The long-term preservation of digital documents containing scientifically relevant data from measurements remains challenging. We focus on two critical aspects: first, the use of highly specialized--- sometimes proprietary and obsolete---formats; and second, the limited usefulness of raw data without contextual information. In the context of a field study on the preservation of gamma-spectroscopic food radioactivity measurements collected after the Chernobyl disaster in 1986, we examine these aspects and describe the problems encountered in an archival environment. We emphasize the implementation of the FAIR guiding principles for scientific data management and stewardship, 1 in particular the principle that "data are described with rich metadata" including "descriptive information about the context." We use the OAIS (Open Archival Information System) reference model as a methodological framework.

Abstract Purpose Recent advances in AI, especially in large language models, have created new opportunities to integrate human and artificial agents through shared linguistic capabilities. This paper presents a multi-agent organizational framework in which human agents, LLMs, and specialized agents (narrow AIs) collaborate via dynamic, topic-based group formation. Topic-driven interactions enable agents to coalesce around evolving interests, supported by threshold-based protocols for temporal adaptation, topic emergence, and participation. Methods Within our framework, human agents guide the overall system objectives, while consultant agents (LLMs) provide semantic analysis and mediation, and specialized agents perform focused domain tasks. By leveraging automated topic modeling, the approach eschews rigid ontologies and instead supports adaptive and interpretable content management. Mathematical properties ensure system coherence—across roles, tasks, and timescales—while allowing the natural evolution of interests and groups. Results We illustrate the framework’s versatility with example scenarios in emergency response, healthcare research, and financial decision-making, emphasizing how human decision-makers, LLM-based consultants, and specialized worker agents jointly fulfill complex goals through transparent topic alignment and threshold-driven coordination. This formalization advances human-computer interaction as a multi-agent phenomenon that integrates human insight with the strengths of next-generation AI models in a cohesive, evolving system.

The long-term lifecycle-related management of digital building information is essential to improve the overall quality of public built assets. However, this management task still poses great challenges for building authorities, as they are usually responsible for large, heterogeneous and long-lived built assets with countless of data sets and documents that are increasingly changing from analogue to digital representations. These digital collections are characterized by complex dependencies, by numerous different, sometimes highly specialized and proprietary formats and also by their inappropriate organization. The major challenge is to ensure completeness, consistency and usability over the entire lifecycle of buildings or their associated digital data and documents.

The DChanges series of workshops focuses on changes in all their aspects and applications: algorithms to detect changes, models to describe them and techniques to present them to the users are only some of the topics that are investigated. This year, we would like to focus on collaboration tools for non-textual documents.

The DChanges series of workshops focuses on changes in all their aspects and applications: algorithms to detect changes, models to describe them and techniques to present them to the final users are only some of the topics we investigate. The workshop is open to researchers and practitioners from industry and academia. This year, we would like to focus on the application of change-tracking and diff algorithms to documents that are collaboratively edited via the web. We will also follow up on the discussion of DChanges 2015 about algorithms and interfaces to better understand and exploit detected changes, and about standards for modeling and transmitting changes. Particular attention will also be given to the use of diff, change tracking, and versioning techniques in the field of digital humanities.

The DChanges series of workshops focuses on changes in all their aspects and applications: algorithms to detect changes, models to describe them and techniques to present them to the final users are only some of the topics we investigate. The workshop is open to researchers and practitioners from industry and academia.

With collaborative tools getting more and more widespread, users have started to become accustomized to features like automatic versioning of their documents or the visualization of changes made by other users. The research community, however, sees that the state of the current tools is seriously lack lusting. The second edition of the DChanges workshop focuses on these shortcomings, introducing new ways to produce version-aware documents and merge changes from multiple sources. Other aspects - in particular, the standardization of formats for tracking changes - are discussed, too.

Many people have approached the problem of investigating the evolution of documents and data from different perspectives, e.g. by tracking changes, versioning and diffing. The goal of this workshop is to share ideas, common issues and principles, and to foster research collaboration on these topics.

Keyword extraction is a common technique in the domain of information retrieval. Keywords serve as a minimalistic summary for single documents or document collections, enabling the reader to quickly perceive the main contents of a text. However, they are often not readily available for the documents of interest.

Auto-versioning file systems offer a simple and reliable interface to document change control. The implicit versioning of documents at each write access catches the whole evolution of a document, thus supporting regulatory compliance rules. Most existing file systems work on low abstraction levels and track the document evolution on their binary representation. Higher-level differencing tools allow for a far more meaningful change-tracking, though.

Many knowledge-based processes rely on XML-based office documents. Up to now, versioning and merging XML documents was a difficult and error-prone task, mostly done manually. The support by tools is still in its infancy. We have presented a novel approach to compare and merge XML documents in a reliable way using context fingerprints. In this demonstration, we show the application of our toolset to ODF documents using a new, simple, and user-friendly graphical user-interface.

XML-based documents play a major role in modern information architectures and their corresponding workflows. In this context, the ability to identify and represent differences between two versions of a document is essential. Several approaches to finding the differences between XML documents have already been proposed. Typically, they are based on tree-to-tree correction, or sequence alignment. Most of these algorithms, however, are too slow and do not support the subsequent merging of changes. In this paper, we present a differencing algorithm tailored to ordered XML documents, called DocTreeDiff. It relies on our context-oriented XML versioning model which allows for document merging, presented in earlier work. An empiric evaluation demonstrates the efficiency of our approach as well as the high quality of the generated deltas.

Different dialects of XML have emerged as ubiquitous document exchange formats. For effective collaboration based on such documents, the capability to propagate edit operations performed on a document is indispensable. In order to avoid the transmission of whole documents, deltas are used to describe these edit operations, allowing the construction of a new version of a document. However, patching a document with a delta it was not generated for is error-prone, and any insert or delete operations performed on the document are likely to affect all subsequent paths within that document.

Archivists and librarians face an ever increasing amount of digital material. Their task is to preserve its authentic content. In the long run, this requires periodic migrations (from one format to another or from one hardware/software platform to another). Document migrations are challenging tasks where tool-support and a high degree of automation are important. A central aspect is that documents are often mutually related and, hence, a document's semantics has to be considered in its whole context. References between documents are usually formulated in graph- or tree-based query languages like URL or XPath. A typical scenario is web-archiving where websites are stored inside a server infrastructure that can be queried from HTML-files using URLs. Migrating websites will often require link adaptation in order to preserve link consistency. Although automated and "trustworthy" preservation of link consistency is easy to postulate, it is hard to carry out, in particular, if "trustworthy" means "provably working correct". In this paper, we propose a general approach to semantically evaluating and constructing graph queries, which at the same time conform to a regular grammar, appear as part of a document's content, and access a graph structure that is specified using First- Order Predicate Logic (FOPL). In order to do so, we adapt model checking techniques by constructing suitable query automata. We integrate these techniques into our preservation framework [12] and show the feasibility of this approach using an example. We migrate a website to a specific archiving format and demonstrate the automated preservation of link-consistency. The approach shown in this paper mainly contributes to a higher degree of automation in document migration while still maintaining a high degree of "trustworthiness", namely "provable correctness".

We introduce a framework that supports archivists in planning and running migrations. The central idea is that -once relevant information pieces of digital documents are modeled -desired migration results can be specified by means of preservation constraints. From these constraint specifications we are able to derive migration algorithms that provably respect a set of document properties before (pre-conditions) and after migration (post-conditions). Underlying is the concept of Abstract State Machines (ASM) modeling archival states. Migrations are modeled as sequences of basic operations that change the archive's state while respecting userdefined constraints. Among others, our target scenarios comprise legal and medical documents where considerable property changes cannot be tolerated and where constraint preservation must hold over a long period of time.

Office applications such as OpenOffice and Microsoft Office are widely used to edit the majority of today's business documents: office documents. Usually, version control systems consider office documents as binary objects, thus severely hindering collaborative work. Since XML has become a de-facto standard for office applications, we focus on versioning office documents by structured XML version control approaches. This enables state-of-the-art version control for office documents.A basic prerequisite to XML version control is a diff algorithm, which detects structural changes between XML documents. In this paper, we evaluate state-of-the-art XML diff algorithms w.r.t. their suitability to OpenOffice XML documents and the future OASIS office document standard. It turns out that, due to the specific XML office format, a careful examination of the diff algorithm characteristics is necessary. Therefore, we identify important features for XML diff approaches to handle office documents. We have implemented a first OpenOffice versioning API that can be used in version control systems as a replacement for line-based or binary diffs, which are currently used.

Industrial requirements specifications suffer from consistency problems, particularly in multi-angular or temporal relationships between different specification results. Current consistency management tools generate too many repairs, lack support for temporal relationships, and are poorly integrated into development processes. In this paper we evaluate our consistency management method on how it improves quality of industrial specifications: we formalize (temporal) consistency rules and generate a few domain-specific repairs for inconsistencies. We demonstrate our method using an example specification. Since the effort for formalization is tunable to specific applications and our prototype shows satisfactory performance, we are confident that our contributions scale to an industrial setting.

Whenever a group of authors collaboratively edits interre-lated documents, semantic consistency is a major goal. Current document management systems (DMS) lack adequate consistency management facilities. We propose liberal use of formal consistency rules, which permits inconsistencies. In this paper we focus on deriving repairs for inconsisten-cies. Our major contributions are: (1) deriving (common) repairs for multiple rules, (2) resolving conflicts between repairs, (3) prioritizing repairs, and (4) support for partial inconsistency resolution, which resolves the most troubling inconsistencies and leaves less important inconsistencies for a later handling. The novel aspect of our approach is that we derive repairs from DAGs (directed acyclic graphs) and not from documents directly. That way the repository is locked during DAG generation only, which is performed incrementally.

Over the last decades, the amount of digital documents has increased exponentially. Nevertheless, traditional document engineering methods are applied. Even worse, the long-term preservation issues have been neglected in standard document life cycle implementations.Our digital (cultural) heritage is, therefore, highly endangered by the silent obsolescence of data formats, software and hardware. Severe losses of information already happened. It is high time to implement concrete solutions.Fortunately numerous institutions already target these issues. Moreover, with the OAIS reference model1 a rich standardized conceptual framework is available, which already serves as implementation basis.2This paper discusses an extension to the OAIS reference model and illustrates a prototype implementation of a document life cycle that is enriched by functions for long-term preservation.More precisely, this paper aims to provide first solutions to the following three problem areas:

When a group of authors collaboratively edits interrelated documents, consistency problems occur almost immediately. Current document management systems (DMS) provide useful mechanisms such as document locking and version control, but often lack consistency management facilities.If at all, consistency is "defined" via informal guidelines, which do not support automatic consistency checks.In this paper, we propose to use explicit formal consistency rules for heterogeneous repositories that are managed by traditional DMS. Rules are formalized in a variant of first-order temporal logic. Functions and predicates, implemented in a full programming language, provide complex (even higher-order) functionality. A static type system supports rule formalization, where types also define (formal) document models. In the presence of types, the challenge is to smoothly combine a first-order logic with a useful type system including subtyping. In implementing a tolerant view of consistency, we do not expect that repositories satisfy consistency rules. Instead, a novel semantics precisely pinpoints inconsistent document parts and indicates when, where, and why a repository is inconsistent.Our major contributions are (1) the use of explicit formal rules giving a precise (and still comprehensible) notion of consistency, (2) a static type system securing the formalization process, (3) a novel semantics pinpointing inconsistent document (parts) precisely, and (4) a design of how to automatically check consistency for document engineering projects that use existing DMS. We have implemented a prototype of a consistency checker. Applied to real world content, it shows that our contributions can significantly improve consistency in document engineering processes.

The heterogeneity of Web information services poses new problems in the processing of user queries over distributed federated data. It was recently proven that the query translation between two information services supporting all Boolean operators can be done in an optimal way. On the Web, however, the situation when at least one Boolean operator is not supported is frequent. We study the case where a Boolean user query cannot be directly translated and should be split into sub-queries. We propose two strategies for query subsumption and discuss in detail the strategy which minimizes the number of submitted sub-queries. We derive an appropriate query form for the minimal strategy and demonstrate how both translation strategies are implemented in the Knowledge Brokers system.

Summary form only given. The amount of information available from electronic sources on the World Wide Web and other on-line information repositories is highly heterogeneous and increasing dramatically. Tools are needed to extract relevant information from these repositories. The Constraint-Based Knowledge Brokers project (CBKB) at RXRC Grenoble realizes sophisticated facilities for efficient information retrieval, schema integration, and knowledge fusion. The current implementation of the CBKB research prototype involves three kinds of agents: a) users, who input queries and process answers (i.e., ranking, fusion) through a GUI; b) wrappers, capable of interrogating heterogeneous information sources, which can provide answers to elementary queries (essentially various public bibliographic catalogues available on the Web, as well as preprint archives and opera information repositories); c) brokers, which can manage complex queries (i.e., decompose a complex query, recompose the partial answers, synthesize a full answer) and which mediate between the GUI and the different wrappers. The core of the system is given by the brokers, which provide various important services such as intelligent caching, filtering and knowledge combination. Requests, intermediate information, and results are internally represented via feature constraints. Requests do not need to be fully defined; they may correspond to partial specifications of the requested information.