Physical Representation Of Data Research Articles

Encoding Variables, Evaluation Criteria, and Evaluation Methods for Data Physicalisations: A Review

Data physicalisations, or physical visualisations, represent data physically, using variable properties of physical media. As an emerging area, Data physicalisation research needs conceptual foundations to support thinking about and designing new physical representations of data and evaluating them. Yet, it remains unclear at the moment (i) what encoding variables are at the designer’s disposal during the creation of physicalisations, (ii) what evaluation criteria could be useful, and (iii) what methods can be used to evaluate physicalisations. This article addresses these three questions through a narrative review and a systematic review. The narrative review draws on the literature from Information Visualisation, HCI and Cartography to provide a holistic view of encoding variables for data. The systematic review looks closely into the evaluation criteria and methods that can be used to evaluate data physicalisations. Both reviews offer a conceptual framework for researchers and designers interested in designing and evaluating data physicalisations. The framework can be used as a common vocabulary to describe physicalisations and to identify design opportunities. We also proposed a seven-stage model for designing and evaluating physical data representations. The model can be used to guide the design of physicalisations and ideate along the stages identified. The evaluation criteria and methods extracted during the work can inform the assessment of existing and future data physicalisation artefacts.

Beyond Backtracking: Connections in Fine-Grained Concurrent Separation Logic

Concurrent separation logic has been responsible for major advances in the formal verification of fine-grained concurrent algorithms and data structures such as locks, barriers, queues, and reference counters. The key ingredient of the verification of a fine-grained program is an invariant, which relates the physical data representation (on the heap) to a logical representation (in mathematics) and to the state of the threads (using a form of ghost state). An invariant is typically represented as a disjunction of logical states, but this disjunctive nature makes invariants a difficult target for automated verification. Current approaches roughly suffer from two problems. They use backtracking to introduce disjunctions in an uninformed manner, which can lead to unprovable goals if an appropriate case analysis has not been made before choosing the disjunct. Moreover, they eliminate disjunctions too eagerly, which can cause poor efficiency. While disjunctions are no problem for automated provers based on classical (i.e., non-separating) logic, the challenges with disjunctions are prominent in the study of proof automation for intuitionistic logic. We take inspiration from that area—specifically, based on ideas from connection calculus , we design a simple multi-succedent calculus for separation logic with disjunctions featuring a novel concept of a connection . While our calculus is not complete, it has the advantage that it can be extended with features of the state-of-the-art concurrent separation logic Iris (such as modalities, higher-order quantification, ghost state, and invariants), and can be implemented effectively in the Coq proof assistant with little need for backtracking. We evaluate the practicality on 24 challenging benchmarks, 14 of which we can verify fully automatically.

Embedded Data Representations.

We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles are making it increasingly easier to display data in-context. While researchers and artists have already begun to create embedded data representations, the benefits, trade-offs, and even the language necessary to describe and compare these approaches remain unexplored. In this paper, we formalize the notion of physical data referents - the real-world entities and spaces to which data corresponds - and examine the relationship between referents and the visual and physical representations of their data. We differentiate situated representations, which display data in proximity to data referents, and embedded representations, which display data so that it spatially coincides with data referents. Drawing on examples from visualization, ubiquitous computing, and art, we explore the role of spatial indirection, scale, and interaction for embedded representations. We also examine the tradeoffs between non-situated, situated, and embedded data displays, including both visualizations and physicalizations. Based on our observations, we identify a variety of design challenges for embedded data representation, and suggest opportunities for future research and applications.

Investigating the Use of a Dynamic Physical Bar Chart for Data Exploration and Presentation.

Physical data representations, or data physicalizations, are a promising new medium to represent and communicate data. Previous work mostly studied passive physicalizations which require humans to perform all interactions manually. Dynamic shape-changing displays address this limitation and facilitate data exploration tasks such as sorting, navigating in data sets which exceed the fixed size of a given physical display, or preparing "views" to communicate insights about data. However, it is currently unclear how people approach and interact with such data representations. We ran an exploratory study to investigate how non-experts made use of a dynamic physical bar chart for an open-ended data exploration and presentation task. We asked 16 participants to explore a data set on European values and to prepare a short presentation of their insights using a physical display. We analyze: (1) users' body movements to understand how they approach and react to the physicalization, (2) their hand-gestures to understand how they interact with physical data, (3) system interactions to understand which subsets of the data they explored and which features they used in the process, and (4) strategies used to explore the data and present observations. We discuss the implications of our findings for the use of dynamic data physicalizations and avenues for future work.

Modeling and Querying Continuous Fields with OLAP Cubes

The notion of SOLAP (Spatial On-Line Analytical Processing) is aimed at exploring spatial data in the same way as OLAP operates over tables. SOLAP, however, only accounts for discrete spatial data. Current decision support systems are increasingly being needed for handling more complex types of data, like continuous fields, which describe physical phenomena that change continuously in time and/or space (e.g., temperature). Although many models have been proposed for adding spatial (continuous and discrete) information to OLAP tools, no one is general enough to allow users to just perceive data as a cube, and analyze any type of spatial data together with typical alphanumerical discrete OLAP data, using only the classic OLAP operators (e.g., Roll-up, Drill-down). In this paper the authors propose a model and an algebra supporting it, that allow operating over data cubes, independently of the underlying data types and physical data representation. That means, in this approach, the final user only sees the typical OLAP operators at the query level, whereas at lower abstraction levels the authors provide discrete and continuous spatial data support as well as different ways of partitioning the space. As far as the authors are aware of, this is the first proposal, which provides such a general framework for spatiotemporal data analysis.

Tangible props for scientific visualization: concept, requirements, application

In this paper, we explore the use of printed tangible props as input devices for scientific visualization. Three-dimensional printing technology is used to create a physical representation of data. The object is then used as a tangible input prop, which exactly matches the data. In addition, two-handed interaction with a stylus is performed on the prop without the use of buttons, instead relying on the detection of contact between the stylus and the prop through precise calibration and tracking. This allows the sense of touch to be harnessed to create a more efficient and natural interaction method for scientific visualizations in virtual and augmented reality. We explain the concept of tangible props and where it can be applied. We also consider the technical requirements of systems using such props. Finally, we present our example application, which uses printed tangible props for interactive measurement of marine coral data. The use of tangible props is found to improve the usability of the application.

A quality-of-service specification for multimedia presentations

The bandwidth limitations of multimedia systems force trade-offs between presentation-data fidelity and real-time performance. For example, digital video is commonly encoded with lossy compression to reduce bandwidth, and frames may be skipped during playback to maintain synchronization. These trade-offs depend on device performance and physical data representations that are hidden by a database system. If a multimedia database is to support digital video and other continuous media data types, we argue that the database should provide a quality-of-service (QOS) interface to allow application control of presentation timing and information-loss trade-offs. This paper proposes a data model for continuous media that preserves device and physical data independence. We show how to define formal QOS constraints from a specification of ideal presentation outputs. Our definition enables meaningful requests for endto-end service guarantees, while leaving the database system free to optimize resource management. We propose one set of QOS parameters that constitute a complete model for presentation error, and we show how this error model extends the opportunities for resource optimization.

On the use of dynamic feedback in knowledge base system design

The problems of the physical design of knowledge base systems is discussed. A basic architecture for adding monitoring and reorganization software to knowledge base management systems is presented. This software uses dynamic feedback from the system to restructure the physical representation of data. Examples of the incorporation of monitoring and reorganization software into existing systems are given.

Physical datarepresentation in a multiprocessor database machine

By using a multiprocessor to implement the lowest level of a relational database we want to achieve fast execution of database operations such as join, find, and update. But the potential speed improvements provided by a multiprocessor can only be achieved if one can construct algorithms and corresponding physical data representations that can utilize the potential. By choosing a particular representation, the grid file, and analyzing its behaviour, we want to point out the difficulties encountered in trying to achieve speed improvements from a multiprocessor.

Physical Datarepresentation in a Multiprocessor Database Machine

<p>By using a multiprocessor to implement the lowest level of a relational database we want to achieve fast execution of database operations such as join, find, and update.</p><p>But the potential speed improvements provided by a multiprocessor can only be achieved if one can construct algorithms and corresponding physical data representations that can utilize the potential.</p><p>By choosing a particular representation, the grid file, and analyzing its behaviour, we want to point out the difficulties encountered in trying to achieve speed improvements from a multiprocessor.</p>