of text), anno-
tators (they provide many new relations for existing text) and proofreaders
(users that mainly fix spelling).
Underdeveloped pages indication. Semantic statistics provide information
about how many concepts and relations are stated on the page. If there are
not too much, maybe it is a good time to pay attention to the page?
Motivation by gamification. Accurate metrics allow for awarding points to
users, giving them badges for different tasks (e.g. badge for adding 5 new
relations in the wiki pages) and creating leaderboards. These ones can mo-
tivate them to create better knowledge base what is the main goal.
The BiFröST (BiFröST Framework för Semantical Tracking), a prototypi-
cal implementation of proposed versioning mechanism for Loki Semantic Wiki is
being developed and tested in collaboration with students at AGH-UST8 . At the
time of submitting the paper, PROV graph is created within framework (see Fig-
ure 2). This first prototype was used in small experiment to collect triples about
940 user activities. Practical implementation of the SPARQL queries scenarios
presented above is a future work.
Fig. 2. First BiFröST prototype. Figure presents form that consists of: (a) place for
URIs/URLs for used resources, both internal and external (red frame); (b) all wiki
pages index (green frame) with filter capabilities (blue frame) for easy internal resources
insertion; (c) whatWasDone and whyWasDone fields for selecting proper concepts from
changes ontology (not visible on the figure).
4 Summary
In this paper the enhanced semantic versioning mechanism is proposed as well
as prototypical implementation called BiFröST. Besides elements that appear in
every Wiki system, like simple changelog and place for discussion, the proposal
incorporates changes ontologies, rich metadata, semantic statistics and reasoning
unit tests. All of them are gathered into the form of the provenance graph that
can be analyzed using SPARQL queries. First prototype implementation was
developed and used in small experiment at AGH UST.
8
See: http://loki.ia.agh.edu.pl/wiki/docs:prov.
Acknowledgements. The paper is supported by the AGH University of Science
and Technology Grant 15.11.120.855.
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