Justification for inclusion dependency normal form

Functional dependencies (FDs) and inclusion dependencies (INDs) are the most fundamental integrity constraints that arise in practice in relational databases. In this paper, we address the issue of normalization in the presence of FDs and INDs and, in particular, the semantic justification for Inclusion Dependency Normal Form (IDNF), a normal form which combines Boyce-Codd normal form with the restriction on the INDs that they be noncircular and key-based. We motivate and formalize three goals of database design in the presence of FDs and INDs: noninteraction between FDs and INDs, elimination of redundancy and update anomalies, and preservation of entity integrity. We show that, as for FDs, in the presence of INDs being free of redundancy is equivalent to being free of update anomalies. Then, for each of these properties, we derive equivalent syntactic conditions on the database design. Individually, each of these syntactic conditions is weaker than IDNF and the restriction that an FD not be embedded in the righthand side of an IND is common to three of the conditions. However, we also show that, for these three goals of database design to be satisfied simultaneously, IDNF is both a necessary and sufficient condition

Fast and Tiny Structural Self-Indexes for XML

XML document markup is highly repetitive and therefore well compressible using dictionary-based methods such as DAGs or grammars. In the context of selectivity estimation, grammar-compressed trees were used before as synopsis for structural XPath queries. Here a fully-fledged index over such grammars is presented. The index allows to execute arbitrary tree algorithms with a slow-down that is comparable to the space improvement. More interestingly, certain algorithms execute much faster over the index (because no decompression occurs). E.g., for structural XPath count queries, evaluating over the index is faster than previous XPath implementations, often by two orders of magnitude. The index also allows to serialize XML results (including texts) faster than previous systems, by a factor of ca. 2-3. This is due to efficient copy handling of grammar repetitions, and because materialization is totally avoided. In order to compare with twig join implementations, we implemented a materializer which writes out pre-order numbers of result nodes, and show its competitiveness.Comment: 13 page

Transforming N-ary relationships to database schemas: an old and forgotten problem

The N-ary relationships, have been traditionally a source of confusion and still are. One important source of confusion is that the term cardinality in a relationship has several interpretations, two of them being very popular. But none of the two approaches, nor the two together, allow us to express all the possible cardinality patterns. The transformations from all the possible relationships to database schemas have never been described by the existing literature. Using the 14 ternary patterns as example, we discuss these transformations particularly the transformations from the patterns ignored in the literature.Postprint (published version

Antioxidant edible films based on bacterial cellulose and tilapia gelatin skin peptides.

In this work antioxidant films (AF) based on bacterial cellulose nanofibers (BCNF) and fish skin gelatin peptides (AFSGP) were developed. AFSGP addiction up to ~44% contributes to increase antioxidant activity (Aa) of BCNF films. The films containing AFSGP and sorbitol presented similar opacity compared to BCNF films without AFSGP. Considering the compact nanostructure, Aa, water vapour permeability and thermal stability, BCNF/AFSGP films can be used as bioactive food packing.Editor: Raul Fangueiro. ICNF. 21, 22 e 23 de jun. 2017

Why is the snowflake schema a good data warehouse design?

Database design for data warehouses is based on the notion of the snowflake schema and its important special case, the star schema. The snowflake schema represents a dimensional model which is composed of a central fact table and a set of constituent dimension tables which can be further broken up into subdimension tables. We formalise the concept of a snowflake schema in terms of an acyclic database schema whose join tree satisfies certain structural properties. We then define a normal form for snowflake schemas which captures its intuitive meaning with respect to a set of functional and inclusion dependencies. We show that snowflake schemas in this normal form are independent as well as separable when the relation schemas are pairwise incomparable. This implies that relations in the data warehouse can be updated independently of each other as long as referential integrity is maintained. In addition, we show that a data warehouse in snowflake normal form can be queried by joining the relation over the fact table with the relations over its dimension and subdimension tables. We also examine an information-theoretic interpretation of the snowflake schema and show that the redundancy of the primary key of the fact table is zero

From ternary relationship to relational tables: a case against common beliefs

The transformation from n-ary relationships to a relational database schema has never been really fully analyzed. This paper presents one of the several ternary cases ignored by the ER-to-RM literature. The case shows that the following common belief is wrong: Given a set of FDs over a table resulting in a non-3NF situation, it is always possible to obtain a fully equivalent set of 3NF tables, without adding other restrictions than candidate keys and inclusion dependencies.Postprint (published version

Ensuring the existence of a BCNF-decomposition that preserves functional dependencies in O (N2) time

A simple condition is presented that ensures that a relation scheme R with a set F of functional dependencies has a Boyce-Codd normal form (BCNF)-decomposition that has the lossless-join property and preserves functional dependencies