Managed Forgetting to Support Information Management and Knowledge Work

Trends like digital transformation even intensify the already overwhelming mass of information knowledge workers face in their daily life. To counter this, we have been investigating knowledge work and information management support measures inspired by human forgetting. In this paper, we give an overview of solutions we have found during the last five years as well as challenges that still need to be tackled. Additionally, we share experiences gained with the prototype of a first forgetful information system used 24/7 in our daily work for the last three years. We also address the untapped potential of more explicated user context as well as features inspired by Memory Inhibition, which is our current focus of research.Comment: 10 pages, 2 figures, preprint, final version to appear in KI - K\"unstliche Intelligenz, Special Issue: Intentional Forgettin

Enabling entity-based aggregators for web 2.0 data

Selecting and presenting content culled from multiple heterogeneous and physically distributed sources is a challenging task. The exponential growth of the web data in modern times has brought new requirements to such integration systems. Data is not any more produced by content providers alone, but also from regular users through the highly popular Web 2.0 social and semantic web applications. The plethora of the available web content, increased its demand by regular users who could not any more wait the development of advanced integration tools. They wanted to be able to build in a short time their own specialized integration applications. Aggregators came to the risk of these users. They allowed them not only to combine distributed content, but also to process it in ways that generate new services available for further consumption. To cope with the heterogeneous data, the Linked Data initiative aims at the creation and exploitation of correspondences across data values. In this work, although we share the Linked Data community vision, we advocate that for the modern web, linking at the data value level is not enough. Aggregators should base their integration tasks on the concept of an entity, i.e., identifying whether different pieces of information correspond to the same real world entity, such as an event or a person. We describe our theory, system, and experimental results that illustrate the approach’s effectiveness

Adaptive ontology re-use: Finding and re-using sub-ontologies

Purpose - The discovery of the "right" ontology or ontology part is a central ingredient for effective ontology re-use. The purpose of this paper is to present an approach for supporting a form of adaptive re-use of sub-ontologies, where the ontologies are deeply integrated beyond pure referencing. Design/methodology/approach - Starting from an ontology draft which reflects the intended modeling perspective, the ontology engineer can be supported by suggesting similar already existing sub-ontologies and ways for integrating them with the existing draft ontology. This paper's approach combines syntactic, linguistic, structural and logical methods into an innovative modeling-perspective aware solution for detecting matchings between concepts from different ontologies. This paper focuses on the discovery and matching phase of this re-use process. Findings - Owing to the combination of techniques presented in this general approach, the work described performs in the general case as well as approaches tailored for a specific usage scenario. Research limitations/implications - The methods used rely on lexical information obtained from the labels of the concepts and properties in the ontologies, which makes this approach appropriate in cases where this information is available. Also, this approach can handle some missing label information. Practical implications - Ontology engineering tasks can take advantage from the proposed adaptive re-use approach in order to re-use existing ontologies or parts of them without introducing inconsistencies in the resulting ontology. Originality/value - The adaptive re-use of ontologies by finding and partially re-using parts of existing ontological resources for building new ontologies is a new idea in the field, and the inclusion of the modeling perspective in the computation of the matches adds a new perspective that could also be exploited by other matching approaches. © Emerald Group Publishing Limited

Finding Experts on the Semantic Desktop

Abstract. Expert retrieval has attracted deep attention because of the huge economical impact it can have on enterprises. The classical dataset on which to perform this task is company intranet (i.e., personal pages, e-mails, documents). We propose a new system for finding experts in the user’s desktop content. Looking at private documents and e-mails of the user, the system builds expert profiles for all the people named in the desktop. This allows the search system to focus on the user’s topics of interest thus generating satisfactory results on topics well represented on the desktop. We show, with an artificial test collection, how the desktop content is appropriate for finding experts on the topic the user is interested in.

Social recommendations of content and metadata

In this paper we present metadata based recommendation algorithms addressing two scenarios within social desktop communities: a) recommendation of resources from the co-worker's desktop, and b) recommendation of metadata for enriching the own annotation layer. Together with the algorithms we present first evaluation results as well as empirical evaluations showing that metadata based recommendations can be used in such distributed social desktop communities

Towards digital library mediation for web services

www.sts.tu-harburg.de Web services and related technologies are a ubiquitous topic within the IT community. Due to their flexible system composition characteristics these technologies can be considered a promising building block for the dynamic networking of people and organizations in our increasingly globalized and quickly changing economies. With the growing number of Web services we are in need of elaborate mechanisms or service location, selection, and access as well as for assuring service quality going far beyond the functionalities of service registries. Fortunately, digital library research and practice provides advanced concepts for these tasks. The paper discusses requirements imposed on content description, structuring, enrichment, and retrieval when considering services as a new type of library content and presents a blueprint for a Web service digital library aiming to support the match-making between service providers and potential service users. 1

Towards Concise Preservation by Managed Forgetting: Challenges and Opportunities: Paper - iPres 2013 - Lisbon

In human memory, forgetting plays a crucial role for focusing on important things and neglecting irrelevant details. In digital memories, the idea of systematic forgetting has found little attention, so far. At first glance, forgetting seems to contradict the purpose of archival and preservation. However, we are currently facing a tremendous growth in volumes of digital content. Thus, it becomes ever more important to focus, while forgetting irrelevant details, redundancies and noise. This holds true for better organizing the information space as well as in preservation management for making and revisiting decisions on what to keep. Therefore, we propose the introduction of the concept of managed forgetting as part of a joint information management and preservation management process in digital memories. Managed forgetting models resource selection as a function of attention and significance dynamics. Based on dynamic, multidimensional information value assessment it identifies information objects, e.g., documents or images of decreasing importance and/or topicality and triggers forgetting actions. Those actions include a variety of options, namely, aggregation and summarization, revised search and ranking behavior, elimination of redundancy, and finally, also deletion. In this paper, we present our vision for managed forgetting, discuss the challenges as well as our first ideas for its introduction, and present a case study for its motivation