“Made with Knowledge”
Disentangling the IT Knowledge Artifact by a Qualitative Literature Review
Federico Cabitza and Angela Locoro
Università degli Studi di Milano-Bicocca,
Viale Sarca 336 20126, Milano, Italy
Keywords: Knowledge Artifact, IT Artifact, Organizational Knowledge, Literature Review.
Abstract: Knowledge Artifact (KA) is an analytical construct by which analysts, researchers and designers from
different disciplines usually denote those material objects that in organizations regard the creation, use,
sharing and representation of knowledge. This paper aims to fill a gap in the existing literature by providing
a conceptual framework for the interpretation of the heterogeneous contributions on this concept in the
specialist literature. From our survey of the main contributions to the definition of this concept, we outline a
spectrum of stances laying between two theoretical extremes: we denote one pole “representational”, as it is
grounded on the idea that knowledge can be an “object per se”; and the other pole “socially situated”, as it
builds on the viewpoint seeing knowledge as a social practice, that is an epiphenomenon of a situated,
context-dependent and performative interaction of human actors through and with “objects of knowing”. In
proposing a unifying model to gather complementary dimensions of knowledge together, our aim is to shed
light on the multiple ways these ideas can inform the “reification” of knowledge into particular IT artifacts,
which we call IT Knowledge Artifact (ITKA), and on how seemingly irreconcilable positions can contribute
in the design of these computational artifact supporting knowledge work in organizations.
1 INTRODUCTION
“IT artifact” is a general expression to denote “the
application of IT to enable or support some task(s)
embedded within a structure(s) that itself is
embedded within a context(s).” (Benbasat and
Zmud, 2003). Convincingly introduced in the
Information Systems literature almost 15 years ago
by Orlikowski & Iacono, such a concept has been
addressed by hundreds of scholars in this time lapse
from different and complementary perspectives
(Akhlaghpour et al., 2013) and endowed with
several definitions (Alter, 2006) to account for the
multiple manifestations and proteiform nature of
software applications in organizational settings.
Notwithstanding this apparent scholarly variety,
recent contributions are converging towards a
stronger recognition of the importance of both the
semiotic and social nature of the IT artifact (Lee et
al., 2013), as this is never “natural, neutral,
universal, or given [but it is rather] socially created,
[…] shaped by the interests, values, and assumptions
of a wide variety of communities of developers,
investors, users, […] embedded in […] a social
contexts [that let][…] emerge [them] from ongoing
social practices, […][and] not static and
unchanging, but in a continual evolution.
(Goldkuhl, 2013). In particular, it has also been
recently claimed that taking the socio-technical
nature of the IT artifact seriously (Markus and
Mentzel, 2014; Harrison et al., 2007) is essential to
promote “ethical responsibility [and] to minimize
the negative consequences of information and
communication technologies”. In this paper, we
focus on Socio-technical IT artifacts that support
knowledge, as a valuable subset of the more genera
concept discussed above, and hence on the notion of
IT Knowledge Artifact (ITKA in what follows). In
(Cabitza et al., 2014) this class of software
applications has been proposed to encompass
“material [IT] artifacts [which are] either designed
or purposely used to enable and support knowledge-
related processes within a community, […], like idea
expression and exchange, content and structure
negotiation, meaning reconciliation, collective
deliberation, new product and process co-design,
knowledge representation at various degrees of
64
Cabitza F. and Locoro A..
“Made with Knowledge” - Disentangling the IT Knowledge Artifact by a Qualitative Literature Review.
DOI: 10.5220/0005086100640075
In Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS-2014), pages 64-75
ISBN: 978-989-758-050-5
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
(under)specification, problem framing and solving,
mutual learning, and novice training”.
Tackling this matter from a socio-technical
perspective requires focusing on those IT artifacts
that create and circulate new information within
human practices, often on the basis of computational
rules that in some way mirror domain-specific
knowledge, as well as on those artifacts that enable
and support knowledge-intensive activities and tasks
both at human (i.e., cognitive) level and at social
(i.e., community) level. A first step in this direction
is to focus on the different aspects of computational
support to knowledge practices, as emerging from
different research strands and scholarly works
articulated around the concept of Knowledge
Artifact (KA in what follows).
We believe it is time to denote these particular
ITKAs in more precise and specific terms (starting
from the work of Cabitza, 2013), in order to fill a
gap in the literature on them where, to the best of
our knowledge, a review drawing on affinities and
divergences in the use of the term KA is still
missing.
The purpose of this work is then to conduct a
qualitative review that would help answer some
main research questions like: “what do we talk about
when we talk about knowledge” as in (Davenport
and Prusak, 2000) in the IT discourse? What are the
underlying assumptions in the design of ITKAs?
How these assumptions affect the design of these
artifacts and, consequently, their low or high
adoption and effective use by their intended users?
The phrase mentioned in the title of this
contribution epitomizes in an intentionally
ambiguous manner the two extremes of whole
spectrum of possible answers that can be given to
the questions above mentioned; a bipole where
ITKAs can be seen as either “made of knowledge”
(Salazar-Torres et al., 2008) or “made in virtue of
knowledge” (Brown and Duguid, 2001). On one
pole, we can recognize the tenets of the Knowledge
Representation (KR) field, which assumes a realistic
perspective on knowledge, i.e., a relation between
the objects conceived in the mind and the apparently
immutable outside forms perceived as reality. KR
expresses the concrete possibility to represent things,
in order to capture their essence for sharing a
discourse with others. This pole roots in Artificial
Intelligence and is based on some principles (Sowa,
2000) that inform the design of ITKAs as KR
devices: this includes models of real objects
according to a formal theory that elucidate their
nature, their relations, and their instances.
Knowledge, in this sense, should represent the
reached consensus by a community on a description
of a piece of reality, being that a domain of
discourse, an application, a task, and so on, which
has been disambiguated, automated and embedded
in a system for managing knowledge.
On the other pole, a complementary mode of
knowledge, or better yet of “knowing”, draws on the
distinction between the procedural “know how” and
the discursive “know that” (Collins and Evans,
2008), but also on a dimension of interpretation,
where “an individual pre-understanding is a result of
experience within a tradition” (Winograd and Flores,
1987, p. 74). This knowledge disposition is a part of
a process that is “neither subjective nor objective”
(Winograd and Flores, 1987, p. 75) and has
biological roots (Maturana and Varela, 1992): it
emerges from patterns of interaction that couple
living organisms with their internal structures and
external environments, and orient their actions and
changes “in many dimensions at the same time” (p.
116). (Greenhalgh and Wieringa, 2011) grasp such
interplay of knowledge with the word “mindlines”,
that is “internalized guidelines”; in other words, the
capacity of “continually being adjusted partly by
grazing on written sources […][and] mainly by
reflecting on experience during discussion with
colleagues and opinion leaders, […][especially when
they share] real stories of how they managed real
cases” (p. 506).
The main contribution of our work is the
proposal of a conceptual framework of key values
and attributes for the analysis of the rationales and
design principles at stake around the concept of
(IT)KA (that is simply the computational
counterpart of a KA), according to the results of an
extensive qualitative review. The outcome of this
analysis helped us conceive two main categories of
ITKAs: the “Representational ITKA” and the
“Socially situated ITKA”. In general, this
categorization could be a tool for the analyst and
designer to interpret the peculiarities of the setting
hosting ITKAs, as well as to understand the ways
and goals according to which ITKAs are built and
used. In addition, this analysis could be a first
contribution to unravel implicit values and
assumptions for ITKAs design.
The paper is structured as follows: after a brief
introduction to the method adopted for our
qualitative review, we show the results of the
different phases of our analysis, discuss them by also
providing examples of design, and conclude.
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2 METHOD, CATEGORIES AND
DIMENSIONS OF ANALYSIS
2.1 Search and Selection
Our review of the literature on ITKAs relies on the
works of (Webster and Watson, 2002), and
(Wolfswinkel et al., 2011). We strictly adhere to all
the phases listed and described in the last paper,
whose analysis phase corresponds to grounded
theory methodology. The search and selection
phases are depicted in Figure 1. In particular, for the
retrieval of relevant articles on KAs the Google
Scholar engine was queried in Summer 2013, with
the following keywords: “Knowledge Art*fact*
is|are|(can be)”, for the first round of searches. The
top ranked articles with their abstract were
examined, and we proceeded with a selection of the
part of them that resulted within the scope of the
review as formulated in the introduction. This
resulted in a final selection of 21 sources, each
containing a definition of KA, and part of which
were used in our design Section. A second and a
third query were issued with the term: “knowledge
representation”, and “ontology design”, respectively,
in order to refine the branch of the KAs literature on
the representational side. A total of 40 papers were
selected, and 3 papers were kept as paradigmatic of
KAs real applications. A fourth query with the term:
“epistemic object” was finally issued in order to
refine the branch of the KAs literature on the
situativity side. A total of 3 papers were selected and
used as above. A final round of queries were issued
in the AIS eLibrary for finding selected theoretical,
primary study, and review articles based on the
criteria of having being published as a journal article
(e.g. MIS Quarterly Executive) or conference
proceedings (e.g. ICIS and ECIS) of the AIS
community. After a thorough analysis and re-read of
excerpts, a final bunch of 15 articles was finally
selected and exploited for the creation of our
conceptual model on KAs. This selected literature
spans at the intersection of theoretical approaches to
organizational knowledge (Burrell and Morgan,
1994), sociological and information systems studies
on IT conceptualization (de Vaujany, 2005; Iivari et
al., 1998; Iivari, 2007; Orlikowski and Iacono,
2001), as well as Knowledge Management Systems
reviews and Organizational Knowledge resources
studies (Holsapple and Joshi, 2001; Alavi and
Leidner, 2001, Binney, 2001, Rodríguez-Elias et al.,
2008).
2.2 Analysis and Presentation
The open coding phase was conducted on either the
21 papers containing definitions of KAs (see Table 1
for a detail of sources and definitions), and the 15
theoretical papers on IT artifact and Knowledge
Management conceptualizations; the axial coding
phase was conducted by extracting conceptual
dimensions from the 15 theoretical papers (the
findings of the articles were put in an output table, as
in Webster et al. 2002, with the categories of the
research conceptualization as concepts. Each article
could span more than one concept and attribute. See
Table 2), and by classifying the 21 papers on KAs
definitions and the 10 real case applications papers
according to them (see the descriptive analysis of
Sections 3.1 and 3.2); the selection coding phase
lead to a further synthesis of our findings into the
two main categories of KAs classification, and was
based on all the papers collected (see Figure 2 for a
summary of our findings).
2.2.1 Open Coding: Ka Definitions
Table 1 reports the 21 definitions of KA and can be
ideally split in two quite equal parts. The first part
refers to a definition of KA where knowledge is
conceived as being a part of res extensa, to look
through this definitorial phenomenon from a
Cartesian perspective. The second part of definitions
puts more emphasis on the communicative aspects
of individual activities, whose collectively shared
and interpretable output is the piece of knowledge
(here conceived as a part of res cogitans) that can be
supported by KAs. This ontological distinction
brings important consequences in the way KAs are
designed for the aims and scope that they should
support, with their different forms and within
different environments.
2.2.2 Axial Coding: Categories and
Dimensions of Knowledge Artifacts
and IT Design
The two dimensions of objectivity and situativity
(our input dimensions for classifying ITKA-based
applications, see Section 2.2.3) characterize the
categories of our output map, depicted in Table 2,
where a bipolar conceptualization of the literature on
KAs has been conceived. This table is a
classificatory device for our review activity. The
dimensions described are ideally split in two parts.
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Figure 1: Search and Selection steps.
The first part is theoretical and stems from the
framework of Burell & Morgan, within
organizational studies. We enrich the ontological
dimension of knowledge with other perspectives:
that of Nonaka & Takeuchi talking of explicit and
implicit knowledge; that of Sowa indicating the way
knowledge is representable; that of Duguid
highlighting the cultural side of knowledge,
especially in Communities of Practice.
Besides Burrell and Morgan epistemology, we
have preferred to contrast the term “positivist” with
a set of terms that should better characterize the
“non-positivist” stance. To this aim, we especially
highlighted a historical that sees users and systems
as an evolution towards “interactive agents” from
passive ones. This, in our view, better expresses the
epistemology of the “Socially situated KA”
perspective.
The “knowledge modes and structures” are those
of Alavi & Leidner, Iivari and de Vaujany.
Rodríguez-Elias et al. and spans from the more
“unstructured” (as in audio, video and free text) to
the more “structured” (as in metadata, formal
categories and graphics).
The second part of Table 2 focuses on the
application of the first part principles to IT artifacts
design and requirements. Orlikowski & Iacono and
Iivari gave a classification of IT artifacts and of IT
applications archetypes, respectively. We related and
decided to group them under a unique perspective.
Alavi & Leidner gave a taxonomy of which
kinds of knowledge is processable by KMS, and
Holslappe & Joshi extracted some attributes of
organizational knowledge resources. We selected
from both the more salient for our conceptualization.
We added Massey & Montoya-Weiss’
conceptualization of time, and Iivary’s IS
development approaches classification, as well as
March & Smith’s evaluation dimension in IT. A
final dimension is that of KM Applications by
Binney, as a frame into which we could exemplify
how the issues of passing from representational
knowledge to socially situated knowledge may also
fit into the given “KM landscapes”.
2.2.3 Selective Coding: Objectivity Vs
Situativity
The two categorical dimensions of objectivity and
situativity, together with their relationships with
different kind of IT applications, are reported in
Figure 2.
Situativity, for our purposes, can be epitomized
in terms of the extent the KA is capable to adapt
itself to the context and situation at hand, as well as
the extent it can be appropriated by its users and
exploited in a given situation. Objectivity, to our
aims, can be conversely considered the capability of
the KA to represent true facts in an objective, crisp,
and context-independent manner, as well as the
extent it can be transferred among its users as an
object carrying some knowledge with itself. To
adopt evocative terms introduced by (Goguen, 1992)
and (Latour, 1987), then objectivity refers to the
extent a KA is “cold / immutable” (cf. Latour) and
“dry” (cf. Goguen), while situativity refers to the
extent such an object is “warm / mutable”, and
“wet”, respectively.
Each group of applications of Figure 2 is
associated with the research and design principles,
values and assumptions of the disciplines that lay at
the intersection points of the Figure. This schema
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wants to express how much objectivity and
situativity is implied by each design input and
requirement for the IT artifact as the final output.
Besides the two extremes, no other group of
applications contains purely objectivity or
situativity, but the most part of them result in a
differently mixed blend of the two.
Depending on the attributes collected in our axial
coding analysis (the dimensions depicted in the
second part of Table 2), we can give a brief
overview of what objectivity and situativity mean in
terms of the knowledge phases, structures, attributes,
and knowledge-based activities that these
applications and tools are supporting, while
delegating a detailed description of some aspects of
their design to the next Section.
Objectivity seems to characterize more all those
large-scale applications that are oriented to business
and enterprise activities, where the dimensions of
organizations require to handle information
quantitatively, and in a centralized way (e.g. by
collecting all the specialized knowledge distributed
among the different sectors of an organization and
by adopting a uniform and top-down codification).
The aim of such applications is to collect, store,
retrieve, and apply information across the lens of
standard procedures that guarantee the control of a
complex system and the rapid problem solving and
decision making at a “routine” level, as well as at a
managerial level.
Information systems technology lays in the
middle, is scalable, and constitutes the set of tools
able to process and manage information (i.e. to
structure, store and maintain the documents by
indexing, organizing, classifying, filtering it, and so
on).
Computer Supported Cooperative Learning and
Computer Supported Cooperative Work
technologies support a more individual and personal
dimension in the management of the knowledge that
they are called to handle. In a way, the environments
of such applications are less standardised, not totally
specified, and strongly oriented to creation, design,
innovation, apprenticeship, creative working and
management, and unstructured communication and
cooperation tasks (often outside and between
organizations).
In what follows, a necessarily brief review of
some literature on ITKAs is reported, as selected and
framed along our conceptual categorization and
analysis.
3 DISENTANGLING ASPECTS OF
ITKA DESIGN
3.1 The Representational ITKAS
Representational ITKA are objects where knowledge
is reduced to a formal logic way that aims to capture
their “essence” (Holsapple and Joshi, 2001; 2002).
In this tradition, KA may have varying degree of
structuredness e.g.,(Giunchiglia and Chenu-Abente,
2009), from documents, diagrams, manuals, to
formal ontologies and knowledge bases, passing
through the whole range of semi structured sources
that are used in organizational settings, like
spreadsheets, forms, XML documents, and the like
(Toro and Kulkarni, 2008; Diaz and Canals, 2007).
In addition, in this stance KA can be endowed
with a varying degree of generativity, from simple
proof checkers to even very complex inference
engines. Ontologies (Guarino, 1998), for example,
are the representational objects that epitomize
knowledge structure and computation over it.
The ontological spectrum (Noy and Hafner,
1997) includes the so called lightweight ontologies,
i.e., simple vocabularies of hierarchical terms, which
mainly serve to classify items; lexical resources
(Fellbaum, 1998), which makes explicit and
expandable the local space of word meanings, for
advanced search and retrieval tasks; fully
axiomatized theories, all encoded in logic languages
(Baader, 2003) and equipped with reasoning tools.
As the computational complexity tends to
increase rapidly, more than often the model of
reality that undergoes the conceptualization and
axiomatization process tends to be partial and
oversimplified (Sowa, 2000).
According to the above definitions,
representational KA are those stored in a Knowledge
Management repository (Weber et al., 2006), in a
Digital Library (Candela et al., 2008), and the like,
as structured sources of static knowledge, as well as
in more sophisticated tools that computationally
“activate” knowledge, like Decision Support System
or Expert Systems (Matook and Brown, 2008), or
any semantically enriched IT System, with its
automatic or semi-automatic services for structuring,
storing, extracting, retrieving, evaluating, and
maintaining knowledge artifacts e.g.,(Maedche et
al., 2003).
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Table 1: KA: 21 definitions. Italics in definitions is ours.
Author KA definition
Paavola et al. (2004) Knowledge creation activities rely heavily on the use, manipulation and evolution
of shared KAs externalizing a body of (tacit or explicit) knowledge
Smith (2000) any item that captures explicit or tacit knowledge
Ancori (2000) something where knowledge is made “explicit” and “recorded”, as the formal
outcome of a process of codification
Seiner (2001) defined piece of recorded knowledge that exists in a format that can be retrieved to
be used by others
Diaz & Canals (2007) minimal unit of explicit and exchangeable knowledge
something that encapsulates knowledge [that can be] informal (where knowledge is
strong hard-coded), semi-formal (where informal knowledge representation is
mixed with formal representation), or formal (where knowledge is represented by a
formal knowledge representation system)
Krupansky (2006) an artefact which represents an encoding of knowledge
S. Gandhi (2004) When knowledge is fixed or codified, a KA is created, and it is this knowledge
artifact that can be managed.
Holsapple & Joshi (2001) object that convey or hold usable representations of knowledge
Holsapple & Joshi (2002) object that represents knowledge
Weber et al. (2006) whatever element stored in a KM repository
Weber & Gunawardena (2008) a knowledge engineering formalism of knowledge representation […] that allows a
computational system to make decisions and solve problems
Alavi & Leidner (2001) must include the minimal elements for a user to make a decision to solve a
problem, and be easily interpretable
Salazar-Torres et al. (2008) vehicle for knowledge sharing
artifact made of knowledge. [...] can be very useful to ensure the effectiveness of
the transfer and utilization of knowledge in organizations of all sorts.
Mödritscher & Hoffmann (2007) any piece of (digital) information relevant for a certain working context and
enriched with semantic information in terms of metadata
Mangisengi & Essmayr (2002) anything that allows knowledge to be communicated independently of its holder
Scrivener (2002) artefact designed with the intention of communicating knowledge
Mansingh et al. (2009) input to and product of knowledge enabled activities
Giunchiglia & Chenu-Abente
(2009)
object created as a result of an activity which encodes knowledge, the
understanding or awareness gained beyond data
Bereiter (2002) products or objects of thinking and reasoning that can be collectively argued
Oinas-Kukkonen (2004) serve as a collaboration vehicle through interaction between information
producers and consumers, within a team of co-workers or among other
stakeholders [and] support understanding and communication in the individual
learning of new things
Y. Tzitzikas et al. (2007) KA refer to what is being created and/or shared by a group of learners (and could
be a set of words, documents, concept maps, ontologies, annotations, etc).
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Table 2. Conceptual Framework of Organizational KM and ITKAs Design.
Attributes underlying assumptions for Design Representational ITKA Socially situated ITKA
Paradigms of study
[Burrell & Morgan 1994]
Functionalist Interpretive
Ontology (nature of knowledge)
[Sowa 2000; Duguid 2005; Burrell & Morgan
1994; Nonaka & Takeuchi 1995]
explicit / representable
(realism)
tacit / cultural / practical
/actionable (nominalism)
Epistemology (interpretation of knowledge)
[Burrell & Morgan 1994; de Vaujany 2005;
Greenhalgh & Wieringa 2011]
positivist (nomothetic) constructivist / interactionist
/emergentist (ideographic)
IS approaches to IT conceptualizations (status of
knowledge)
[de Vaujany 2005]
autonomous
passive
(deterministic)
integrative (action and
structure cannot be separated)
malleable
actively and interactively
usable (voluntaristic)
Modes and structures of knowledge
[Iivari 2007; de Vaujany 2005; Alavi & Leidner
2001; Duguid 2005, Rodríguez-Elias et al. 2008]
Explicit structuredl
codifiable
descriptive
procedural
objective
essential
formal
rational / conceptual
Explicit unstructured
interpreted
socially constructed
instrumental
performed
comprehensive
subjective
flexible / conventional
IT artifact archetypes (scope and aim of
knowledge)
[Iivari 2007]
To informate / to automate To mediate / to augment
IT artifact views (activities based on knowledge)
[Orlikowski & Iacono 2001]
Computational (algorithm,
model), labor substitution,
production and information
processing tool
Social relation tool
proxy / ensemble view
Knowledge Management views (phases of
knowledge)
[Alavi & Leidner 2001]
factual
data oriented
object to be stored and
manipulated
condition of access to
information
personalized information
state of knowing and
understanding
process of applying expertise
potential to influence action
Attributes of knowledge in Organizational
knowledge resources
[Iivari et al 1998; Holsapple & Joshi 2001; Massey
& Montoya-Weiss 2006; March & Smith 1995]
Quality: validity
Main view: objective
Time: discrete, ordered,
dependent
Level of certainty/detail:
decidable / specified
Usage: computational /
procedural / top-down oriented
Quality: utility (means-end
oriented)
Main view: subjective
Time: continuous, chaotic,
independent
Level of certainty/detail:
undecidable / left incomplete
Usage: pragmatic / situational /
bottom-up oriented
Knowledge Management Applications
[Binney 2001]
Transactional
Analytical
Asset
Process
Developmental
Innovation and creation
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Figure 2: Selective Coding: classification of ITKA-based applications grouped by research discipline and according to the
two dimensions of objectivity and situativity.
In a representational approach, some suggestions
on how to couple formalisms with design
requirements for a better use of KAs are devised
(Szulanski, 1996). (Weber and Gunawardena, 2008)
also recognize that “the design of knowledge
artifacts includes the processes where they are
applicable”. KAs for enhancing and supporting
highly specialized tasks in communities of experts
are those depicted in (Bandini and Manzoni, 2002;
Bandini et al., 2003, Salazar-Torres et al., 2008),
where formal knowledge is collected with keeping in
mind, and applying, principles and methodologies
that involve instances, practices, and values of
specific communities and of their past knowledge. In
particular, the KA conceived in this project is a case-
based reasoning KA, in that it supports innovation
management activities by incorporating the jargon of
the technical experts for recording past experiences.
A case-based reasoning mechanism for problem
solving is then provided to facilitate collaboration
within members of other teams.
The computational part is based on the explicit
semantics added to the rather implicit system of
meanings of language symbols, to provide a flexible
layer of negotiation that can adhere to the new case
that needs to be collaboratively examined based on
the past ones. New combinations of the elements
represented in the KA memory support are obtained
by exploiting fuzzy logic rules as computational
counterpart of the qualitative variables of the
specific domain and case at hand.
3.2 The Socially Situated ITKAS
Practice oriented definitions refer to something that
is made during a performance, in “knowing” (Cook
and Brown, 1999), seen as a “social product
[emerging from the] messy, contingent, and situated
outcome or group activity.” (Turnbull, 2000).
In this context, KAs are not supposed to store
knowledge or to be designed to “engender knowing”
(Scrivener, 2002). Better yet, a KA allows its users
to make apt and proper decisions or create
innovation, or solve problems, and overcome
breakdowns. In this stance, it acts as a support or
scaffold to the expression of knowledgeable
behaviors. In complex organizational settings, KAs
regards also how to organize memories, report best
practices, outline ideal and effective methods
(Cabitza and Simone, 2012), because such
representations (either textual, diagrammatic or
pictorial) trigger opportunities for socialization,
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internalization and, by evocation and memory aid,
knowledge retention and exploitation (i.e.,
knowledgeable behavior). As “centers of gravity for
knowledge [KAs] concentrate it, make it tangible,
instrumental, effective” (Allen, 2004, p. 62).
(Knorr-Cetina, 1999; 2001) introduced the
concepts of “performing-with” and “being-in-
relation-with” to distinguish the relation with
“epistemic objects”, the classical objects of study in
scientific practice, which implies a relational attitude
more than a performative one. These objects are
“capable of unfold indefinitely” although
“instantiated”, as they are “simultaneously
mutating” (cf. (Suchman, 2007), on the situated
actions in the context of “heterogeneously enacted
and intrinsically indefinite events”). An “unfolding
ontology” suitable for describing them should be
based on post-scriptive structures, which may
include the “temporality” of things into which
“epistemic objects […] tend to [constantly point to a
possibly] unreachable real whole”.
(Ewenstein and Whyte, 2007) extended this
notion to visual forms, through which both designers
and engineers should cooperate on a common
ground. Visual forms are mutable forms that unfold
“in time”, as “they are not yet but might become in
future iterations”; “in space, as standpoint-specific
boundary objects”. For their boundariness they are
defined “trans-epistemic objects”, i.e. “capable of
traversing and permeating different epistemologies
of design”.
(Massey and Montoya-Weiss, 2006) investigate
the process of knowledge conversion (KC), both in
indirect KC (solitary work interacting with the
artifact) and in direct KC (synchronization via
communicative human-to-human activity). They
propose a model of “personal perception of time”,
i.e., a one task or “monophasic” entity vs. a
“polyphasic” entity or structure of events.
What is put in the foreground by these design
studies are the mutable social and temporal
dimensions of knowledge forms, which seem to
suggest inescapable requirements for the design of
KAs.
4 DISCUSSION AND
CONCLUSIONS
The literature review we have outlined above has
shed light on the manifold, and sometimes even
divergent, perspectives that have so far emerged
about the nature of what scholars have wanted to
denote with the term Knowledge Artifact in the last
15 years. Our literature review unveils the
characteristic of the concept of Knowledge Artifact
to be a “boundary concept” (Löwy, 1990), that is
something that allows “disparate proponents to
appropriate it in consonance with the main aims and
scopes of their fields”. However, with our review we
have also aimed to raise awareness of both the
complementarity and tensions existing between
different stances that can be positioned at some point
within the objectivity vs. situativity spectrum. In
short, this categorization is ultimately aimed at
shedding light on the necessary recognition that
designing for effective knowledge artifacts requires
to address once again important questions on what
we want human knowledge to be, and accept as
possible yet temporary answers contributions
coming from the whole symbolic-subsymbolic range
of stances that have been very briefly outlined in this
work.
All in all, one could rightly wonder how the
categories proposed in this conceptual framework
can be reflected in distinct design principles or,
even, more specific requirements. We hint at these
principles here in a very general manner for
limitations of space. A coherently representational
stance will require KAs to be able to: store more or
less structured documents; possibly classify them on
the basis of some domain ontology; and enable their
retrieval according to queries, filters, topic models
and user profiles of varying complexity. The KA
could also be capable of storing usable
representations of declarative (e.g., assertions and
rules) and procedural (e.g., algorithms, process
models) to assist users in knowledge work or give
them support in decision making. An ideal KA is
assessed in terms of the quality of its output
(pertinency, accuracy, completeness, timeliness,
etc.) and of its autonomy in providing such an output
on the basis of the available information (e.g.,
inputs) within acceptable range of deviations from
the gold standards posed with respect to the quality
dimensions mentioned above. This means that the
process leading to the right output should be aware
of the context, including the user, but within the
variability accepted and considered in the
computational model formally. In Figure 2 these
features characterize the upper Cartesian hemiplane
depicted therein, where also the main systems that
are usually more focused on a representational
treatment of knowledge are listed.
On the other hand, the situated perspective would
require to design KAs that do not necessarily
represent knowledge per se, as said above, but that
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rather promote knowledge-related processes like
innovation, decision making and learning: in this
latter case the nature of the KA cannot be decoupled,
nor generalized, from the specific setting or
Community of Practice where the KA is supposed to
play its role of knowledge facilitator. The first
studies of communities where the creation and
circulation of new knowledge is part of the practices
that foster sense of belonging and identity therein
led to characterize a specific kind of community,
denoted as “knowing community” (Cabitza et al,
2014), which is defined as the social gathering
around a KA and where actors interact also in virtue
of the KA mediation. To account for this mediating
capability, specific principles have been proposed
for the design of situated KAs, namely,
representational locality, semantic openness, and
flexible underspecification, and discussed in
(Cabitza et al., 2013). Differently from the
representational KA, the quality of the situated KA
cannot be proved formally, but rather assessed in
terms of user adoption, appropriation and
satisfaction towards knowledge work support, that is
in terms of the extent users consider the KA fit to
their needs and capable of triggering social
interactions that would allow them to create,
socialize and diffuse new knowledge. In Figure 2,
we denoted this capability “socio-technical fit” (in
the bottommost hemiplane) as this is certainly an
attribute that a KA does not possess independently
of the social setting in which it is adopted, but rather
something depending on many factors that go
beyond the merely computational and performance-
related aspects of the artifact. As locality is
important for situated KAs (by definition itself of
situation), any strong or strict structure hardwired in
the artifact at design time could undermine, or just
hinder, the processes of user appropriation (Dix,
2007) and evolutionary growth (Mørch, 2003) the
KA must somehow undertake to support a knowing
community over time. For this reason, the capability
of the KA to be adapted, configured, and tinkered by
end users themselves to improve the above
mentioned fit is the second dimension on which
prospective situated KAs can be assessed (see Figure
2, bottommost hemisphere).
Based on the literature review, future research
can address several directions. First, the literature
review highlights the diversity of KAs; we suggested
a typology based on two dimensions, i.e. objectivity
and situativity. However, other proposals and
taxonomies are possible. On a more conceptual
level, our categorization can also be taken as a
contribution for a scholarly debate still to be
developed, regarding what features should a KA
exhibit, and on what kind of priorities to focus on
with respect to the application domain or
community. A major attention to the social practice
aspects of knowledge, for instance, could motivate
the design of artifacts that are made to be local, in
continuous evolution, and to host necessarily
incomplete, and possibly partially inconsistent and
ambiguous representations.
These only seemingly paradoxical features
should not then be taken as deficiencies of the tools
conceived to support knowledge, but rather as
features that result from a deep understanding of the
semiotic nature of human representations (Gourlay,
2004) and that require a committed research agenda
in the next years to come to be fully realized in
running applications and knowledge artifacts.
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