From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web

In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these requirements. We demonstrate a conceptual implementation of OAI-ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for Information Science and Technology (JASIST

Assessing the Design of Web Interoperability Protocols

Existing Web interoperability protocols are, arguably, overly complex as a result of each protocol being designed by a different group, providing a single service, and having its own syntax and vocabulary. Some standards, such as RSS, are popular and are designed with simplicity in mind and include easy to understand documentation, which is a key reason for its high adoption levels. However, the majority of protocols are complex, making them relatively difficult for programmers to understand and implement and thus hampering communication between heterogeneous information systems. This paper proposes a possible new direction for high-level interoperability protocols by focusing on simplicity. The High-level Interoperability Protocol - Common Framework (HIP-CF) was designed and evaluated as a proof of concept that, if interoperability is simplified and it is made easier for programmers to understand and implement protocols, it could lead to having more interoperable systems as well as increased protocol adoption levels. Evaluation showed that this is a reasonable view and that there is a lot of room for improvement when it comes to interoperability protocols

Integrating institutional repositories into the Semantic Web

The Web has changed the face of scientific communication; and the Semantic Web promises new ways of adding value to research material by making it more accessible to automatic discovery, linking, and analysis. Institutional repositories contain a wealth of information which could benefit from the application of this technology. In this thesis I describe the problems inherent in the informality of traditional repository metadata, and propose a data model based on the Semantic Web which will support more efficient use of this data, with the aim of streamlining scientific communication and promoting efficient use of institutional research output

Report on shape analysis and matching and on semantic matching

In GRAVITATE, two disparate specialities will come together in one working platform for the archaeologist: the fields of shape analysis, and of metadata search. These fields are relatively disjoint at the moment, and the research and development challenge of GRAVITATE is precisely to merge them for our chosen tasks. As shown in chapter 7 the small amount of literature that already attempts join 3D geometry and semantics is not related to the cultural heritage domain. Therefore, after the project is done, there should be a clear ‘before-GRAVITATE’ and ‘after-GRAVITATE’ split in how these two aspects of a cultural heritage artefact are treated.This state of the art report (SOTA) is ‘before-GRAVITATE’. Shape analysis and metadata description are described separately, as currently in the literature and we end the report with common recommendations in chapter 8 on possible or plausible cross-connections that suggest themselves. These considerations will be refined for the Roadmap for Research deliverable.Within the project, a jargon is developing in which ‘geometry’ stands for the physical properties of an artefact (not only its shape, but also its colour and material) and ‘metadata’ is used as a general shorthand for the semantic description of the provenance, location, ownership, classification, use etc. of the artefact. As we proceed in the project, we will find a need to refine those broad divisions, and find intermediate classes (such as a semantic description of certain colour patterns), but for now the terminology is convenient – not least because it highlights the interesting area where both aspects meet.On the ‘geometry’ side, the GRAVITATE partners are UVA, Technion, CNR/IMATI; on the metadata side, IT Innovation, British Museum and Cyprus Institute; the latter two of course also playing the role of internal users, and representatives of the Cultural Heritage (CH) data and target user’s group. CNR/IMATI’s experience in shape analysis and similarity will be an important bridge between the two worlds for geometry and metadata. The authorship and styles of this SOTA reflect these specialisms: the first part (chapters 3 and 4) purely by the geometry partners (mostly IMATI and UVA), the second part (chapters 5 and 6) by the metadata partners, especially IT Innovation while the joint overview on 3D geometry and semantics is mainly by IT Innovation and IMATI. The common section on Perspectives was written with the contribution of all

Reasoning with Mixed Qualitative-Quantitative Representations of Spatial Knowledge

Drastic transformations in human settlements are caused by extreme events. As a consequence, descriptions of an environment struck by an extreme event, based on spatial data collected before the event, become suddenly unreliable. On the other hand, time critical actions taken for responding to extreme events require up-to-date spatial information. Traditional methods for spatial data collection are not able to provide updated information rapidly enough, calling for the development of new data collection methods. Reports provided by actors involved in the response operations can be considered as an alternative source of spatial information. Indeed, reports often convey spatial descriptions of the environment. The extraction of spatial descriptions from such reports can serve a fundamental role to update existing information which is usually maintained within, and by means of, Geographic Information Systems. However, spatial information conveyed by human reports has qualitative characteristics, that strongly differ from the quantitative nature of spatial information stored in Geographic Information Systems. Methodologies for integrating qualitative and quantitative spatial information are required in order to exploit human reports for updating existing descriptions of spatial knowledge. Although a significant amount of research has been carried on how to represent and reason on qualitative data and qualitative information, relatively little work exists on developing techniques to combine the different methodologies. The work presented in this thesis extends previous works by introducing a hybrid reasoning system--able to deal with mixed qualitative-quantitative representations of spatial knowledge--combining techniques developed separately for qualitative spatial reasoning and quantitative data analysis. The system produces descriptions of the spatial extent of those entities that have been modified by the event (such as collapsed buildings), or that were not existing before the event (such as fire or ash clouds). Furthermore, qualitative descriptions are produced for all entities in the environment. The former descriptions allow for overlaying on a map the information interpreted from human reports, while the latter triggers warning messages to people involved in decision making operations. Three main system functionalities are investigated in this work: The first allows for translating qualitative information into quantitative descriptions. The second aims at translating quantitative information into qualitative relations. Finally, the third allows for performing inference operations with information given partly qualitatively and partly quantitatively for boosting the spatial knowledge the system is able to produce

Reasoning with Mixed Qualitative-Quantitative Representations of Spatial Knowledge

Drastic transformations in human settlements are caused by extreme events. As a consequence, descriptions of an environment struck by an extreme event, based on spatial data collected before the event, become suddenly unreliable. On the other hand, time critical actions taken for responding to extreme events require up-to-date spatial information. Traditional methods for spatial data collection are not able to provide updated information rapidly enough, calling for the development of new data collection methods. Reports provided by actors involved in the response operations can be considered as an alternative source of spatial information. Indeed, reports often convey spatial descriptions of the environment. The extraction of spatial descriptions from such reports can serve a fundamental role to update existing information which is usually maintained within, and by means of, Geographic Information Systems. However, spatial information conveyed by human reports has qualitative characteristics, that strongly differ from the quantitative nature of spatial information stored in Geographic Information Systems. Methodologies for integrating qualitative and quantitative spatial information are required in order to exploit human reports for updating existing descriptions of spatial knowledge. Although a significant amount of research has been carried on how to represent and reason on qualitative data and qualitative information, relatively little work exists on developing techniques to combine the different methodologies. The work presented in this thesis extends previous works by introducing a hybrid reasoning system--able to deal with mixed qualitative-quantitative representations of spatial knowledge--combining techniques developed separately for qualitative spatial reasoning and quantitative data analysis. The system produces descriptions of the spatial extent of those entities that have been modified by the event (such as collapsed buildings), or that were not existing before the event (such as fire or ash clouds). Furthermore, qualitative descriptions are produced for all entities in the environment. The former descriptions allow for overlaying on a map the information interpreted from human reports, while the latter triggers warning messages to people involved in decision making operations. Three main system functionalities are investigated in this work: The first allows for translating qualitative information into quantitative descriptions. The second aims at translating quantitative information into qualitative relations. Finally, the third allows for performing inference operations with information given partly qualitatively and partly quantitatively for boosting the spatial knowledge the system is able to produce

Provenance-aware knowledge representation: A survey of data models and contextualized knowledge graphs

Expressing machine-interpretable statements in the form of subject-predicate-object triples is a well-established practice for capturing semantics of structured data. However, the standard used for representing these triples, RDF, inherently lacks the mechanism to attach provenance data, which would be crucial to make automatically generated and/or processed data authoritative. This paper is a critical review of data models, annotation frameworks, knowledge organization systems, serialization syntaxes, and algebras that enable provenance-aware RDF statements. The various approaches are assessed in terms of standard compliance, formal semantics, tuple type, vocabulary term usage, blank nodes, provenance granularity, and scalability. This can be used to advance existing solutions and help implementers to select the most suitable approach (or a combination of approaches) for their applications. Moreover, the analysis of the mechanisms and their limitations highlighted in this paper can serve as the basis for novel approaches in RDF-powered applications with increasing provenance needs

A Framework for Web Object Self-Preservation

We propose and develop a framework based on emergent behavior principles for the long-term preservation of digital data using the web infrastructure. We present the development of the framework called unsupervised small-world (USW) which is at the nexus of emergent behavior, graph theory, and digital preservation. The USW algorithm creates graph based structures on the Web used for preservation of web objects (WOs). Emergent behavior activities, based on Craig Reynolds’ “boids” concept, are used to preserve WOs without the need for a central archiving authority. Graph theory is extended by developing an algorithm that incrementally creates small-world graphs. Graph theory provides a foundation to discuss the vulnerability of graphs to different types of failures and attack profiles. Investigation into the robustness and resilience of USW graphs lead to the development of a metric to quantify the effect of damage inflicted on a graph. The metric remains valid whether the graph is connected or not. Different USW preservation policies are explored within a simulation environment where preservation copies have to be spread across hosts. Spreading the copies across hosts helps to ensure that copies will remain available even when there is a concerted effort to remove all copies of a USW component. A moderately aggressive preservation policy is the most effective at making the best use of host and network resources. Our efforts are directed at answering the following research questions: 1. Can web objects (WOs) be constructed to outlive the people and institutions that created them? We have developed, analyzed, tested through simulations, and developed a reference implementation of the unsupervised small-world (USW) algorithm that we believe will create a connected network of WOs based on the web infrastructure (WI) that will outlive the people and institutions that created the WOs. The USW graph will outlive its creators by being robust and continuing to operate when some of its WOs are lost, and it is resilient and will recover when some of its WOs are lost. 2. Can we leverage aspects of naturally occurring networks and group behavior for preservation? We used Reynolds’ tenets for “boids” to guide our analysis and development of the USW algorithm. The USW algorithm allows a WO to “explore” a portion of the USW graph before making connections to members of the graph and before making preservation copies across the “discovered” graph. Analysis and simulation show that the USW graph has an average path length (L(G)) and clustering coefficient (C(G)) values comparable to small-world graphs. A high C(G) is important because it reflects how likely it is that a WO will be able spread copies to other domains, thereby increasing its likelihood of long term survival. A short L(G) is important because it means that a WO will not have to look too far to identify new candidate preservation domains, if needed. Small-world graphs occur in nature and are thus believed to be robust and resilient. The USW algorithms use these small-world graph characteristics to spread preservation copies across as many hosts as needed and possible. USW graph creation, damage, repair and preservation has been developed and tested in a simulation and reference implementation

Proceedings of the 12th International Conference on Digital Preservation

The 12th International Conference on Digital Preservation (iPRES) was held on November 2-6, 2015 in Chapel Hill, North Carolina, USA. There were 327 delegates from 22 countries. The program included 12 long papers, 15 short papers, 33 posters, 3 demos, 6 workshops, 3 tutorials and 5 panels, as well as several interactive sessions and a Digital Preservation Showcase