How do we quantify biodiversity? All the evidence in one place.

Biodiversity is a multi-dimensional concept that is represented by a large variety of measures. This complexity and lack of consistency limits the development of a coherent scientific understanding of biodiversity and how properties, such as ecosystem services, may depend on it. Here, I demonstrate that the formal discipline of creating a relational database (RDB) for information about biodiversity and its measures, is a useful tool in organising such knowledge into coherent sense. Following steps of the logical database design and data normalization to build a RDB, results in a formal definition of biodiversity within a well defined concept structure; mapping rules between the concepts of biodiversity and entities of RDB and a consistent information structure - all in one place. I show how this is then used to support evidence-based objective statements about biodiversity

Sets and indices in linear programming modelling and their integration with relational data models

LP models are usually constructed using index sets and data tables which are closely related to the attributes and relations of relational database (RDB) systems. We extend the syntax of MPL, an existing LP modelling language, in order to connect it to a given RDB system. This approach reuses existing modelling and database software, provides a rich modelling environment and achieves model and data independence. This integrated software enables Mathematical Programming to be widely used as a decision support tool by unlocking the data residing in corporate databases

MODEL PILIHAN RUTE DISTRIBUSI BARANG ANTAR-PULAU PADA KORIDOR AMBON-MASOHI DI PROVINSI MALUKU

Penelitian ini dimaksudkan untuk memodelkan pilihan Rute Distribusi Barang (RDB) antar-pulau pada koridor Ambon-Masohi di Provinsi Maluku. Objek yang diteliti yaitu pengendara angkutan barang (truk) yang melalui RDB I (lintasan Hunimua-Waipirit) dan RDB II (lintasan Hunimua-Amahai). Metode yang digunakan adalah Regresi Linear Berganda untuk pemodelan Utilitas dan Regresi Logistik Binomial untuk pemodelan Probabilitas. Variabel yang dimodelkan, adalah: (1) Pilihan RDB (Y); (2) biaya penyeberangan (X1), waktu penyeberangan (X2) dan frekwensi penyeberangan (X3). Data primer diperoleh dari survei Stated Preference (SP) kepada 75 responden. Hasil pemodelan menemukan bahwa RDB I masih menjadi favorit pilihan distributor dibandingkan RDB II karena keunggulan pada atribut frekwensi penyeberangan. Untuk itu disarankan kepada pihak otoritas transportasi penyeberangan agar dapat meningkatkan infrastruktur penyeberangan pada lintasan Hunimua-Waipirit guna mendukung kelancaran distribusi barang pada lintasan tersebut, serta meningkatkan frekwensi penyeberangan pada RDB II menjadi 2 Round Trip