=Paper=
{{Paper
|id=Vol-290/paper-7
|storemode=property
|title=Towards a Semantic Contact Management
|pdfUrl=https://ceur-ws.org/Vol-290/paper06.pdf
|volume=Vol-290
|dblpUrl=https://dblp.org/rec/conf/fews/CelinoCV07
}}
==Towards a Semantic Contact Management==
https://ceur-ws.org/Vol-290/paper06.pdf
Towards a Semantic Contact Management
Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
CEFRIEL – Politecnico of Milano, Via Fucini 2, 20133 Milano, Italy
{irene.celino,francesco.corcoglioniti,emanuele.dellavalle}@cefriel.it
Abstract. Many organizations face every day the problem of effectively
managing their contacts (customers, suppliers, partners, etc.), in terms
of communication, clustering, networking, analysis, and so on.
Our company decided to cope with this issue by gathering the require-
ments for Contact Management and by designing and developing a pro-
totype, called GeCo, to fit Cefriel needs.
During the development of this application, which ran in parallel with
some research projects dealing with Semantic Web technologies, we rec-
ognized that the addition of some “semantics”, both in the data modeling
and in the tool design, would help a lot in solving the open issues for the
general problem of Contact Management.
In this paper we summarize the main criticalities in managing contacts
and we suggest how Semantic Web technologies can contribute to their
successful solution.
1 Introduction
Today, the success of an organization considerably depends on its ability in
managing and cultivating its network of contacts, namely customers, suppliers,
partners.
The more the organization grows, the bigger this network becomes; moreover,
it becomes difficult to have a unitary view on that network, because the different
organizational units have different demands which lead to the adoption of differ-
ent solutions of Contact Management. Information about contacts, as a result, is
fragmented within the organization or duplicated between organizational units,
each one with its different view. This situation can cause inefficiencies (e.g., the
problem of “who knows who” arises) and loss of opportunities (e.g., a unit can-
not exploit acquaintances of other units of the same organization, because their
contacts are inaccessible).
A solution can come by managing contacts in a (logically) centralized way,
by a collaborative approach in which each member of the organization can edit
and access all the contacts. This way, each contact is associated to a rich profile,
obtained from the aggregation of information coming from several sources, pri-
marily from users but also from legacy systems and other, pre-existing sources.
This rich knowledge base, no more fragmented, provides a unitary and consistent
view of the contact network. There are a lot of advantages: improved efficiency
64 2nd International ExpertFinder Workshop (FEWS2007)
2 Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
and better data quality (because of the shared data entry and management),
improved search of contacts (e.g. by expertise area), no opportunity loss (since
all data is now easily accessible), enabling advanced operations otherwise diffi-
cult to achieve, such as analysis to support strategic decision and planning (e.g.,
“what existing contact could be interested in the product X?”).
At Cefriel (our company), we designed and developed a prototype of Contact
Management application following this centralized and collaborative approach.
In the beginning we chose “traditional” technologies, but several difficulties came
out and led us to speculate on a Semantic Web solution. On the basis of the
preliminary results, in this paper we present the challenges and problems that
arose in developing such a Contact Management application and we investigate
the applicability of approaches and technologies from the Semantic Web world
to solve the open issues.
The remainder of the paper is structure as follows: section 2 outlines what
Contact Management is and how it is declined in our company; section 3 analyzes
the problems and issues that arise when realizing an application to deal with
Contact Management, independently of the technologies chosen; in section 4, we
envision how the employment of Semantic Web technologies can help in solving
the issues presented in the previous section; finally, we draw some conclusions
and illustrate the following steps in section 5.
2 Contact Management
Contact Management deals with the acquisition and maintenance of knowledge
about a user’s contacts, where the term contact could be given the broad meaning
of someone who the user has been exposed to during communication (see also [1]).
Contact Management is a composite discipline which deals with different other
approaches and demands, like:
– Personal Information Management or PIM, which is about keeping trace of
personal contacts, together with details about when and where the acquain-
tance was born and the events and projects in which those contacts were
cultivated; PIM systems are often the first step towards the sharing of those
information within specific groups (with an opportune access control);
– (Analytical) Customer Relationship Management or CRM, which is about
the management of customers/partners, their interests, their past purchases,
closed/activated/proposed projects with them and the analysis of the con-
tacts to support the business strategy of the organization;
– Public Relations or PR, which are about the timely and customized commu-
nication with the stakeholders outside the organization.
Cefriel1 is a private not-for-profit ICT company with about 130 employees with
different specializations and expertises, which deals every day with a number of
different interactions with various stakeholders. Cefriel’s mission is realized by
three kinds of projects:
1
http://www.cefriel.it
2nd International ExpertFinder Workshop (FEWS2007) 65
Towards a Semantic Contact Management 3
1. Research Projects, at national and European level, which require the inter-
action with partners and evaluators (e.g., the European Commission dele-
gates);
2. Innovation Projects, with industry as well as public administrations, aimed
at innovative solutions and technology transfer, by identification, analysis,
evaluation, integration and creative use of off-the-shelf and new technologies;
3. Educational Projects for post-graduates students as well as training courses
for ICT professionals and executives.
Within those projects, the main needs for Contact Management comprise the
maintenance of relationships with stakeholders and the search of external con-
tacts or internal staff, primarily by expertise area, in order to launch a new
activity or to manage a current one.
In order to deal with all those heterogeneous contacts, we decided to gather
all the different requirements for their management and to design and develop a
prototype of Contact Management application. We named this tool GeCo (from
the Italian “Gestione Contatti”, i.e., Contact Management) and we employed
traditional technologies to build a web application which allows the collabora-
tive editing, update and retrieval of the contacts, as well as the creation and
management of groups and distribution lists.
3 Issues about the implementation of a Contact
Management application
While designing and developing GeCo, we tried to realize a logically-centralized
and collaborative solution; by doing this, we met several issues that we can
schematize under five macro-categories: data acquisition, data relevance and re-
cency, extensibility (of both the model and the tool), data fruition, privacy and
security. In the following, we analyze each one of those categories, highlighting
the main difficulties we met in solving the problem of Contact Management from
a (traditional) technological point of view.
3.1 Data Acquisition
The acquisition and the preservation of contact information are expensive and
delicate activities, since contact data must be often inserted manually and the
correctness of data is crucial to assure the usefulness of the Contact Management
application (e.g., there must be no mistake in emails or telephone numbers).
We can identify two principal ways for acquiring contact information, namely
manual editing and reuse of pre-existing data sources (internal or external).
None of these is sufficient on its own and both the approaches are required for
Contact Management. For example, there are situations where manual editing
is inappropriate or disallowed, since contact data could be already available
(e.g. in the company LDAP directory) or it can also happen that organizational
reasons prevent some information (e.g. employees’ data) from being edited in a
collaborative way. Vice versa, it is frequent that required information must be
explicitly provided by users, due to the absence of existing data sources.
66 2nd International ExpertFinder Workshop (FEWS2007)
4 Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
In GeCo – the tool we developed – manual editing is designed to be a collabo-
rative activity, since each user can insert and modify contact data. This approach
makes the solution stronger, enabling the optimization and a better distribution
of the contact management effort, that is delegated to the contributing users.
The collaborative approach is undoubtedly one of the greatest strength of
the GeCo solution, since a contact inserted by one user can be re-used by all
other users of the system; nonetheless, this “teamwork” editing makes hard to
assure consistency and quality of the inserted data. For example, we can meet
the following problems:
– Contact Identification and Uniqueness: the same contact can be inserted
multiple times by different users which don’t realize that the specific infor-
mation is already present and stored in the system;
– Concurrent Updates: different users editing the same contact can disagree
on the shared data (e.g., the value of one or more contact properties); there
is also a strong need of versioning and configuration management, because a
user can inadvertently and wrongly overwrite previously correct data, caus-
ing the need of reverting the data to a previous version.
Regarding the reuse of existing data sources, we have to face the typical prob-
lems of data integration, i.e. the heterogeneity of data and schemata and the
presence of duplicated, inconsistent or incomplete data. Although marginally,
these problems arose also during the implementation of the GeCo prototype,
when we had to integrate existing employees’ data coming from several sources.
3.2 Data Relevance and Recency
In Contact Management systems, a perceived problem is assuring the relevance
of the inserted contacts and the recency of related data.
Contact Management is an expensive task: the greater the number of man-
aged contacts, the more expensive their acquisition and preservation, and the
more difficult the functionalities of search and fruition over them. Therefore,
given that different interlocutors of a person or different partners of an organi-
zation are not equally important, it is a good practice to keep track only of the
relevant contacts in order to reduce the maintenance effort.
Nonetheless, identifying the relevant contacts is not a simple task, because
they can change over time: an interlocutor or partner, which is important today
for a running activity, can become less interesting for the company when that
activity ends. As a result, whenever facing the decision of evaluating the relevance
of a contact, users are inclined to go for the most conservative choice, by keeping
memory of irrelevant contacts that will never be deleted. As an example, a test
conducted between users with different functions and various communication
demands highlighted that only 19% of stored contacts was actually relevant [1].
This fact was noted also during the deploy of GeCo and we took advantage of
the initial loading for “cleaning” the data from irrelevant contacts.
Another relevant aspect in managing contacts is data recency. It must be
noted that a significant part of contact information has a dynamic nature (e.g.,
2nd International ExpertFinder Workshop (FEWS2007) 67
Towards a Semantic Contact Management 5
a person can change his telephone number, move to a different address, leave
his occupation for a new job, etc.). Therefore, it is crucial to have up-to-date
contact information.
This requirement has a strong impact over the management of contacts,
especially when data is inserted manually by users. How can the system keep
the information always up-to-date? How can a user, when accessing some contact
data, verify whether those data are still valid? This problem arises also when a
single person is responsible for the contact management, but it is more strongly
perceived when the approach to the data editing and update is collaborative,
because data could be inserted by a different - and perhaps unknown - user
(e.g., who inserted this piece of information? can I trust that editor?).
3.3 Tool and Model Extensibility
Even in a middle-sized company, we can identify different needs in the Contact
Management, coming from different classes of users. Directory Board, Commu-
nication, Marketing, Technical Support: those units have different requirements
and are interested in different kinds of information when dealing with contacts.
A widespread solution consists in the use of different, independent tools that
respond to specific demands. This, however, leads to data fragmentation which,
in turn, hampers the development of new opportunities and the efficiency deriv-
ing from a unitary and overall vision.
On the other hand, by adopting a logically centralized solution, the different
requisites must be supported by a single tool, enabling each class of users to
store and manage the contact information of its interest. This means that the
tool, for each contact, will manage:
1. a baseline set of properties, which are in common for the various users (e.g.,
name, affiliation, telephone, email, etc.);
2. various sets of additional information, to support specific demands, to be
handled by different applications or to be used by different classes of users
(e.g., participation to projects or training courses, interest in specific prod-
ucts or services offered by the organization, etc.)2 .
Many requisites are typically not apparent or clear during the design phase and
often originates only after the adoption of the tool. As a consequence, the tool
and the underlying data model have to be extended in order to meet the new
requirements, with the risk of complex adaptations or refactorings, perhaps justi-
fied by the advantages of an integrated contact management approach. For those
reasons, the Contact Management tool is required to adopt an easily extensible
architectural solution, in terms of data schema and tool functionalities, so that
acquisition and access to additional data can be provided at “run-time”, when
the application is already in the production environment.
2
Particular care must be taken, however, when adding functionalities to a Contact
Management tool, in order to prevent the “overloading” of the tool with the business
logic specific of conceptually different tools.
68 2nd International ExpertFinder Workshop (FEWS2007)
6 Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
To complicate things further, to extend the model or the tool it is often
necessary to integrate or link different information sources or other internal
applications (e.g., a product DB), which often are pre-existing and cannot be
modified (e.g., when they are strictly connected to the core business of the com-
pany). Nonetheless, in order to fulfil the necessary functions, the tool must be
able to integrate data from those sources, or to put the contacts in connection
to information stored in the sources.
3.4 Data Fruition
Once we gathered a large amount of complex data which respond to the different
requirements, and once we found a solution to manage their consistency and
update, we still have to enable an effective and efficient fruition by the final
users of the Contact Management system.
In this regard, we can identify three main requisites:
1. Contact Organization: the different users have specific demands in organizing
their contacts, for example they wish to classify or to group them in cate-
gories, or they need to define lists of addresses for specific objectives, like
distribution lists for advertising. In the most common Contact Management
tools, there is a little support for contact organization, because the users
operate in different “fluid” contexts, in which teams, activities, projects and
associations change over time.
2. Contact Search: when the number of contacts is very high, it can be difficult
to perform effective searches over them. We can further distinguish between
two kinds of search:
– Formal or Directed Search (cf. also [2]), when the user is looking for
a specific contact of which he knows, for example, name and surname;
the input information can be incomplete or lead to multiple contacts
selection (e.g., a lookup for “John Smith” which results in a hundred
matches): the tool must ease the individuation of the “right” result (e.g.,
by enabling a search refinement);
– Free or Indirected search, when the user is looking for contacts with
specific characteristics (e.g., all the employees of company X, all the
contacts whose birthday is tomorrow, etc.); a frequent and crucial need
is the search of contacts by expertise area (see also [3]).
3. Access or Reuse of Contact Information: especially in the everyday use of
PIM tools, it frequently happens that the user wishes to reuse a selected
contact, for example by importing it in the address book of his mail client
or by using directly its email address to send a message. The integration
between the Contact Management system and other PIM tools (like the
mail client in the previous example) must be two-way, i.e. users should be
also allowed to import contact information into the Contact Management
tool and integrate it with the possible pre-existing data, in order to avoid
replication or fragmentation of data over multiple tools.
2nd International ExpertFinder Workshop (FEWS2007) 69
Towards a Semantic Contact Management 7
3.5 Privacy and Security
Contacts are often a valuable asset of an organization and as such they should
be properly protected. Typically, contacts’ data may comprise confidential infor-
mation and its analysis could reveal important details about the organization,
its relationships and strategy.
As a consequence, access to (part of the) contacts or related information is
often restricted by security policies. For example, confidential telephone numbers
and personal information can be accessible only to selected users, or some infor-
mation, though public and not confidential, is editable only by a subset of users,
since it is strictly bound to specific demands. Moreover, it can be useful to let
users associate notes to a contact (e.g., memoranda, remarks about task progress,
comments and personal opinions on the person, etc.); in that case, those notes
must be considered private and be accessible only by their respective author.
Security constraints are in contrast with a purely collaborative approach,
nonetheless their satisfaction is essential to make organizations adopt the tool.
Therefore, a Contact Management tool must define and implement an appropri-
ate model for access control and privacy preservation and must support users in
defining access policies and problem-solving guidelines (e.g., whenever a contact
is duplicated by a user that had no access to the pre-existing information).
4 Adding “semantics” to a Contact Management
application
All the issues presented in the previous section arose when we designed and
developed the GeCo prototype. This experience taught us the problems, difficul-
ties and limits, arising in realizing a Contact Management application, which,
addressed with “traditional” approaches and technologies (as we initially did),
prevented us from getting a brilliant and comprehensive result in the end.
However, the lesson learned from this experiment, together with our knowl-
edge and experience about Semantic Web technologies, led us to several con-
siderations about what would represent the best possible solution for Contact
Management. We strongly believe that Contact Management could heavily ben-
efit from the adoption of a “semantic” approach and this is the main motivation
for writing this paper. Both current results from the Semantic Web field and
further development of standards, methods and techniques which are envisioned
in the research community can greatly improve Contact Management applica-
tions and help to achieve better results and provide new solutions to the different
challenges we introduced in section 3.
In the following, we follow this direction by investigating, for each issue in-
troduced in the previous section, the “semantic” solutions we foresee and the ad-
vantages they promise with regards to more traditional approaches. We present
the effects we can get with current Semantic Web technologies and solutions
(e.g. RDF, ontological models, the FOAF vocabulary), as well as the outcomes
we expect from the ongoing standardization efforts in the field (e.g. SPARQL,
RDFa, GRDDL, RIF); in the latter case, we try to outline our expectations and
demands.
70 2nd International ExpertFinder Workshop (FEWS2007)
8 Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
4.1 Semantics in Data Acquisition
A possible way to handle the consistency problem arising from manual editing
(duplicated data and concurrent updates, as outlined in 3.1) is to track all the
modifications occurring to contact data. More specifically, we designed the GeCo
system in order to keep trace of:
– Data Provenance, i.e. what data were inserted by which user; this enables a
user to ask directly to the author about the reliability and trustworthiness
of each piece of stored information;
– Update History, i.e. the “log” of updates (e.g., inserted values, date, editor);
this enables a correct versioning of data, with the consequent possibility of
roll-back in case of erroneous data update.
Representing and managing all the data described above revealed to be quite
troublesome in the architecture we chose, based on the use of relational DBs.
Therefore, in order to limit the complexity, we opted for a partial solution, by
keeping trace only of the last update editor and by storing within the history
only the complete contact information rather that the single modified values.
However, a full solution to those problems would have been achieved quite
easily by representing information by means of RDF triples [4] described by an
ontology, because:
1. Data provenance and update history can be compared and re-conducted
to metadata associated to triples, using Named Graphs [5] or, with proper
care, reification [6]. In this way, we exploit RDF capabilities in (1) treating
and representing complex information in a homogeneous way with graphs of
triples and (2) working on data with a fine-grained granularity, by associ-
ating metadata to triples or groups of triples (the same technique is quite
troublesome, for example, in relational databases). With regards to data
provenance, we strongly support a wider adoption of provenance tracking
techniques and we look forward to seeing a progress in the standardization
of solutions like Named Graphs.
2. By using ontologies, we can formally describe integrity constraints and in-
ference rules, in order to assure the coherence of the knowledge base (e.g.,
we can exploit rules, based on properties values, to infer the equivalence of
duplicated contacts). In that respect, we foresee great improvements towards
a comprehensive solution through the standardization activities of RIF Core
and its dialects [7].
Regarding the reuse of existing data sources, RDF is well suited for data inte-
gration, which could be achieved through (1) wrapping external data sources by
means of mappers that expose a SPARQL [8] end-point, (2) integrating the dif-
ferent data simply by merging RDF graphs and, in case, (3) exploiting inference
rules to identify relations between different data or to state the equivalence of
data coming from different sources and describing different aspects of the same
resource.
Apart from the databases and legacy sources typically present in an organi-
zation, an interesting kind of source is represented by the profiles and electronic
2nd International ExpertFinder Workshop (FEWS2007) 71
Towards a Semantic Contact Management 9
business cards published by users on the Web (e.g. in their home page). The
importance of those sources is twofold: on the one hand, their use helps in re-
ducing the effort required for contact editing and maintenance; on the other
hand, they represent authoritative sources, since data is maintained directly by
their respective owners and we can usually rely on its correctness and recency
(as discussed thoroughly in section 4.2).
To enable the system to deal with those external sources, the information
must be expressed in a standard format. In this regard, there are some pro-
posals for standard like vCard [9], but we believe that better results can be
obtained with Semantic Web approaches which allow for making data semantics
explicit and therefore machine processable. Pragmatically, contact information
can be encoded directly in RDF by some reference vocabulary or ontology (e.g.,
FOAF [10]). This information could then be published on-line as Linked Data [11]
or even incorporated in the (X)HTML pages (e.g., via RDFa [12] or Microfor-
mats3 ) and extracted thereof in an automatic way (e.g., via GRDDL [13]). With
this solution, each contact can be identified and referred to by a dereferenceable
URI, so that the Contact Management system could (semi-)automatically access
the most up-to-date information whenever needed.
4.2 Semantics in Data Relevance and Recency
In Contact Management, the problems of data relevance and recency are crucial.
In the GeCo prototype system, we identified two possible families of solutions
to manage the selection and update of relevant contacts:
1. A technical solution (based on the provenance data and update history main-
tained by the system, see 4.1) tracks the last user and the last modification
date of a contact, in order to give a rough hint about data recency. Actually,
this is not a comprehensive solution, since it helps only in identifying the
user to ask to about the “freshness” of data.
2. An organizational solution can be achieved by defining proper guidelines to
associate each contact to an internal responsible editor (e.g. the person who
initially inserted it) to whom the update of contact information is delegated.
This solution is partial too, since it relies upon users’ good will to follow the
guidelines; of course it would be possible to code the guideline enforcement
within the system, but this would make the solution too stiff.
None of the previous solutions proved to be completely effective. A further step
toward a more comprehensive solution, proposed in [1], consists in automatically
selecting the relevant contacts, in order to (visually) filter out the other irrelevant
ones. This selection prevents the “waste” of time and effort related to their
maintenance. In the cited work, the relevance of a contact is related to different
factors belonging to two categories:
– Communication History, which includes parameters like frequency, recency,
longevity, presence of long-term interactions, reciprocity;
3
http://microformats.org
72 2nd International ExpertFinder Workshop (FEWS2007)
10 Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
– Communication Style, which is about the attitude of a user towards commu-
nication and contact management, deriving from his interaction demands.
The automatic selection of relevant contacts is a feature that we cannot disregard
and that can be facilitated by the use of Semantic Web technologies. First of all,
it enables the visual interface to hide the irrelevant contacts, in order to reduce
the informational overload for the users. This result can be achieved by selecting
the RDF nodes to be visualized or by querying the contacts’ RDF information
to extract only the desired metadata. In the second place, this feature can be
the basis for advanced functionalities like alerting, filtering and prioritization
for inward communication, or reminding to cultivate relationships (e.g., alerting
a user to contact a person that he did not hear from recently). We can get
this result by defining opportune inference rules to determine the information
to be notified or suggested to the user. A related work is the Semantic Email
Addressing proposed in [14], which suggest a way to address email to a targeted
audience based on the “semantics” of the group of addressees.
Finally, another way to select the relevant information and to keep it up-to-
date, as well as to simplify contact update and editing tasks, consists in exploiting
and integrating external information sources (as introduced in 4.1), which can be
either more up-to-date or authoritative, when they represent the “official” source
for data about a contact (e.g., personal home pages which publishes personal
data, telephone numbers, emails, etc.). This approach requires a support from
outside the organization, but can achieve better results or, at least, more reliable
data.
4.3 Semantics in Tool and Model Extensibility
The requisites we drew in section 3.3 imply the need for extending the infor-
mation managed by the Contact Management tool, after its development or
deployment, and in case directly at run-time.
The information extension can be applied at different levels: on the data
layer, on the application layer and on the user interface level.
At data level, extending the information means enlarging the model, by
adding new types of information and by integrating or linking to external data
sources. To this end, a Semantic Web approach appears to be particularly suit-
able and useful: enlarging the model becomes concrete by extending the ontology
(adding new concepts and properties or importing other ontologies). Moreover,
integrating external data sources could be easily achieved by using RDF (see
4.1). Data integration could be interesting also in the opposite direction, by
letting other systems to access information managed by the Contact Manage-
ment tool; the enforceability of this approach, however, heavily depends on the
characteristics of the external, pre-existing and legacy systems.
At application level, extending the information means supporting new oper-
ations and functionalities (e.g., data mining, decision-support analysis, stickers
printing, etc.). Those features often result in separate applications because they
are strictly related to a specific user cluster or intended for specialized demands.
Nonetheless, adopting a Semantic Web approach, the design and development of
2nd International ExpertFinder Workshop (FEWS2007) 73
Towards a Semantic Contact Management 11
those applications are simplified, because they can rely upon an (RDF) reposi-
tory of integrated data, described by an ontology which formalizes their seman-
tics and which can be re-used at application level. Besides data aggregation,
the tool may also “export” (e.g. through Web Services) several general-purpose
operations, which can be exploited by external applications.
At user interface level, extending the information means supporting new
data visualization and editing. In this regard, the same (RDF) model used to
represent data and the ontological formalization used to express their semantics
can be exploited in order to (semi-)automatically generate the user interface. The
simplest solution is the adoption of RDF Browsers, like Tabulator [15], Disco [16]
or Rhizomer [17], which automatically generates an HTML presentation starting
from RDF (linked) data. A more evoluted approach is represented by Semantic
Web Portals [18] and by Web frameworks that exploit an ontological model to
determine resources’ presentation and navigational patterns (like in [19]), based
on a model-driven approach in which the model is expressed by the ontology.
4.4 Semantics in Data Fruition
For what regards contact organization, an effective “semantic” approach to im-
prove data access and fruition is tagging, i.e., the possibility to classify contacts
along pre-defined or user-generated categories. Those classifications can then be
used for searching, together with other contact-specific information.
Contact search can be successfully solved by adopting Semantic Web ap-
proaches:
– Formal or Directed Search implies the use of a search engine; having an
ontology of the managed data, a semantic search engine can be employed
(like, for example, Squiggle [20]). Differently from a syntactic search engine,
it can support the user in disambiguating his search criteria to smoothly get
to the desired contact information.
– Free or Indirected Search, on the other hand, requests for selecting, grouping
and browsing through contacts on the basis of the associated information.
Also in this case, the presence of an ontology enables semantic navigation
and faceted browsing solutions (like BrowseRDF [21] or /facet [22]). Those
approaches let the user to limit (or extend) the focus on specific contact
categories, which become different as the navigation continues, always sup-
ported by the application which takes care of avoiding the user to reach a
“deadlock”.
For what regards the access or reuse of contact information in everyday PIM
tools, possible solutions heavily depend on the features of different tools. We can
imagine the design of plug-ins for the most commonly used tools or, whenever
possible, the exploitation of importing features to migrate data to them.
4.5 Semantics in Privacy and Security
The privacy and security issues discussed in section 3.5 ask for the adoption
and the enforcement of proper access control mechanisms, controlled by flexible
security policies defined by system administrators and data owners.
74 2nd International ExpertFinder Workshop (FEWS2007)
12 Irene Celino, Francesco Corcoglioniti, and Emanuele Della Valle
This access control model should be focused on data access rights (read
and update operations) and should be aimed at supporting the definition of
access policies, specifying the users allowed to access or update a particular
contact or kind of information. As a general rule-of-thumb, we propose to define
access rights and policies in terms of user groups (e.g., the whole staff working
on a particular project), while the object of those policies can be identified in
one or more contacts or in a set of cross-over properties over all the contacts
(e.g., contacts’ birthday can be accessed only by the Communication department
which is in charge of sending greetings messages).
The proposed access control system can exploit the common RDF model and
the availability of ontologies which formalize the meaning of data. For example,
policy rules could be expressed through a rule language, while specific access
rights could be associated to contact “triples” through the use of Named Graphs,
in addition to provenance information and update history (cf. section 4.1). Fi-
nally, data ontology can be used as a basis to express access policies, by associat-
ing specific rules to some contact classes or to their properties, therefore defining
the user groups in terms of their “semantics”.
Generally speaking, the contact data maintained by the tool could be seen
as a (logically) centralized RDF repository, which can be protected through the
use of an access control framework for RDF stores, like the ones proposed in [23]
and [24]. Those frameworks support the definition of rule based policies, which
control the execution of the fundamental repository operations (insert, remove
and read operations) and consider also the case of triggered reasoning that can
result in adding, deleting or retrieving additional information.
5 Conclusions and Future Work
In this paper, we presented our analysis of the needs and requirements of Contact
Management, on the basis of previous experience with our GeCo prototype.
It is quite well-known that today companies cannot miss a proper and care-
ful management of their contacts, in order to make their network grow and to
cultivate a good relationship with their business partners. People clearly per-
ceive that “knowing who you know” and finding the right contacts to start a
cooperation with (e.g., finding an expert in a specific field) are becoming more
and more crucial in today’s business.
We explained how a Contact Management application aims at solving a real-
world problem which becomes more and more apparent every day, with the birth
and spreading of new systems aimed at supporting people in keeping trace of
their existing contacts and to exploit the opportunity of finding new ones (like
LinkedIn, for example). However, neither those social networking systems nor
the widespread PIM tools or email clients we everyday use are able to give a
complete answer to the general question of Contact Management. A compre-
hensive solution can come only if a tool succeeds in supporting not only the
editing, storage and search for contacts, but also the integration with existing
and running systems and processes.
2nd International ExpertFinder Workshop (FEWS2007) 75
Towards a Semantic Contact Management 13
Contact Management is a data-intensive field, where information semantics
plays a key role in supporting the effective acquisition, management and retrieval
of contacts. In this sense, we believe that the adoption of “semantic” technologies
could enable more sophisticated functionalities, such as automatic contact clas-
sification, identification of potential partners and planning of a more targeted
and effective communication.
Moreover, personal information about an individual is spread today in sev-
eral, independent data sources: each time we establish a work relationship or
register for a service, we usually have to communicate our personal information.
This represents a cost, which increases when we want or need to keep this in-
formation up-to-date (e.g. when we expect to be contacted by the interlocutor).
The exposed considerations lead us to believe that Contact Management could
be a valuable use case for the evaluation of Semantic Web technologies.
In the next future, we are planning to extend the GeCo prototype through the
progressive adoption of the semantic approaches highlighted in this paper. We
would like also to move toward the use of published user profiles as a source for
contacts. To this end, we could initially support the acquisition of foaf profiles,
because of their wide adoption (over 10’000’000 foaf profiles on the Web in 2005),
as well as the publication of a subset of the managed contacts as Linked Data.
Acknowledgments
We wish to thank the anonymous reviewers for their useful comments. This
research has been partially supported by the SEEMP EU-funded project (IST-
4-027347) and by the NeP4B Italian-funded FIRB project (MIUR-2005).
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