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... this kind of application would be monopolizing the user’s attention, e.g. like an email programm, it would be best used in full screen mode. That leads to the conclusion that it has to be a sovereign posture program [42]. This is also enforced by the fact that such an application would be used very often and therefore dominates the users attention as a primary tool. The fact of having an sovereign posture points out that a semantic desktop application has to be designed for optimal use by perpetual intermediates (see axiom in [42, chapter 8]). For future Semantic Applications, users will expect that the experience is similar to existing applications. An overview of existing applications is given in Figure 3. Based on the expectations of users we recommend: when building Semantic Desktop ...
Context 2
... program workflow itself is simple, and simplicity is a key feature of useful software. Systems that went beyond the simple workflow faced problems of complexity. For example, the gnowsis system started as a mixture of database, inference engine, user interface, and data integration architecture. The high goals of gnowsis lead to a complex architecture and performance problems which again forced us to refactor the project and split it into reusable components (a process that is not finished yet). Haystack also consists of database, user interface and domain specific (email, instant messaging, picture editing) functions. Haystack offers useful features and is a well administered project, but the demands on computing power, memory and disk storage are high. Also, users faced with such complex systems need a long training time to understand the system and benefit from them. Protégé gives an example of a clean architecture: provide a fast, extensible user interface for ontology editing and leave storage and inference to plugins and external services. The following description gives a rough image what a typical Semantic Desktop application of today looks like. We expect totally new interaction models for the future that extend this model, as already the example applications extend the model in different ways. Visual examples are given in fig. 3. As a reference we took these applications: Mindraider, Gnowsis, Aduna Autofocus, Haystack, PhotoStuff, Protégé, Personal Brain (thebrain.com), Windows Vista. We propose that the core parts of a user interface and application for information interaction are (see figure ...
Citations
... Personal Information Managers (PIMs) 1 consist of all kinds of tools dealing with personal information such as calendar applications, address books, bookmark managers, and email applications. The Semantic Desktop (SD) 2 [3,4] can be considered as a semantic web (SW)-based PIM dealing with machine-readable RDF-based metadata based upon a multi-layered ontology and modularized middleware [5]. We consider the SD as a past reference architecture. ...
A blog post at Google on 16 May 2012 with the title "Introducing the Knowledge Graph: things, not strings" represented one of the first references concerning the current definition of Knowledge Graphs. On the other hand, the article by Krisztian Balog et al. "Personal Knowledge Graphs: A Research Agenda" represented one of the very first references clearly defining the commonalities of Personal Knowledge Graphs (PKGs) such as presenting a "Spider-Web" graph layout having as the user its "center of gravity." To date, the literature related to PKGs is currently scarce given that it is still a virgin and promising research field. In this chapter, we present a survey including a classification of different types of applications of PKGs, spanning from E-learning Systems to Personal Information Managers (PIMs), to the Decentralized Web (e.g. the "Social Linked Data" (SOLID) stack), and so on. This classification identifies nine overlapping categories given that PKGs may belong to one or more categories. In each classification, we focus/highlight common and outstanding architectural components as reference architectures for each category type. We end-up the chapter by including and suggesting a reference architecture depicting desired main components for a semantic web (SW)-based PKG.
... Such a personal or corporate KG is a core pillar of the Corporate Memory system and the PKA based on it. Especially solutions developed in our department involve the Semantic Desktop [60,180] as an ecosystem bridging users' local devices with the Corporate Memory residing on the intranet. Technically, the Semantic Desktop aims at bringing Semantic Web [29] technology to users' desktops. ...
... Deep Linking Desktop Resources Having personal KGs with personal concepts and their relationships help AI systems to understand the employees' workrelated domains. However, not all native documents on their desktops are associated with these concepts as intended by the Semantic Desktop vision [180]. To bridge this gap, we proposed a deep linking approach in Schröder et al. [190]. ...
This paper presents a retrospective overview of a decade of research in our department towards self-organizing personal knowledge assistants in evolving corporate memories. Our research is typically inspired by real-world problems and often conducted in interdisciplinary collaborations with research and industry partners. We summarize past experiments and results comprising topics like various ways of knowledge graph construction in corporate and personal settings, Managed Forgetting and (Self-organizing) Context Spaces as a novel approach to Personal Information Management (PIM) and knowledge work support. Past results are complemented by an overview of related work and some of our latest findings not published so far. Last, we give an overview of our related industry use cases including a detailed look into CoMem, a Corporate Memory based on our presented research already in productive use and providing challenges for further research. Many contributions are only first steps in new directions with still a lot of untapped potential, especially with regard to further increasing the automation in PIM and knowledge work support.
... One approach lies in the development of a Semantic Desktop, which aims at deriving and representing a user's mental (work) model and embedding it in the user's desktop environment (for an overview see Sauermann et al., 2005). The mental model is formally represented in a Personal Information Management Model (PIMO) representing a user's mental model as closely as possible in a machineunderstandable way in order to serve as a personal work assistant (Grimnes et al., 2009) and, thus, free the users of their mental load Sauermann et al., 2007;Maus et al., 2013). ...
Information overload resulting from the ever faster growing mass of digital data makes knowledge work more and more complex. Being able to not get distracted and focus on what is currently relevant consumes valuable cognitive resources. Support by intelligent assistance software might alleviate this problem. We report two experiments that addressed this challenge by examining how context-based assistance may provide more available cognitive resources. Experiment 1 focused on work within a single context. Results indicate that external relevance classification can improve memory for content classified as currently more relevant. Experiment 2 focused on switching between two different contexts and shows that cognitive performance after context switches can be enhanced by context-specific structuring and saving a previous task status. Taken together, these results clearly demonstrate that automatic external information structuring by intelligent assistance software can protect knowledge workers from information overload by lightening their cognitive load and, thus, help improve cognitive performance.
... Cole, 2005;Ghorashi & Jensen, 2012;Kim & Croft, 2010;W. Liu, Rioul, McGrenere, Mackay, & Beaudouin-Lafon, 2018;Sauermann, Bernardi, & Dengel, 2005;Seenu, Rao, & Padma, 2014) or applying semantic search to the desktop (Adrian, Klinkigt, Maus, & Dengel, 2009;Handschuh, Möller, & Groza, 2007;Sauermann et al., 2006), for example by using semantic attributes to enhance search ranking (Chirita, Costache, Nejdl, & Paiu, 2006). Others, however, have sought to support specific search contexts, such as finding similar or duplicate files (Manber, 1994) or supporting search with a more interactive interface and drawing on a detailed file metadata index (G. ...
... ),Kim and Croft (2010), G.Liu, Jiang, and Feng (2017), W.Liu, Rioul, McGrenere, Mackay, and Beaudouin-Lafon (2018),Manber (1994),Sauermann, Bernardi, and Dengel (2005),Sauermann et al. (2006),Seenu, Rao, and Padma (2014) improved cloud and file sharing (7) Bergman, Whittaker, and Frishman(2018), W. Jones, Thorsteinson, Thepvongsa, and Garrett (2016), C. C. Marshall, Wobber, Ramasubramanian, and Terry (2012), Prinz and Zaman (2005), Rode et al. (2006), S. Voida, Edwards, Newman, Grinter, and Ducheneaut (2006), Whalen, Toms, and Blustein (2008) enriched file or folder metadata (6) He, Li, and Shen (2013), W. ...
Computer users spend time every day interacting with digital files and folders, including downloading, moving, naming, navigating to, searching for, sharing, and deleting them. Such file management has been the focus of many studies across various fields, but has not been explicitly acknowledged nor made the focus of dedicated review. In this article we present the first dedicated review of this topic and its research, synthesizing more than 230 publications from various research domains to establish what is known and what remains to be investigated, particularly by examining the common motivations, methods, and findings evinced by the previously furcate body of work. We find three typical research motivations in the literature reviewed: understanding how and why users store, organize, retrieve, and share files and folders, understanding factors that determine their behavior, and attempting to improve the user experience through novel interfaces and information services. Relevant conceptual frameworks and approaches to designing and testing systems are described, and open research challenges and the significance for other research areas are discussed. We conclude that file management is a ubiquitous, challenging, and relatively unsupported activity that invites and has received attention from several disciplines and has broad importance for topics across information science.
... As a prerequisite, we assume that users are aware of the concept "context" (Gomez-Perez et al., 2009) and that they successfully/willingly organize their data accordingly, e.g. information items are stored using a personal information model (PIMO) (Sauermann et al., 2007;Maus et al., 2013), which reflects a user's mental model in a semantic network and is based on the so-called Semantic Desktop approach (Sauermann et al., 2005). Thus, all things belonging to the same context in the user's mindcalendar events, files, emails, bookmarks, topics etc. (see Figure 3 for an example)are actually stored within a corresponding context in their PIMO. ...
Inhibition is one of the core concepts in Cognitive Psychology. The idea of inhibitory mechanisms actively weakening representations in the human mind has inspired a great number of studies in various research domains. In contrast, Computer Science only recently has begun to consider inhibition as a second basic processing quality beside activation. Here, we review psychological research on inhibition in memory and link the gained insights with the current efforts in Computer Science of incorporating inhibitory principles for optimizing information retrieval in Personal Information Management. Four common aspects guide this review in both domains: 1. The purpose of inhibition to increase processing efficiency. 2. Its relation to activation. 3. Its links to contexts. 4. Its temporariness. In summary, the concept of inhibition has been used by Computer Science for enhancing software in various ways already. Yet, we also identify areas for promising future developments of inhibitory mechanisms, particularly context inhibition.
... information model (PIMO) (Maus et al., 2013;Sauermann et al., 2007), which reflects a user's mental model in a semantic network and is based on the so-called Semantic Desktop approach (Sauermann et al., 2005; most recent prototype in Jilek et al., 2018a). In the most recent implementation called cSpaces (short for Context Spaces Semantic Desktop; Jilek et al., 2018c), all things belonging to the same context in the user's mind-calendar events, files, e-mails, bookmarks, topics etc. (see Fig. 3 for an example)-are thus actually stored within a corresponding context in their PIMO. ...
Inhibition is one of the core concepts in Cognitive Psychology. The idea of inhibitory mechanisms actively weakening representations in the human mind has inspired a great number of studies in various research domains. In contrast, Computer Science only recently has begun to consider concepts such as digital forgetting or suppression of irrelevant information to complement activation and highlighting of relevant information. Here, we review psychological research on inhibition in memory and link the gained insights with the current efforts and opportunities in Computer Science of incorporating inhibitory principles for reducing information overload and improving information retrieval in Personal Information Management. Four common aspects guide this review in both domains: (i) the purpose of inhibition to increase processing efficiency; (ii) its relation to activation; (iii) its links to contexts; (iv) its temporariness. In summary, the principle of suppressing information has been used by Computer Science for enhancing software in some ways already. Yet, we consider how novel methods for reducing information overload can be inspired by a more systematic involvement of the inhibition concept.
... Since the early 2000s, there has been a lot of research on Semantic Desktop (SD) [8] systems. A survey covering several relevant approaches can be found in [2]. ...
Semantic services (e.g. Semantic Desktops) are still afflicted by a cold start problem: in the beginning, the user's personal information sphere, i.e. files, mails, bookmarks, etc., is not represented by the system. Information extraction tools used to kick-start the system typically create 1:1 representations of the different information items. Higher level concepts, for example found in file names, mail subjects or in the content body of these items, are not extracted. Leaving these concepts out may lead to underperformance, having to many of them (e.g. by making every found term a concept) will clutter the arising knowledge graph with non-helpful relations. In this paper, we present an interactive concept mining approach proposing concept candidates gathered by exploiting given schemata of usual personal information management applications and analysing the personal information sphere using various metrics. To heed the subjective view of the user, a graphical user interface allows to easily rank and give feedback on proposed concept candidates, thus keeping only those actually considered relevant. A prototypical implementation demonstrates major steps of our approach.
... The Semantic Desktop is a step towards addressing the problem of information overload on our desktop computers. Sauermann et al. [12] stated that the file system is one of the building blocks for a Semantic Desktop. Ontology-based file systems could enhance the capabilities of file systems [13]. ...
The organization of files in any desktop computer has been an issue since their inception. The file systems that are available today organize files in a strict hierarchy that facilitates their retrieval either through navigation, clicking directories and sub-directories in a tree-like structure, or searching (which allows for the finding of the desired files using a search tool). Research studies show that users rarely (4-15%) use the latter approach, thus leaving navigation as the main mechanism for retrieving files. However, navigation does not allow a user to retrieve files nonhierarchically, which makes it limited in terms of time, human effort and cognitive overload. To mitigate this issue, several Semantic File Systems (SFSs) have been periodically proposed that have made the nonhierarchical navigation of files possible by exploiting some basic semantics but no more than that. None of these systems consider aspects such as time, location, file movement, content similarity, territory, etc. together with learning from user file retrieval behaviors in identifying the desired file and accessing it in less time and with minimum human and cognitive efforts. Moreover, most of the available SFSs replace the existing file system metaphor, which is normally not acceptable to users. To mitigate these issues, this research paper proposes 360°-SFS that exploits the SFS Ontology to capture all the possible relevant file metadata and learns from user browsing behaviors to semantically retrieve the desired files both easily and timely. Based on user studies, the evaluation results show that the proposed 360°-SFS outperforms the existing traditional directory navigation and Recently Open Files.
... The number of application areas, in which users are supported by systems that operate in (near) real-time, grows: chatbots, digital companions, knowledge work support systems -just to name a few. Our particular scenario involves a system based on Semantic Desktop [16] technology, that semi-automatically re-organizes itself based on user context in order to better support knowledge work and information management activities [10]. We envision an intelligent, proactive assistance parallel to the actual work. ...
... Figure 8 additionally shows the results itemized by LD. If term and link match exactly (LD=0, which is the case for 69% of all annotations), all recognition rates are above 92% 16 . In LD ranges of LD=1 to LD=4 (11% of all annotations), HMT/CST's recall is close to 0%, whereas MLFST still has rates of 79%, 66%, 36% and 8%, respectively. ...
A growing number of applications users daily interact with have to operate in (near) real-time: chatbots, digital companions, knowledge work support systems -- just to name a few. To perform the services desired by the user, these systems have to analyze user activity logs or explicit user input extremely fast. In particular, text content (e.g. in form of text snippets) needs to be processed in an information extraction task. Regarding the aforementioned temporal requirements, this has to be accomplished in just a few milliseconds, which limits the number of methods that can be applied. Practically, only very fast methods remain, which on the other hand deliver worse results than slower but more sophisticated Natural Language Processing (NLP) pipelines. In this paper, we investigate and propose methods for real-time capable Named Entity Recognition (NER). As a first improvement step we address are word variations induced by inflection, for example present in the German language. Our approach is ontology-based and makes use of several language information sources like Wiktionary. We evaluated it using the German Wikipedia (about 9.4B characters), for which the whole NER process took considerably less than an hour. Since precision and recall are higher than with comparably fast methods, we conclude that the quality gap between high speed methods and sophisticated NLP pipelines can be narrowed a bit more without losing too much runtime performance.
https://arxiv.org/abs/1812.02119
... Semantic Desktop. The Semantic Desktop (SD) [18] is especially intended to capture knowledge that emerges from individuals and then spreads into groups like project teams. SD brings Semantic Web 5 technology to users' computing devices using a knowledge representation, i.e. giving resources unique identifiers (URIs) and allowing to make statements about them, e.g. using RDF 6 , resulting in a semantic graph. ...
Knowledge workers face an ever increasing flood of information in their daily lives. To counter this and provide better support for information management and knowledge work in general, we have been investigating solutions inspired by human forgetting since 2013. These solutions are based on Semantic Desktop (SD) and Managed Forgetting (MF) technology. A key concept of the latter is the so-called Memory Buoyancy (MB), which is intended to represent an information item's current value for the user and allows to employ forgetting mechanisms. The SD thus continuously performs information value assessment updating MB and triggering respective MF measures. We extended an SD-based organizational memory system, which we have been using in daily work for over seven years now, with MF mechanisms directly embedding them in daily activities, too, and enabling us to test and optimize them in real-world scenarios. In this paper, we first present our initial version of MB and discuss success and failure stories we have been experiencing with it during three years of practical usage. We learned from cognitive psychology that our previous research on context can be beneficial for MF. Thus, we created an advanced MB version especially taking user context, and in particular context switches, into account. These enhancements as well as a first prototypical implementation are presented, too.
https://arxiv.org/abs/1811.12177
