Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (schemas, catalogs, or other data structures) as input, and produces as output a mapping between corresponding nodes of the graphs. Depending on the matching goal, a subset of the mapping is chosen using filters. After our algorithm runs, we expect a human to check and if necessary adjust the results. As a matter of fact, we evaluate the ‘accuracy ’ of the algorithm by counting the number of needed adjustments. We conducted a user study, in which our accuracy metric was used to estimate the labor savings that the users could obtain by utilizing our algorithm to obtain an initial matching. Finally, we illustrate how our matching algorithm is deployed as one of several high-level operators in an implemented testbed for managing information models and mappings. 1.

Many problems encountered when building applications of database systems involve the manipulation of models. By “model, ” we mean a complex structure that represents a design artifact, such as a relational schema, object-oriented interface, UML model, XML DTD, web-site schema, semantic network, complex document, or software configuration. Many uses of models involve managing changes in models and transformations of data from one model into another. These uses require an explicit representation of “mappings ” between models. We propose to make database systems easier to use for these applications by making “model ” and “model mapping ” first-class objects with special operations that simplify their use. We call this capability model management. In addition to making the case for model management, our main contribution is a sketch of a proposed data model. The data model consists of formal, object-oriented structures for representing models and model mappings, and of high-level algebraic operations on those structures, such as matching, differencing, merging, function application, selection, inversion and instantiation. We focus on structure and semantics, not implementation. 1

We present a diff algorithm for XML data. This work is motivated by the support for change control in the context of the Xyleme project that is investigating dynamic warehouses capable of storing massive volume of XML data. Because of the context, our algorithm has to be very efficient in terms of speed and memory space even at the cost of some loss of "quality". Also, it considers, besides insertions, deletions and updates (standard in diffs), a move operation on subtrees that is essential in the context of XML. Intuitively, our diff algorithm uses signatures to match (large) subtrees that were left unchanged between the old and new versions. Such exact matchings are then possibly propagated to ancestors and descendants to obtain more matchings. It also uses XML specific information such as ID attributes. We provide a performance analysis of the algorithm. We show that it runs in average in linear time vs. quadratic time for previous algorithms. We present experiments on synthetic data that confirm the analysis. Since this problem is NPhard, the linear time is obtained by trading some quality. We present experiments (again on synthetic data) that show that the output of our algorithm is reasonably close to the "optimal" in terms of quality. Finally we present experiments on a small sample of XML pages found on the Web. 1

Archiving is important for scientific data, where it is necessary to record all past versions of a database in order to verify findings based upon a specific version. Much scientific data is held in a hierachical format and has a key structure that provides a canonical identification for each element of the hierarchy. In this article, we exploit these properties to develop an archiving technique that is both efficient in its use of space and preserves the continuity of elements through versions of the database, something that is not provided by traditional minimum-edit-distance diff approaches. The approach also uses timestamps. All versions of the data are merged into one hierarchy where an element appearing in multiple versions is stored only once along with a timestamp. By identifying the semantic continuity of elements and merging them into one data structure, our technique is capable of providing meaningful change descriptions, the archive allows us to easily answer certain temporal queries such as retrieval of any specific version from the archive and finding the history of an element. This is in contrast with approaches that store a sequence of deltas where such operations may require undoing a large number of changes or significant reasoning with the

Modern search engines answer keyword-based queries extremely efficiently. The impressive speed is due to clever inverted index structures, caching, a domain-independent knowledge of strings, and thousands of machines. Several research efforts have attempted to generalize keyword search to keytree and keygraph searching, because trees and graphs have many applications in next-generation database systems. This paper surveys both algorithms and applications, giving some emphasis to our own work.

Semistructured data may be irregular and incomplete and does not necessarily conform to a fixed schema. As with structured data, it is often desirable to maintain a history of changes to data, and to query over both the data and the changes. Representing and querying changes in semistructured data is more difficult than in structured data due to the irregularity and lack of schema. We present a model for representing changes in semistructured data and a language for querying over these changes. An important feature of our approach is that we represent and query changes directly as annotationson the affected data, instead of indirectly as the difference between database states. We describe the implementation of our model and query language. We also describe the design and implementation of a query subscription service that permits users to subscribe to changes in semistructured information sources. 1

XML has become the de facto standard format for web publishing and data transportation. Since online information changes frequently, being able to quickly detect changes in XML documents is important to Internet query systems, search engines, and continuous query systems. Previous work in change detection on XML, or other hierarchically structured documents, used an ordered tree model, in which left-to-right order among siblings is important and it can affect the change result. This paper argues that an unordered model (only ancestor relationships are significant) is more suitable for most database applications. Using an unordered model, change detection is substantially harder than using the ordered model, but the change result that it generates is more accurate. This paper proposes X-Diff, an effective algorithm that integrates key XML structure characteristics with standard tree-to-tree correction techniques. The algorithm is analyzed and compared with XyDiff [CAM02], a published XML diff algorithm. An experimental evaluation on both algorithms is provided.

On-line forums for the collaborative creation of bodies of information are a phenomenon of rising importance; the Wikipedia is one of the best-known examples. The open nature of such forums could benefit from a notion of reputation for its authors. Author reputation could be used to flag new contributions from low-reputation authors, and it could be used to allow only authors with good reputation to contribute to controversial or critical pages. A reputation system for the Wikipedia would also provide an incentive to give high-quality contributions. We present in this paper a novel type of contentdriven reputation system for Wikipedia authors. In our system, authors gain reputation when the edits and text additions they perform to Wikipedia articles are longlived, and they lose reputation when their changes are undone in short order. We have implemented the proposed system, and we have used it to analyze the entire Italian and French Wikipedias, consisting of a total of 691,551 pages and 5,587,523 revisions. Our results show that our notion of reputation has good predictive value: changes performed by low-reputation authors have a significantly larger than average probability of having poor quality, and of being undone.

XML documents on the web are often found without DTDs, particularly when these documents have been created from legacy HTML. Yet having knowledge of the DTD can be valuable in querying and manipulating such documents. Recent work (cf. [10]) has given us a means to (re-)construct a DTD to describe the structure common to a given set of document instances. However, given a collection of documents with unknown DTDs, it may not be appropriate to construct a single DTD to describe every document in the collection. Instead, we would wish to partition the collection into smaller sets of "similar" documents, and then induce a separate DTD for each such set. It is this partitioning problem that we address in this paper. Given two

We present a change-centric method to manage versions in a Web WareHouse of XML data. The starting points is a sequence of snapshots of XML documents we obtain from the web. By running a diff algorithm, we compute the changes between two consecutive versions. We then represent the sequence using a novel representation of changes based on completed deltas and persistent identifiers. We present the foundations of the logical representation and some aspects of the physical storage policy. The work presented here was developed in the context of the Xyleme project of massive XML warehouse for XML data from the Web. It has been implemented and tested. We briefly discuss the implementation.