=Paper=
{{Paper
|id=Vol-1224/paper4
|storemode=property
|title=Openplexus: Distributed Knowledge-Sharing in Virtual Teams
|pdfUrl=https://ceur-ws.org/Vol-1224/paper4.pdf
|volume=Vol-1224
|dblpUrl=https://dblp.org/rec/conf/i-semantics/GiacintoP14
}}
==Openplexus: Distributed Knowledge-Sharing in Virtual Teams==
https://ceur-ws.org/Vol-1224/paper4.pdf
Openplexus: Distributed Knowledge-Sharing in Virtual
Teams
Robert Giacinto1 , Ana M. Lara Palma2
Cologne University of Applied Sciences1
Steinmüllerallee 1, 51643 Gummersbach, Germany
University of Burgos2
Hospital del Rey, 09001 Burgos, Spain
Abstract. In this paper we describe a new distributed knowledge sharing frame-
work that supports knowledge discovery and context-aware knowledge sharing
in virtual teams by introducing a 3-tier knowledge sharing architecture. The three
layers reflect different facets of knowledge: the personal knowledge that might
only have a relevant meaning for its author, the shared vocabulary and experience-
based knowledge of teams and the persistent knowledge of the organisational
memory. The prototype was designed by following a user-centred design ap-
proach in which the involved users gave important insight for the definition of
relevant use cases and scenarios that describe common tasks in virtual teams.
Key words: Knowledge Sharing, Semantic Web, Distributed Systems, Virtual
Teams
1 Introduction
One main concern with knowledge work in virtual teams is the externalisation and
reusability of knowledge that is created in projects. Virtual teams can be described as
“groups of geographically, organizationally and/or time dispersed workers brought to-
gether by information and telecommunication technologies to accomplish one or more
organizational task” [5, p. 7]. Many artefacts are often buried in folders or email at-
tachments of a single computer and are therefore not available to others. Enterprise In-
formation Systems that focus on archiving documents in a central repository solve the
availability issue but do not support easy discovery and reuse in virtual team settings
since finding the right document or at least a good starting point for a search activity can
be time-consuming and is often context-related rather than task-related. Our tool tries to
bridge the gap between existing search-oriented information systems and the need for
context-aware recommendations and the creation of informal knowledge spaces that
can be used to make the tacit and distributed knowledge of a virtual team explicit and
accessible to the organisation.
The remainder of this paper is organised as follows: In section 2 we describe our
approach to a context-aware system called Openplexus. Section 3 gives an overview of
the current architecture of the system and we conclude this paper with a summary of
the current state and future work in section 4.
Posters & Demos Track @ SEMANTiCS2014 15
2 Approach
With the growing amount of available data the incorporation of contextual information
into the selection and filtering process can help cut down the number of candidates in
search results and therefore reduces the effort for the individual ([1], [3]) to find the right
document for a task. The use of context models can be found in several implementations
of semantic information systems (e.g. [4], [2]) and mainly differs in the number of
context dimensions that are taken into account. These systems focus on local events
that affect the context of an individual. In virtual teams, the context that influences the
importance or meaning of a document can change even in the absence of a user.
Many definitions of context have been proposed in the literature over the years com-
ing from different research areas. For our system, we use the definition by Shkundina et
al. [6] where a context is comprised of six dimensions: (1) information, (2) organisation
(organisational structures or persons), (3) behaviour (performed actions), (4) operation
(used tools or applications), (5) cause (task and user goals) and (6) chronology (timeline
of events).
To model different layers of available knowledge in virtual teams, a 3-tier knowl-
edge architecture is implemented in Openplexus:
1. Personal layer that holds the individual knowledge of the owner of this instance.
The knowledge can only be accessed by the owner.
2. Team or Knowledge Sharing layer that holds the knowledge that belongs to a team
or that was shared with other individuals.
3. Organisational layer that holds the knowledge that should be accessible to all users
in the organisational network.
To enable the user define a personal mental model and support the sharing of it, a
shared base vocabulary is necessary from which the personal knowledge space is de-
rived. These shared concepts are described in the Openplexus Upper Level Ontology
and come from interview sessions with stakeholders and contextual enquiries. Where
possible, existing ontologies (e.g. Prov-O1 , DUL2 , FOAF3 and Vocab-Org4 ) were used
to derive sub-properties and sub-resources in the Openplexus namespace to create a
clean and understandale schema for the user while relying on the expressiveness of
existing vocabularies.
3 Openplexus Architecture
Fig. 1 depicts the architecture of the Openplexus system. It is designed as an event-based
middleware system built from a set of loosely-coupled and extendable components. The
system gathers and aggregates local and distributed event information created by dif-
ferent processes to model the current context. In its current implementation the system
1
http://www.w3.org/TR/2013/REC-prov-o-20130430/
2
http://www.ontologydesignpatterns.org/ont/dul/DUL.owl
3
http://xmlns.com/foaf/0.1/
4
http://www.w3.org/TR/vocab-org/
16 Giacinto & Lara Palma
Fig. 1. Conceptual overview of essential components implemented in an Openplexus
node. Dashed arrows symbolise the use of the event bus, solid arrows are direct com-
munications between two components.
focuses on the dynamic nature of collaborations in teams which are supported by the
possibility to create adhoc peer-to-peer networks with nodes of other team members in
which shared activities and events are distributed and kept synchronised.
Local Event Providers Local Event Providers are used to push context-related events
from user interactions with the operating system and external applications to Open-
plexus. Here, two different providers are implemented: (1) Plugins for third-party ap-
plications like email clients or web browsers and (2) native event listeners to capture
interactions with the operating system or watched folders. Additional events are fired by
tools provided by Openplexus that help create new team spaces, let the user join active
team spaces or share documents with team members. Each interaction with the system
that influences a user’s context is associated with an event that is fired and processed by
the Openplexus system.
Local Content and Information Extraction This component listens for filesystem and
files-related events and implements content extractors for the most common filetypes.
The extraction can happen automatically if the related file resides in a watched folder
or manually if the user passes a file to Openplexus (adding it to the personal knowledge
space or sharing it with a team).
Organisational Services This is a set of components that can provide access to services
that are only available to members of an organisation (e.g. access to the organisation-
wide knowledge-base which can be comprised of semantic services or other (legacy)
databases where queries are handled by an integration layer, or internal authentication
services). The current implementation holds the ontology that acts as the organisational
knowledge layer and directories of currently active team activities that a user can join.
Posters & Demos Track @ SEMANTiCS2014 17
(Local & Shared) Context Processing For every team a separate process handles the
distributed events that come from the network of connected peers. The remote context
of the team and the local context of the user are combined and enriched with information
from past contexts that are similar to the current one. All context-related events are used
as input for a multi-layer perceptron that is trained and used to classify the type of the
current context where the identified type defines the way how the recommendations are
calculated.
(Local & Shared) Knowledge Space A local knowledge space belongs to exactly one
user and is only accessible from the local Openplexus node. Here, the user is able to
introduce new concepts to the local ontology. In its current state, subclassing of existing
concepts is supported. The new concept is then added to the ontology of the knowledge
space if it is the private knowledge space of the user. In a distributed knowledge space,
this change is proposed to all members of this shared space and is only applied if the
majority of this team accepts the change.
Distributed Teams Handling Interactions between team members are related to a Team
Activity which is the temporal event when members of a team collaborate. These team
activities can happen in adhoc peer-to-peer (P2P) networks that are used for communi-
cation and knowledge sharing tasks. Openplexus handles a shared knowledge space for
each team. It holds the shared knowledge and context information that is created during
collaboration activities and maps to the second tier of our knowledge hierarchy.
Context-Aware Dashboard The dashboard is the UI of the system and serves as a single
point of entry to all services of the platform. The current focus for the implementation of
this component is the context-based visualisation of the available data by adjusting the
displayed content and resources depending on the current context of the system. Fig. 2
depicts a mockup which emphasises the proactive aggregation of relevant information.
In this example, Openplexus identifies a phone call context and deligates the rendering
of the UI to a context-specific visualisation handler.
4 Conclusion and Future Work
In this paper, we presented an architecture of a context-aware information system that
aggregates and processes information from different knowledge tiers of an organisation,
offering a fuller view on the available knowledge. The next steps include formalising
and extending the context similarity measure in use and the evaluation of the qual-
ity of the recommendations by evaluating precision and recall in a given scenario and
the usability of the system. Additionally, the handling of distributed changes and the
weighting of the tiers requires further investigation.
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18 Giacinto & Lara Palma
Fig. 2. Mockup of the context-aware dashboard, presenting information for an ongoing
phone call.
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