NoSQL data stores are commonly schema-less, providing no means for globally defining or managing the schema. While this offers great flexibility in early stages of application development, developers soon can experience heavy burden dealing with increasingly heterogeneous data. This paper targets schema evolution stores, complex task adapting and changing implicit structure stored. We discuss recommendations developer community on handling changes, introduce a simple, declarative language....

Zusammenfassung In der Ära rasanter technologischer Fortschritte erweisen sich traditionelle Methoden des Forschungsinformationsmanagements als unzureichend. Präsentiert wird eine Projektskizze, die das Konzept „Data Management 4.0“ einführt. Dieses nutzt Künstliche Intelligenz (KI), um Forschungsinformationssysteme signifikant zu verbessern. Durch Integration KI-gestützter Lösungen könnten Institutionen erhöhte Effizienz, Genauigkeit und optimale Ressourcenzuteilung bei Handhabung großer...

Data accumulating in data lakes can become inaccessible the long run when its semantics are not available. The heterogeneity of formats and sheer volumes collections prohibit cleaning unifying manually. Thus, tools for automated lake analysis great interest. In this paper, we target particular problem reconstructing schema evolution history from lakes. Knowing how is structured, structure has evolved over time, enables programmatic access to lake. By deriving a sequence versions, rather than...

This paper explores scalable implementation strategies for carrying out lazy schema evolution in NoSQL data stores. For decades, has been an evergreen database research. Yet new challenges arise the context of cloud-hosted backends: With all reads and writes charged by provider, migrating entire instance eagerly into a can be prohibitively expensive. Thus, migration may more cost-efficient, as legacy entities are only migrated case they actually accessed application. Related work shown that...

The use of Elastic Stack (ELK) solutions and Knowledge Graphs (KGs) has attracted a lot attention lately, with promises vastly improving business performance based on new insights better decisions. This allows organizations not only to reap the ultimate benefits data governance but also consider widest possible range relevant information when deciding their next steps. In this paper, we examine how management visualization are used in that ELK collect integrated from different sources one...

Building applications for processing data lakes is a software engineering challenge. We present Darwin, middleware that operate on variational data. This concerns with heterogeneous structure, usually stored within schema-flexible NoSQL database. Darwin assists application developers in essential and schema curation tasks: Upon request, extracts description, discovers the history of versions, proposes mappings between these versions. Users may interactively choose which are most realistic....

We demonstrate MigCast, a tool-based advisor for exploring data migration strategies in the context of developing NoSQL-backed applications. Users MigCast can consider their options evolving model along with legacy already persisted cloud-hosted production database. They explore alternative actions as financial costs are predicted respective to cloud provider chosen. Thereby they better equipped assess potential consequences imminent decisions. To this end, maintains an internal cost model,...

Abstract When NoSQL database systems are used in an agile software development setting, data model changes occur frequently and thus, is routinely stored different versions. The management of versioned leads to overhead potentially impeding the development. Several migration strategies exist that handle legacy differently during accesses, each which can be characterized by certain advantages disadvantages. Depending on requirements for application, we evaluate compare through metrics like...

When NoSQL database systems are used in an agile software development setting, data model changes occur frequently and thus, is routinely stored different versions. This leads to overhead affecting the particular, management of accesses. In this context, migration strategies exist, which characterized by certain advantages disadvantages. Using exactly that strategy whose characteristics match according scenario, depends on query workload, caused schema evolution, requirements for application...

Abstract Data-driven methods and data science are important scientific in many research fields. All approaches require professional engineering components. At the moment, computer experts needed for solving these tasks. Simultaneously, scientists from fields (like natural sciences, medicine, environmental engineering) want to analyse their autonomously. The arising task is development of tools that can support an automated curation utilisable domain experts. In this article, we will...

To provide good results and decisions in data-driven systems, data quality must be ensured as a primary consideration. An important aspect of this is cleaning. Although many different algorithms tools already exist for cleaning, an end-to-end solution still needed. In paper, we present our vision well-founded optimizer. contrast to studies that consider cleaning the context machine learning, approach focuses on various scenarios, such when preprocessing downstream analysis are separated. Our...

We address a practical challenge in agile web development against NoSQL data stores: Upon new release of the application, entities already persisted production no longer match application code. Rather than migrating all legacy eagerly (prior to release) and at cost downtime, lazy migration is popular alternative: When entity loaded by pending structural changes are applied. Yet correctly from several releases back, involving more one at-a-time, not trivial. In this paper, we propose holistic...